JP7176075B1 - Information processing device, information processing method and information processing program - Google Patents

Abstract

An information processing device, an information processing method, and an information processing program that provide content indicating reasons for ranking are provided. In an information processing system (1) in which an external device (20) and an information processing device (100) are communicably connected via a network (N), the information processing device (100) includes an estimating unit (134) and a providing unit (136). have The estimating unit 134 estimates the reason for the order of the target transaction object, which is the transaction object displayed as the ranking, based on the transaction object information related to the profit transaction object. The provision unit 136 provides content indicating the reason for the target transaction estimated by the estimation unit 134 . [Selection drawing] Fig. 9

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

Conventionally, techniques for providing various information to users are known. For example, a technology is provided that provides a review document that is expected to be more useful to the user (for example, Patent Literature 1).

JP 2019-212083 A

However, the above conventional techniques have room for improvement. In the above-mentioned prior art, review documents are only provided to users. For example, when providing rankings for transaction objects, the user desires the reason why the transaction objects in the ranking have been ranked. There is a desire to provide content that indicates the reasons for the ranking.

The present application has been made in view of the above, and aims to provide an information processing device, an information processing method, and an information processing program capable of providing content indicating reasons for ranking.

An information processing apparatus according to the present application includes an estimation unit for estimating the reason for ranking of a target transaction object, which is a transaction object to be displayed as a ranking, based on transaction object information related to the transaction object, and the target transaction estimated by the estimation unit. and a providing unit that provides content indicating the target reason.

According to one aspect of the embodiment, it is possible to provide content indicating reasons for ranking.

FIG. 1 is a diagram illustrating an example of information processing executed by an information processing apparatus according to an embodiment; FIG. 2 is a diagram showing an example of content. FIG. 3 is a diagram showing an example of ranking of transaction targets from multiple perspectives. FIG. 4 is a diagram showing an example of search results and rankings. FIG. 5 is a diagram showing an example of search results and rankings. FIG. 6 is a diagram showing an example of search results and rankings. FIG. 7 is a diagram showing an example of search results and rankings. FIG. 8 is a diagram illustrating the concept of product-based ranking. FIG. 9 is a diagram illustrating a configuration example of an information processing system according to the embodiment; 10 is a diagram illustrating an example of a user information storage unit according to the embodiment; FIG. 11 is a diagram illustrating an example of a transaction target information storage unit according to the embodiment; FIG. 12 is a diagram illustrating an example of a content storage unit according to the embodiment; FIG. FIG. 13 is a flowchart illustrating an example of the flow of information processing executed by the information processing device. FIG. 14 is a flowchart illustrating an example of the flow of information processing executed by the information processing device. FIG. 15 is a flowchart illustrating an example of the flow of information processing executed by the information processing device. FIG. 16 is a flowchart illustrating an example of the flow of information processing executed by the information processing device. FIG. 17 is a flowchart illustrating an example of the flow of information processing executed by the information processing device. FIG. 18 is a flowchart illustrating an example of the flow of information processing executed by the information processing device. FIG. 19 is a flowchart showing an example of the flow of information processing executed by the information processing device. FIG. 20 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus.

Embodiments for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Further, each embodiment can be appropriately combined within a range that does not contradict the processing contents. Also, in each of the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

(embodiment)
[1. Example of information processing]
First, an example of information processing executed by the information processing apparatus 100 will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of information processing executed by an information processing apparatus 100 according to an embodiment. The information processing device 100 executes information processing regarding a transaction target traded in an electronic commerce (EC) service. Here, the transaction object is the use of goods or services. Transaction objects traded in electronic commerce services include transaction objects traded in various forms such as electronic shopping malls (online malls), online shopping sites, auction sites, and flea market sites. Note that FIG. 1 shows an example of information processing for a transaction target traded on an electronic shopping mall.

[1-1. Overview of information processing]
First, an overview of the flow of information processing performed by the information processing apparatus 100 will be described. The information processing device 100 provides information to the user using a search query (also simply referred to as “query”) input by the user using the terminal device 10 . Specifically, the information processing device 100 arranges a tab (also referred to as a "first tab") in which search results corresponding to a search query input by a user are arranged, and a ranking of transaction targets corresponding to the search query. tabs (also referred to as "second tabs"). Then, the information processing apparatus 100 provides content including the generated first tab and second tab. A flow of information processing performed by such an information processing apparatus 100 will be described with reference to FIG.

Note that FIG. 1 illustrates an example in which the information processing apparatus 100 functions as a search apparatus that provides search results to the terminal apparatus 10 used by a user who inputs a query. For example, the information processing apparatus 100 has a function as a search engine that executes a search process for transaction targets traded on an electronic shopping mall. For example, the information processing apparatus 100 has a database (also referred to as a “transaction target database”) in which transaction targets to be searched using queries are indexed and stored. Execute the search process as For example, the information of the transaction target database is stored in the storage unit 120 (see FIG. 9).

As described above, FIG. 1 illustrates a case where the information processing device 100 also functions as a search device, that is, the information processing device 100 and the search device are integrated. There may be. In this case, the information processing system 1 (see FIG. 9) includes a search device that performs search processing for queries and provides search services that provide search results. For example, the information processing device 100 transmits a query input by a user to a search device, receives search results from the search device, and transmits content generated using the search results to the terminal device 10 used by the user. do. For example, when the external device 20 is a search device, the information processing device 100 transmits a query input by a user to the external device 20, receives search results from the external device 20, and generates content using the search results. is transmitted to the terminal device 10 used by the user. The system configuration described above is merely an example, and the information processing system 1 may have any device configuration as long as it can provide desired information to the user who has entered the query.

First, the information processing device 100 acquires information about a user (also referred to as “user information”) from the external device 20 (step S1). The external device 20 transmits user information about the user to the information processing device 100 . For example, the external device 20 transmits user information including user attribute information to the information processing device 100 . For example, the attribute information includes various information such as information indicating demographic attributes such as age, gender, area of residence, and occupation, and information indicating psychographic attributes such as interests and lifestyles. Note that the attribute information is merely an example, and the user information may include any information as long as it relates to the user. For example, user information may include a history of user behavior, such as behavior on the Internet. For example, the user information may include a user's action history such as browsing history and purchase history of information on transaction targets in an electronic commerce service such as an electronic shopping mall.

In addition, the information processing device 100 acquires information about the transaction object (also referred to as "transaction object information") from the external device 20 (step S2). For example, the information processing device 100 acquires, from the external device 20, transaction target information of a transaction target to be traded on the electronic shopping mall. For example, the information processing device 100 acquires, from the external device 20, transaction target information of a transaction target that is being sold (exhibited) on the online shopping mall. For example, the information processing device 100 acquires transaction target information of a transaction target from the external device 20 every predetermined period.

Here, the transaction target information includes various information regarding the transaction target. For example, the transaction target information includes various information used to provide information on the transaction target. For example, the transaction target information includes the seller, the selling price, the image of the transaction target, the category, the title, the description, the payment method, the sales period, the number of sales, and the like.

Further, for example, the transaction target information includes the sales history of the transaction target. For example, the transaction target information includes information such as the number of reservations, the number of orders, the number of sales, and the order amount (sales) of the transaction target. In addition, for example, the transaction object information includes the period elapsed from the date and time when the transaction object was sold, the number of views of information indicating the transaction object (number of PV (page views)), the number of reviews of the transaction object, the evaluation of the transaction object, etc. information is included.

The transaction target information may also include information on external factors related to the transaction target. For example, transaction target information may include information posted on a transaction target on an SNS (Social Networking Service). For example, transaction target information may include posted information posted by a user on an SNS. For example, the posted information is text information posted by the user on Twitter (registered trademark), Facebook (registered trademark), Instagram (registered trademark), YouTube (registered trademark), etc., or image information such as images and videos. There may be. For example, the trading object information may include information on the number of searches for the trading object.

Further, the transaction target information may include information on internal factors related to the transaction target. For example, the transaction target information may include incentive information for the transaction target. For example, the transaction target information may include information on incentives given to the user for the transaction target. For example, the transaction target information may include coupon information for the transaction target. For example, the deal information may include price reduction information about the deal. Note that the above is only an example, and the transaction target information may include any information as long as it is information related to the transaction target.

In the above example, the information processing device 100 performs the acquisition process in steps S1 and S2. and target information may be obtained at the same time.

The information processing device 100 also receives a search query input by the user from the terminal device 10 (step S3). For example, the terminal device 10 transmits a search query input by the user to the information processing device 100 . For example, the terminal device 10 used by the user U1 transmits the search query input by the user U1 to the information processing device 100 . Thereby, the information processing apparatus 100 acquires the search query input by the user U1. In FIG. 1 , the user U1 inputs the search query “television” into the terminal device 10 , and the terminal device 10 transmits the search query “television” input by the user U1 to the information processing apparatus 100 . For example, the user U1 enters the search query "television" into an entry field for entering a search query such as the search box BX1 in FIG.

Then, the information processing apparatus 100 that has received the search query “television” performs processing for providing information to the user. In FIG. 1, the information processing apparatus 100 generates a search result through search processing using the search query "television" (step S4). The information processing device 100 extracts transaction target information corresponding to the search query "television" using information in the transaction target database. For example, the information processing apparatus 100 performs a search process on the transaction target database using the search query "television", and extracts transaction target information corresponding to the search query "television". For example, the information processing apparatus 100 extracts transaction target information including information such as a character string corresponding to the search query “television” in the transaction target information.

It should be noted that the extraction of information corresponding to the query is performed using conventional technology, and any processing may be used as long as the transaction target can be specified, and detailed description thereof will be omitted. Further, when the search process is performed by a device (search device) other than the information processing device 100, the information processing device 100 transmits the search query "television" to the search device, and the search result of the search query "television" is sent from the search device. receive. The information processing apparatus 100 generates search results for the search query "television" using the transaction target information extracted as information corresponding to the search query "television". For example, the information processing apparatus 100 generates the list information of the transaction object of the extracted transaction object information as the search result of the search query "television".

In addition, the information processing device 100 generates a ranking of transaction targets corresponding to the search query "television" (step S5). For example, the information processing apparatus 100 ranks each transaction target (also referred to as “ranking target”) included in the search results of the search process using the search query “television”. to generate a ranking. For example, the information processing device 100 calculates a score for each transaction target to be ranked, and generates a ranking of the transaction target using the calculated score. For example, the information processing apparatus 100 generates a ranking by assigning higher ranks in descending order of score.

For example, the information processing device 100 calculates the score of the transaction object based on the transaction object information regarding the transaction object. The information processing apparatus 100 receives transaction target information of a transaction target and calculates a score of the transaction target using a function (also referred to as a “score function”) that outputs the score of the transaction target. The information processing apparatus 100 calculates the score of the transaction target using a score function in which the output value increases as multiple factors such as the number of orders of the transaction target, the order value, and the number of views (number of PVs) increase. may

For example, the information processing device 100 multiplies each of a plurality of elements such as the number of orders, the amount of orders, and the number of views (number of PVs) of the transaction target by the weight (coefficient) of each element (also referred to as a "partial score"). ) to calculate the score of the transaction target. The information processing apparatus 100 may calculate the sum of the partial scores of each of the multiple elements of the transaction object as the score of the transaction object. The information processing device 100 may calculate the average of the partial scores of each of the multiple elements of the transaction object as the score of the transaction object.

In addition, the information processing device 100 calculates the score of the transaction target using aggregated values aggregated for each predetermined period for each of a plurality of factors such as the number of orders, the order amount, and the number of views (number of PVs) of the transaction target. You may The information processing apparatus 100 may calculate the score of the transaction object using a total value that is aggregated for each date for each of a plurality of elements of the transaction object. In this case, the information processing device 100 uses a value (also referred to as a “period score”) obtained by multiplying the aggregated value of a plurality of elements of the transaction target aggregated for each predetermined period by the weight (coefficient) of each element (also referred to as “period score”). A subject score may be calculated. The information processing apparatus 100 may calculate the score of the transaction target using a value obtained by multiplying the period score of each period by an attenuation coefficient according to the difference between the period and the time of calculation. The information processing apparatus 100 may calculate the score of the transaction target using a value obtained by multiplying the period score of each period by an attenuation coefficient whose value decreases in the past period.

Note that the above is merely an example, and the information processing apparatus 100 may use any information to calculate the score of the transaction target. The information processing apparatus 100 may correct the score of the transaction object using a coefficient based on the evaluation of the sales source (store) that sells the transaction object to the calculated score of the transaction object. The information processing apparatus 100 may correct the score of the transaction object by multiplying the calculated score of the transaction object by a coefficient based on the evaluation of the seller who sells the transaction object.

Then, the information processing apparatus 100 generates content to be provided to the user using the search result of the search query "television" and the ranking of the transaction target corresponding to the search query "television" (step S6). The information processing apparatus 100 generates content including a first tab in which the search results of the search query "television" are arranged and a second tab in which the ranking of the transaction target corresponding to the search query "television" is arranged.

Then, information processing apparatus 100 provides content including the generated first tab and second tab (step S7). The information processing apparatus 100 transmits the generated content including the first tab and the second tab to the terminal device 10 used by the user who entered the search query "television".

An example of content provided to the terminal device 10 will now be described with reference to FIG. FIG. 2 is a diagram showing an example of content. The content C1 in FIG. 2 includes a first tab content (not shown) in which the search results of the search query "television" are arranged, and a second tab content C2 in which the ranking of the transaction target corresponding to the search query "television" is arranged. content that contains In addition, the search query "television" input by the user is arranged in the search box BX1 of the content C1 in FIG.

In addition, the content C1 of FIG. 2 includes a first heading TB1 and a second heading TB2 for switching and displaying the first tab content and the second tab content C2. Either the first heading TB1 or the second heading TB2 can be selected, and in the display area AR1 of the content C1, the first tab content or Any of the second tab content is displayed.

In FIG. 2, the information processing apparatus 100 displays the first tab content, the second tab content C2, and the first heading TB1 and the second heading TB2 for switching and displaying the first tab content and the second tab content C2. Generate content C1 that includes: Then, the information processing apparatus 100 provides content including the first tab content, the second tab content C2, and the first heading TB1 and the second heading TB2 for switching and displaying the first tab content and the second tab content C2. C1 is sent to the terminal device 10. The terminal device 10 that has received the content C1 from the information processing device 100 displays the content C1.

As shown in FIG. 2, the first heading TB1 is written as "search", and when the first heading TB1 is selected, the first tab content with the search results arranged is displayed in the display area AR1. In addition, the second heading TB2 is written as "Ranking", and when the second heading TB2 is selected, the second tab content in which the trading target ranking is arranged is displayed in the display area AR1.

In FIG. 2, when the first headline TB1 is selected by the user, the first tab content in which the search results of the search query "television" are arranged is displayed in the display area AR1. Also, when the user selects the second headline TB2, the second tab content C2 in which the ranking of the transaction target corresponding to the search query "television" is arranged is displayed in the display area AR1.

FIG. 2 shows a state where the second headline TB2 is selected, and the terminal device 10 displays the second tab content C2 in which the rankings of the trading objects corresponding to the search query "television" are arranged in the display area AR1. Specifically, in the display area AR1 of the content C1, the second tab content C2 showing the ranking in which the transaction targets corresponding to the search query "television" are arranged in descending order of score is displayed.

FIG. 2 shows a case where the information of the trading object (referred to as “transaction object G1”) ranked first is displayed in the display area AR1 of the content C1. The transaction object G1 is the television X sold by the sales source SA. The sales source SA is, for example, a shop (store) that sells products in an electronic shopping mall. The terminal device 10 displays various information such as the product name, price, and free shipping of the transaction target G1 as the information of the transaction target G1. In addition, the terminal device 10 displays reason information RS1 indicating the reason why the trading object G1 ranks first in the vicinity of the information of the trading object G1. Details of the reason will be described later.

In FIG. 2, only the information of the transaction object G1 ranked first is shown, but in the second tab content C2, the transaction object ranked second is shown below the transaction object G1 ranked first. Information is arranged, and information indicating transaction objects (televisions) ranked third and higher is arranged under the information. For example, the user of the terminal device 10 touches the display screen of the terminal device 10 and performs a scrolling operation to scroll the display in the display area AR1 downward, and the second and subsequent trading objects are displayed in the display area AR1. (television) can be displayed. It should be noted that the above operation by the user is only an example, and the terminal device 10 can accept any operation by the user as long as the display in the display area AR1 can be changed according to the operation by the user. good.

Also, in FIG. 2, when the user selects the first headline TB1 and the selected headline is switched from the second headline TB2 to the first headline TB1, the terminal device 10 displays the search query "television" in the display area AR1. ” is displayed. That is, the terminal device 10 switches the display of the display area AR1 from the second tab content C2 to the first tab content in which the search results of the search query "television" are arranged. In addition, in the search results of the search query "television" in the first tab content, the transaction objects may be randomly arranged, or the transaction objects may be arranged according to any criteria such as new arrival order or sales order. .

In this manner, the terminal device 10 switches between the first tab content and the second tab content C2 and displays them in the display area AR1 according to the user's selection. That is, the terminal device 10 displays either the first tab content or the second tab content C2 in the display area AR1 of the content C1 according to the user's selection.

As described above, the information processing apparatus 100 provides the terminal device 10 of the user with the content C1 to be displayed in the display area AR1 by switching between the first tab content and the second tab content C2 according to the user's selection. do. As a result, the user who uses the terminal device 10 provided with the content C1 displays the first tab content on the terminal device 10 when he/she wants to simply see the search results, and displays the first tab content on the terminal device 10 when he/she wants to see the ranking. The terminal device 10 is caused to display the 2-tab content C2. In the case of the content C1 in which the information is switched and displayed in this way, the user using the terminal device 10 switches the display according to the content he/she wants to see, causes the terminal device 10 to display the content, and confirms the content. be able to. Therefore, the information processing device 100 can provide appropriate content.

[1-2. Details of various processes]
Assuming the information processing described above, details of various processes will be described. It should be noted that descriptions of the same points as those described above will be omitted as appropriate. Also, various types of processing described below may be combined as appropriate. For example, information explaining the reason for the ranking of the trading object may be provided in the ranking from multiple perspectives, which will be described later. Note that the above is merely an example, and various types of processing may be combined in any way within the range in which combined processing is possible.

[1-2-1. cut〕
The information processing apparatus 100 provides content indicating ranking of transaction targets based on the search query and a view satisfying a predetermined condition (also referred to as a "relevant view") related to the search query among a plurality of views corresponding to the transaction target. may be provided.

In addition, the aspect corresponding to the transaction object here is, for example, a viewpoint (point of view) to the transaction object. For example, when dealing with a transaction target, the category, brand, usage scene, specifications (product specifications and functions) to which the transaction target applies, issues that can be resolved by the transaction target, and problems that can be resolved by the transaction target, etc. , various cuts (perspectives) corresponding to the transaction target are included. In the following, after the processing for determining the aspect to be displayed in the ranking is explained, the display of the ranking in the determined aspect will be explained.

The information processing apparatus 100 determines an aspect having a high degree of relevance to the search query as a related aspect among the plurality of aspects. For example, the information processing apparatus 100 selects an aspect having a relevance score (simply referred to as “relevance”) indicating a degree of relevance to the search query, which is equal to or greater than a predetermined threshold, among the plurality of aspects. determine the relevant cut with a high For example, the information processing apparatus 100 uses a predetermined algorithm for calculating the degree of relevance to calculate the degree of relevance for each of a plurality of aspects of the search query. The information processing apparatus 100 may interpret the intent of the search query and calculate the degree of relevance of each of a plurality of aspects of the search query using an algorithm for estimating the degree of relevance between the search query and each aspect. For example, the information processing apparatus 100 uses a predetermined algorithm for calculating normalized degrees of relevance to calculate the degrees of relevance for each of a plurality of angles of a search query. For example, the information processing apparatus 100 calculates the degree of relevance of each of the plurality of angles of the search query so that the sum of the degrees of relevance of each aspect is one.

Note that the above is merely an example, and the information processing apparatus 100 may use any information to calculate the degree of association between each of the plurality of angles and the search query. The information processing apparatus 100 may calculate the degree of relevance of each of the multiple perspectives for the search query using the relevance list information in which the degree of relevance of each of the multiple perspectives is associated with the keyword. For example, the information processing apparatus 100 may refer to the degree-of-relevance list information, determine a keyword corresponding to the search query, and use the degree of relevance of each of the multiple angles associated with the determined keyword.

For example, the information processing apparatus 100 determines a perspective with a degree of association equal to or greater than a predetermined threshold as a relevant perspective with a high degree of relevance to the search query. For example, when there is an aspect whose degree of association is equal to or higher than a first threshold value (for example, 0.5), the information processing apparatus 100 determines only that aspect as a related aspect. In this case, the information processing apparatus 100 provides content including one ranking based on one related aspect and search query.

For example, when there is no cut with a degree of association equal to or greater than a first threshold, the information processing apparatus 100 determines cuts with a degree of relevance equal to or greater than a second threshold (for example, 0.1) and less than a first threshold as related cuts. For example, when there are multiple perspectives (related perspectives) equal to or greater than the second threshold and less than the first threshold, the information processing apparatus 100 selects content including multiple rankings (multi-ranking) based on each of the plurality of relevant perspectives and the search query. offer. The information processing apparatus 100 may provide unranked content based on the relevant aspect and the search query when there is no aspect with a degree of relevance equal to or higher than the second threshold. Note that the above is merely an example, and the information processing apparatus 100 may determine the ranking to be provided based on any conditions. The information processing apparatus 100 provides content including a plurality of rankings (multi-ranking) based on each relevant aspect and the search query, without using the first threshold and using the aspect equal to or greater than the second threshold as the relevant aspect. good too.

On the premise of the above points, the information processing according to the cut will be described with reference to FIG. FIG. 3 is a diagram showing an example of ranking of transaction targets from multiple perspectives. In addition, in FIG. 3, the state divided|segmented for every cut is shown for description. FIG. 3 describes ranking when a plurality of perspectives are determined as related perspectives. In FIG. 3, a case where the search query is a character string "XXXX" will be described as an example. In FIG. 3, an abstract character string such as the character string "XXXX" is used for explanation, but the character string "XXXX" indicates a predetermined target (the name of a predetermined game software series in the example of FIG. 4). do.

Also, FIG. 3 shows a case where three cuts, cut #1, cut #2, and cut #3, are determined as related cuts. In FIG. 3, abstract character strings such as cut #1, cut #2, and cut #3 are shown, but each cut is, for example, "plush toy", "hero play", and "trading card" in the case of FIG. It is information that shows a specific cut.

For example, the information processing device 100 corresponds to each of cut #1, cut #2, and cut #3 among the trade targets (search result trade targets) included in the search results of the search process using the search query “XXXX”. Decide what you want to trade. For example, the information processing apparatus 100 uses the transaction object information of the search result transaction object to determine the transaction object corresponding to each of the cut #1, cut #2, and cut #3.

Here, the transaction target information includes information indicating the perspective to which each transaction target corresponds. For example, transaction target information includes information that indicates multiple perspectives such as categories to which each transaction target applies, brands, usage scenes, specifications, issues that can be resolved by the transaction target, and human concerns that can be resolved by the transaction target. be

For example, the information processing apparatus 100 refers to the transaction target information of the search result transaction target, and determines (identifies) the transaction target corresponding to each of the cut #1, cut #2, and cut #3. The information processing apparatus 100 generates a ranking of perspective #1 by ranking transaction objects corresponding to perspective #1 as ranking targets of perspective #1.

For example, the information processing apparatus 100 calculates a score for a transaction target corresponding to cut #1, which is a ranking target, and generates a ranking of cut #1 using the calculated score. Note that the calculation of the score of the transaction target is the same as the content explained in FIG. 1, so the explanation is omitted. For example, the information processing apparatus 100 generates a ranking of the cut #1 by assigning a higher rank in descending order of score.

The list information TA1 shown in FIG. 3 shows a list in which the rank of the transaction object, the transaction object ID (Identifier) which is the identification information for identifying the transaction object, and the score are associated with each other. In the list information TA1, the rank "first" is the transaction object ID "M34" and the score is "0.94". The rank "second" is the transaction object ID "M7" and the score is "0.89". The order "third place" is the transaction object ID "M1" and the score is "0.63". The information processing apparatus 100 uses information such as that shown in the list information TA1 to generate the ranking of the cut #1.

Similarly, the information processing apparatus 100 ranks transaction targets corresponding to cut #2 as ranking targets for cut #2, thereby generating a ranking for cut #2. For example, the information processing apparatus 100 calculates a score for a transaction target corresponding to cut #2, which is a ranking target, and generates a ranking of cut #2 using the calculated score.

The list information TA2 shown in FIG. 3 shows a list in which the rank of the transaction object, the transaction object ID, which is identification information for identifying the transaction object, and the score are associated with each other. In the list information TA2, the ranking "1st" is the transaction object ID "M162" and the score is "0.84". The rank "second" is the transaction object ID "M77" and the score is "0.74". The order "third place" is the transaction object ID "M18" and the score is "0.68". The information processing apparatus 100 uses information such as that shown in the list information TA2 to generate the ranking of the cut #2.

Similarly, the information processing apparatus 100 ranks transaction targets corresponding to cut #3 as ranking targets for cut #3, thereby generating a ranking for cut #3. For example, the information processing apparatus 100 calculates a score for a transaction target corresponding to cut #3, which is a ranking target, and generates a ranking of cut #3 using the calculated score.

The list information TA3 shown in FIG. 3 shows a list in which the rank of the transaction object, the transaction object ID, which is identification information for identifying the transaction object, and the score are associated with each other. In the list information TA3, the rank "first" is the transaction object ID "M15" and the score is "0.98". The rank "2nd" is the transaction object ID "M41" and the score is "0.79". The order "third place" is the transaction object ID "M91" and the score is "0.53". The information processing apparatus 100 uses information such as that shown in the list information TA3 to generate the ranking of the cut #3. Note that the processing for generating rankings for each aspect is not limited to the above, and any processing may be used as long as it is possible to generate rankings for a plurality of aspects described above. After calculating the score of each of the search result transaction objects, the information processing device 100 classifies the corresponding transaction objects for each aspect, and sorts them in descending order of score for each aspect after classification. A ranking may be generated.

Then, the information processing apparatus 100 generates content including the ranking of cut #1, the ranking of cut #2, and the ranking of cut #3. For example, the information processing apparatus 100 can display the first tab content in which the search results of the search query "XXXX" are arranged, and the second tab content in which the ranking of cut #1, the ranking of cut #2, and the ranking of cut #3 are laid out. Generate content that contains Then, the information processing apparatus 100 divides the first tab content in which the search results of the search query "XXXX" are arranged, and the second tab content in which the ranking of cut #1, the ranking of cut #2, and the ranking of cut #3 are laid out. The containing content is transmitted to the terminal device 10 . The terminal device 10 that has received the content from the information processing device 100 displays the received content.

In this way, the information processing apparatus 100 can provide appropriate content by providing content indicating the ranking of transaction targets based on the search query and the relevant aspect that satisfies a predetermined condition in relation to the search query. can.

Note that the above is merely an example, and the information processing apparatus 100 may use various information as appropriate to determine the approach. The information processing apparatus 100 may determine the approach according to user attributes or user concerns. Also, the information processing apparatus 100 may determine the approach based on the search history. If the ratio of the search query "bouquet" being used in combination with the search query "present" is equal to or greater than a predetermined ratio, the cut end of the search query "bouquet" may be determined to be "present".

Further, the information processing apparatus 100 may determine the approach based on the interest estimated from the search history. As described above, the information processing apparatus 100 may generate rankings of transaction targets linked to information (title, text, review) corresponding to a search query and an aspect. Further, when the degree of relevance of a certain aspect is too high (satisfies a predetermined condition), the information processing apparatus 100 may generate only the ranking of that aspect.

[1-2-2. Search results and ranking example]
Next, examples of search results and rankings will be described with reference to FIGS. 4 to 7. FIG. 4 to 7 are diagrams showing examples of search results and rankings.

[1-2-2-1. multiple cuts]
First, the example of FIG. 4 will be described. In FIG. 4, the character string "XXXX" used as the search query indicates the name of a predetermined game software series. The information processing apparatus 100 generates a search result through search processing using the search query “XXXX”.

In addition, the information processing apparatus 100 determines three categories of "stuffed toy", "hero game", and "trading card" that are equal to or greater than the second threshold and less than the first threshold as related categories. Then, the information processing apparatus 100 generates content including the ranking of the “stuffed toy,” the ranking of “hero play,” and the ranking of “trading card.” In FIG. 4, the information processing apparatus 100 generates content including the second tab content C12 including the ranking RL11 of "plush toy", the ranking RL12 of "hero play", and the ranking RL13 of "trading card".

In FIG. 4, the information processing apparatus 100 displays a first tab content C11, a second tab content C12, and a first heading TB1 and a second heading TB1 for switching and displaying the first tab content C11 and the second tab content C12. Generate content that includes TB2. Then, the information processing apparatus 100 displays the first tab content C11, the second tab content C12, and the first heading TB1 and the second heading TB2 for switching and displaying the first tab content C11 and the second tab content C12. The containing content is transmitted to the terminal device 10 . The terminal device 10 that receives the content including the first tab content C11, the second tab content C12, the first heading TB1 and the second heading TB2 from the information processing device 100 displays the received content.

The first tab content C11 and the second tab content C12 are displayed in an area for displaying tabs (contents) in the content, such as the area AR1 of the content C1. For example, the first tab content C11 and the second tab content C12 are displayed in the area AR1 with the search query "XXXX" entered by the user in the search box BX1 of the content C1 in FIG.

For example, when the user selects the first headline TB1, the first tab content C11 in which the search results of the search query "XXXX" are arranged is displayed in the display area AR1. Further, when the user selects the second headline TB2, the second tab content C12 in which the ranking of the transaction target corresponding to the search query "XXXX" is arranged is displayed in the display area AR1. That is, the terminal device 10 switches between the first tab content C11 and the second tab content C12 and displays them in the display area AR1 according to the user's selection.

Next, the example of FIG. 5 will be described. FIG. 5 shows a case where the character string "baby gift" is used as a search query. The information processing apparatus 100 generates a search result by performing a search process using the search query "baby gift". The information processing apparatus 100 generates content including the first tab content C21 in which the search results corresponding to the search query "baby gift" are arranged.

In addition, the information processing apparatus 100 determines three cuts of "diaper cake", "swaddle", and "baby utensils" which are equal to or more than the second threshold and less than the first threshold as related cuts. Then, the information processing apparatus 100 generates content including the ranking of the cut "diaper cake", the ranking of the cut "wrapping", and the ranking of the cut "baby utensils". In FIG. 5, the information processing apparatus 100 generates content including the second tab content C22 including the ranking RL21 of the cut "diaper cake", the ranking RL22 of the cut "swaddle", and the ranking RL23 of the cut "baby utensils".

In FIG. 5, the information processing apparatus 100 displays a first tab content C21, a second tab content C22, and a first heading TB1 and a second heading TB1 for switching and displaying the first tab content C21 and the second tab content C22. Generate content that includes TB2. Then, the information processing apparatus 100 displays the first tab content C21, the second tab content C22, and the first heading TB1 and the second heading TB2 for switching and displaying the first tab content C21 and the second tab content C22. The containing content is transmitted to the terminal device 10 . The terminal device 10 that receives the content including the first tab content C21, the second tab content C22, the first heading TB1 and the second heading TB2 from the information processing device 100 displays the received content.

The first tab content C21 and the second tab content C22 are displayed in an area for displaying tabs (contents) in the content, such as the area AR1 of the content C1. For example, the first tab content C21 and the second tab content C22 are displayed in the area AR1 with the search query "baby gift" input by the user in the search box BX1 of the content C1 in FIG. .

For example, when the first headline TB1 is selected by the user, the first tab content C21 in which the search results for the search query "baby gift" are arranged is displayed in the display area AR1. Also, when the user selects the second headline TB2, the second tab content C22 in which the ranking of the transaction target corresponding to the search query "baby gift" is arranged is displayed in the display area AR1. That is, the terminal device 10 switches between the first tab content C21 and the second tab content C22 and displays them in the display area AR1 according to the user's selection.

Next, the example of FIG. 6 will be described. FIG. 6 shows a case where the character string "perfume" is used as a search query. The information processing apparatus 100 generates a search result through search processing using the search query “perfume”. The information processing apparatus 100 generates content including first tab content C31 in which search results corresponding to the search query "perfume" are arranged.

In addition, the information processing apparatus 100 determines three cross-cuts, "brand #1", "brand #2", and "brand #3", which are equal to or greater than the second threshold and less than the first threshold, as related cross-cuts. Then, the information processing apparatus 100 generates content including the ranking of the cut "brand #1", the ranking of the cut "brand #2", and the ranking of the cut "brand #3". Note that FIG. 6 shows abstract character strings such as brand #1, brand #2, and brand #3, but each brand is information that can specify a specific brand. In FIG. 6, the information processing apparatus 100 displays contents including the second tab content C32 including the ranking RL31 of the cut "brand #1", the ranking RL32 of the cut "brand #2", and the ranking RL33 of the cut "brand #3". Generate.

In FIG. 6, the information processing apparatus 100 displays a first tab content C31, a second tab content C32, and a first heading TB1 and a second heading TB1 for switching and displaying the first tab content C31 and the second tab content C32. Generate content that includes TB2. Then, the information processing apparatus 100 displays the first tab content C31, the second tab content C32, and the first heading TB1 and the second heading TB2 for switching and displaying the first tab content C31 and the second tab content C32. The containing content is transmitted to the terminal device 10 . The terminal device 10 that receives the content including the first tab content C31, the second tab content C32, the first heading TB1 and the second heading TB2 from the information processing device 100 displays the received content.

The first tab content C31 and the second tab content C32 are displayed in an area for displaying tabs (contents) in the content, such as the area AR1 of the content C1. For example, the first tab content C31 and the second tab content C32 are displayed in the area AR1 with the search query "perfume" entered by the user in the search box BX1 of the content C1 in FIG.

For example, when the first headline TB1 is selected by the user, the first tab content C31 in which the search results for the search query "perfume" are arranged is displayed in the display area AR1. Also, when the user selects the second headline TB2, the second tab content C32 in which the ranking of the transaction target corresponding to the search query "perfume" is arranged is displayed in the display area AR1. That is, the terminal device 10 switches between the first tab content C31 and the second tab content C32 and displays them in the display area AR1 according to the user's selection.

[1-2-2-2. One cut]
Next, the case where there is one related cut as shown in FIG. 7 will be described. FIG. 7 shows a case where the character string "washing machine" is used as a search query. The information processing apparatus 100 generates a search result through search processing using the search query "washing machine". The information processing apparatus 100 generates content including first tab content C41 in which search results corresponding to the search query "washing machine" are arranged.

In addition, the information processing apparatus 100 determines one cut that is equal to or greater than the first threshold as a related cut. Then, the information processing apparatus 100 generates content including a ranking of one aspect. In FIG. 7, the information processing apparatus 100 generates content including the second tab content C42 including ranking of one aspect. In this case, the information processing apparatus 100 can display a list of trading targets with a single ranking compared to a case where rankings from a plurality of perspectives are included. The information processing apparatus 100 may generate the second tab content C42 including character information indicating one cut.

In FIG. 7, the information processing apparatus 100 displays a first tab content C41, a second tab content C42, and a first heading TB1 and a second heading TB1 for switching and displaying the first tab content C41 and the second tab content C42. Generate content that includes TB2. Then, the information processing apparatus 100 displays the first tab content C41, the second tab content C42, and the first heading TB1 and the second heading TB2 for switching and displaying the first tab content C41 and the second tab content C42. The containing content is transmitted to the terminal device 10 . The terminal device 10 that receives the content including the first tab content C41, the second tab content C42, the first heading TB1 and the second heading TB2 from the information processing device 100 displays the received content.

The first tab content C41 and the second tab content C42 are displayed in an area for displaying tabs (contents) in the content, such as the area AR1 of the content C1. For example, the first tab content C41 and the second tab content C42 are displayed in the area AR1 with the search query "washing machine" entered by the user in the search box BX1 of the content C1 in FIG. .

For example, when the user selects the first headline TB1, the first tab content C41 in which the search results of the search query "washing machine" are arranged is displayed in the display area AR1. Also, when the user selects the second heading TB2, the second tab content C42 in which the ranking of the transaction target corresponding to the search query "washing machine" is arranged is displayed in the display area AR1. That is, the terminal device 10 switches between the first tab content C41 and the second tab content C42 and displays them in the display area AR1 according to the user's selection.

[1-2-3. Narrowing down of transaction targets]
The information processing device 100 may determine a transaction object (also referred to as a “target transaction object”) to be displayed as a ranking based on transaction object information related to the transaction object. This point will be described below. For example, the information processing apparatus 100 displays transaction objects (target transaction objects) as rankings based on transaction object information among transaction objects (search result transaction objects) included in search results of search processing using a search query. to decide. In this case, the information processing apparatus 100 generates rankings for the determined (narrowed down) target transaction targets. For example, the information processing apparatus 100 generates content including the second tab content in which the ranking generated for the target transaction object is arranged.

Then, the information processing device 100 provides content indicating the ranking generated for the target transaction object. For example, the information processing apparatus 100 provides content including second tab content in which rankings generated for the target transaction object are arranged.

For example, the information processing apparatus 100 may determine the target transaction object based on the sales history (information such as whether or not the product was sold, the number of orders). For example, the information processing apparatus 100 may determine the target transaction object based on the period that has elapsed since the date and time when the transaction object was sold. For example, the information processing apparatus 100 may determine, as the target transaction object, a transaction object within a predetermined period of time since the date and time of the last sale. For example, the information processing apparatus 100 may determine, as target transaction objects, a predetermined number of transaction objects in descending order of the last sold date and time.

For example, the information processing device 100 may determine the target transaction object based on the number of transaction objects sold. For example, the information processing apparatus 100 may determine a transaction object that has sold a predetermined number or more as a target transaction object.

For example, the information processing apparatus 100 may determine the target transaction object based on the number of views (PV number) of the information of the transaction object. For example, the information processing apparatus 100 may determine a transaction object for which the number of views of information (the number of PVs) is equal to or greater than a predetermined number of times as a target transaction object.

For example, the information processing apparatus 100 may determine the target transaction object based on the number of reviews for the transaction object. For example, the information processing apparatus 100 may determine a transaction object with a predetermined number of reviews or more as a target transaction object.

For example, the information processing device 100 may determine the target transaction object based on the evaluation of the transaction object. For example, the information processing apparatus 100 may determine a transaction object whose evaluation is equal to or greater than a predetermined value as a target transaction object.

Further, for example, the information processing device 100 may determine the target transaction object based on the score of the transaction object. The information processing apparatus 100 may determine a transaction object whose score satisfies a predetermined condition as a target transaction object.

Further, for example, the information processing apparatus 100 may determine the target transaction object based on external factors such as a boom, SNS, number of searches, and the like. For example, the information processing apparatus 100 may determine a transaction object that has been posted on the SNS a predetermined number of times or more as a target transaction object. For example, the information processing apparatus 100 may determine a transaction object for which the number of searches is equal to or greater than a predetermined number as a target transaction object.

Further, for example, the information processing apparatus 100 may determine the target transaction object based on internal factors such as coupons and price reductions. For example, the information processing apparatus 100 may determine a transaction object for which a coupon was provided within a predetermined period as a target transaction object. For example, the information processing apparatus 100 may determine a transaction object whose price has been reduced within a predetermined period as a target transaction object.

For example, the information processing apparatus 100 may display the first tab content in which the search results of the search query are arranged, and the target transaction determined (narrowed down) based on the transaction target information among the search result transaction targets corresponding to the search query. The content including the second tab content in which the ranking generated with the target as the target (population) is arranged is transmitted to the terminal device 10 . The terminal device 10 that has received the content from the information processing device 100 displays the received content.

Through the above processing, the information processing apparatus 100 can appropriately determine transaction targets to be ranked. Accordingly, the information processing apparatus 100 can provide appropriate content. Note that the above is merely an example, and the information processing apparatus 100 may determine the target transaction object using various information as appropriate. For example, the information processing apparatus 100 may appropriately use user information of a user to whom information is provided to determine a target transaction target, which will be described later.

[1-2-4. Reason for ranking]
As shown in FIG. 2, the information processing apparatus 100 may provide content including reason information indicating the reason why the transaction target has the ranking. For example, the information processing device 100 estimates the reason for the ranking of the transaction object (target transaction object) displayed as a ranking based on the transaction object information of the transaction object, and provides content indicating the estimated reason for the target transaction object. .

The information processing apparatus 100 may provide the estimated reason along with the ranking. For example, the information processing apparatus 100 generates content in which the reason is placed near the information indicating the target transaction target in the ranking. In FIG. 2, the information processing apparatus 100 displays the reason information RS1 indicating the reason why the trading object G1, which is the television X sold by the sales source SA, ranked first, on the right side (near) the image of the trading object G1. A content C1 including the arranged second tab content C2 is generated. The information processing apparatus 100 transmits to the terminal device 10 the content C1 including the second tab content C2 in which the reason information RS1 indicating the reason why the transaction target G1 is ranked first is arranged to the right side of the image of the transaction target G1. do.

For example, the information processing device 100 may estimate based on the tendency of the transaction object information of a plurality of elements (types) included in the transaction object information. For example, the information processing apparatus 100 presumes that the most characteristic element is the reason for the ranking of the target transaction object. For example, the information processing apparatus 100 presumes that the element with the highest evaluation is the reason for the ranking of the target transaction object. The plurality of elements included in the transaction target information include various elements related to the number of orders of the transaction target, the number of views of information, the number of reviews, the number of reservations, external factors, internal factors, and the like.

For example, the information processing apparatus 100 presumes that the one with the highest score among a plurality of elements related to browsing (PV), ordering, review, etc., is the reason for the ranking of the target transaction object. In this case, the information processing device 100 may calculate a partial score corresponding to each of the multiple elements included in the transaction target information. For example, the information processing device 100 receives information of a plurality of elements included in the transaction target information, and uses a function (score function) that outputs a partial score of the elements to obtain a score of the plurality of elements included in the transaction target information. Calculate the partial score for each. For example, the information processing device 100 calculates the average value of the partial scores corresponding to each of the plurality of elements included in the transaction object information as the score of the transaction object. For example, the information processing device 100 calculates the score of the transaction object by summing the partial scores corresponding to each of the plurality of elements included in the transaction object information. The information processing apparatus 100 presumes that the element with the largest partial score for the target transaction object is the reason for the ranking of the target transaction object. For example, the information processing apparatus 100 estimates an element having the largest partial score of the element "number of orders" for the target transaction object as the reason for the rank of the target transaction object being the element "number of orders".

Through the above process, the information processing apparatus 100 can appropriately estimate the reason for the ranking of the trading object in the ranking. Note that the above is only an example, and the information processing apparatus 100 may use various information as appropriate to estimate the reason for the ranking of the target transaction object. For example, the information processing device 100 may estimate the reason for the order of the target transaction object based on the result of comparison with the trend of each element of other transaction objects. In this case, the information processing apparatus 100 provides a reason for indicating the comparison result. For example, the information processing apparatus 100 provides a reason for showing the comparison result with other transaction objects, such as a worse evaluation than the first transaction object.

In addition, the information processing apparatus 100 may provide the reason for the ranking and the order of the target transaction object taking into consideration external factors including factors other than the electronic commerce service. For example, the information processing apparatus 100 presumes, together with the external factor, the factor that became characteristic after the occurrence of the external factor as the reason for the target transaction object. When the number of views (number of PVs) increases after the target transaction object is posted on the SNS, and the ranking also increases, the information processing apparatus 100 uses both the number of posts on the SNS and the number of views as the reason for the ranking of the target transaction object. It may be assumed that In this case, the information processing apparatus 100 may provide both the posting on the SNS and the number of views as reasons for the ranking of the target transaction object. Further, the information processing apparatus 100 may provide the ranking considering the internal factors and the reason for the ranking of the target transaction object. Further, the information processing apparatus 100 may estimate a factor according to the user's attribute as the reason.

The information processing apparatus 100 estimates the reason for the ranking based on the ranking elements. The information processing apparatus 100 may presume and provide a reason such as "This transaction target was released a long time ago, but it has a high evaluation and ranks first." The information processing apparatus 100 may also estimate the reasons for ranking by analyzing ranking elements such as external factors, internal factors, leading indicators, and review evaluations.

For example, when the number of views (PV) and the ratio (weighting) of orders and reviews, which are elements used to calculate the score, are 10:1:1, the information processing device 100 assigns the reason for the ranking of the target transaction to the element " number of views (PV)”.

For example, when the number of views (PV) and the ratio (weighting) of orders and reviews, which are elements used to calculate the score, are 1:1:10, the information processing device 100 assigns the reason for the ranking of the target transaction to the element " may be presumed to be "reviews". In this manner, the information processing apparatus 100 may estimate the reason for the ranking of the target transaction object from the comparison results and weights of the elements used for score calculation. The information processing apparatus 100 may find a singular point element with a high score and estimate that this element is the reason for the ranking of the target transaction object.

Further, the information processing apparatus 100 may estimate the reason for the rank of the target transaction object according to the relative comparison result with the transaction object of other ranks. For example, the information processing device 100 determines the reason for the order of the target transaction object according to the comparison result, such as "second place because the evaluation is lower than the first place transaction object". presume.

In addition, the information processing apparatus 100 may presume that an external factor related to a boom, such as "because it was provided by XX comedian", is the reason for the ranking of the target transaction object. The information processing apparatus 100 may presume that internal factors such as "because the coupon is sold after being issued" or "because the price has been reduced" are the reasons for the ranking of the target transaction object. The information processing apparatus 100 may, on a rule basis, estimate that when the number of orders increases after the occurrence of an external factor or an internal factor, that factor is the reason for the ranking of the target transaction object. When the number of searches increases, the information processing apparatus 100 may analyze the number of searches, estimate the factors, and estimate that the estimated factor is the reason for the ranking of the target transaction object. The information processing device 100 may presume that the buzzword is the reason for the ranking of the target transaction object. The information processing apparatus 100 may analyze whether or not it was introduced on television by voice recognition, and estimate the reason for the ranking of the target transaction object based on the analysis result.

The information processing apparatus 100 may use a value obtained by excluding the number of promotion links from the number of views (PV). In this case, the information processing apparatus 100 may provide a ranking generated using the number of views (PV) excluding the number of promotion links. The information processing device 100 uses information on the number of views (PV) excluding the number of promotion links as the reason for the ranking of the target transaction object in the ranking generated using the number of views (PV) excluding the number of promotion links. can be estimated by

Further, the information processing apparatus 100 may switch the reason for each attribute of the user. For example, the information processing apparatus 100 may determine which reason to provide for each user based on whether the user likes price reductions, new products, or the like. For example, if the user likes price reductions, the information processing apparatus 100 may determine to provide the element "price reduction" as the reason for ranking the target transaction object. Further, the information processing apparatus 100 may change the threshold for each attribute of the user.

[1-2-5. Ranking target (products, etc.)]
In the above-described example, an example is shown in which each transaction target is a ranking target, but the ranking target is not limited to the transaction target. This point will be described below. First, the premise of the rankings described below will be described.

The television X, which is the transaction target G1 sold by the marketer SA shown in FIG. 2, may be sold as another transaction target by a marketer other than the marketer SA (goods). In this way, even a plurality of transaction targets sold by a plurality of sales sources (shops) may be the same product. For example, a transaction target G1, which is a TV X sold by a marketer SA, and a transaction target G2, which is a TV X sold by a marketer SB, are different transaction targets when viewed as transaction targets, but are viewed as products. are the same product (TV X).

For example, if there are a large number of trade targets corresponding to the same product, it is possible that only information about the same product but different trade targets will be displayed. For example, if several thousand sellers are selling TV X, and multiple TV X trading targets dominate the rankings from 1st to 100th, the same product (TV X) is lined up, and it is difficult to say that the information provided is useful for the user. In this way, when each transaction target is ranked, it may be difficult to provide useful information to the user.

Therefore, the information processing apparatus 100 generates a ranking for a group of trading objects that are the same product as one ranking object, and provides the generated ranking to the user. The information processing apparatus 100 determines a group of transaction objects of the same product among a plurality of transaction objects corresponding to the search query, and generates a ranking of the determined group of transaction objects as one product. For example, the information processing apparatus 100 determines a group of transaction objects that is the product "TV X" from among the plurality of transaction objects corresponding to the search query "TV", and sets the transaction object group as one product "TV X". to generate a ranking.

For example, the information processing apparatus 100 determines which transaction target is the same product by using the transaction target having the same identification information (also referred to as “product identification information”) for identifying the product. For example, product specific information is a JAN code. For example, the information processing device 100 determines that a group of transaction objects with matching JAN codes are the same product.

In addition, the information processing apparatus 100 determines that the transaction object with which the product specifying information is not associated is an individual transaction object (also referred to as "non-product") that is not a product. For example, the information processing apparatus 100 determines that a transaction target with no JAN code is an individual transaction target that is not a product.

Then, the information processing device 100 generates a ranking (also referred to as “product-present ranking”) in which the two types of ranking objects, ie, the product and the individual transaction object, are ranked. The information processing apparatus 100 generates a product ranking in which two types of ranking targets, ie, a product and an individual transaction target, are mixed. In the following, the processing will be described by exemplifying the case where "birth celebration" is used as a search query.

For example, the information processing device 100 generates a product ranking using the first score of the individual transaction target and the second score of the product (also referred to as "product score"). For example, the information processing apparatus 100 calculates the score of each transaction target (search result transaction target) included in the search result of the search process using the search query “baby gift”. Note that the calculation of the score of the transaction target is the same as the content explained in FIG. 1, so the explanation is omitted. The information processing apparatus 100 uses the score of the individual transaction object among the search result transaction objects as the first score.

In addition, the information processing apparatus 100 calculates a second score (product score) of one product using the score of each of the transaction target group that is determined as one product among the search result transaction targets. The information processing apparatus 100 may calculate the product score of one product based on the total score of each of the transaction target groups that are regarded as one product. The information processing apparatus 100 may calculate the average score of each of the transaction target groups that are regarded as one product as the product score of one product. For example, the information processing apparatus 100 uses the score of each of the transaction targets G11, G12, and G13, which are the product "wrap W" among the search result transaction targets of the search query "baby gift", to obtain the product "wrap W". Calculate product scores. For example, the information processing apparatus 100 calculates the average score of each of the transaction targets G11, G12, and G13 of the product "wrapping W" as the product score of the product "wrapping W."

Through the above processing, the information processing apparatus 100 can appropriately generate rankings for ranking targets including products. Accordingly, the information processing apparatus 100 can provide appropriate content. The above is merely an example, and the information processing apparatus 100 may calculate the first score of the individual transaction target and the second score of the product by processing using various information as appropriate. The information processing apparatus 100 calculates the score of only the individual transaction objects among the search result transaction objects included in the search results of the search process using the search query “baby gift” in the same manner as in FIG. Only the product score for the product may be calculated without calculating the score for the group. Note that the information processing apparatus 100 may calculate the score and generate the ranking based on the evaluation of the seller who sells each transaction target, but this point will be described later.

For example, the information processing device 100 uses the first score of the individual transaction target and the second score of the product (product score) to rank the individual transaction in descending order of the first score or the second score. To generate a product presence ranking in which objects and products are mixed. The information processing apparatus 100 generates a product presence ranking including one product "wrapping W" corresponding to the transaction targets G11, G12, and G13.

Then, the information processing apparatus 100 generates content including the product availability ranking. For example, the information processing apparatus 100 displays information of transaction objects G11, G12, and G13 corresponding to one product "wrap W" when one product "wrap W" in the product availability ranking is selected. Generate content. For example, the information processing apparatus 100 generates content including the first tab content in which the search results of the search query "birth celebration" are arranged and the second tab content in which the product availability ranking corresponding to the search query "birth celebration" is arranged. do.

Then, the information processing apparatus 100 transmits to the terminal content including the first tab content in which the search results of the search query "birth celebration" are arranged and the second tab content in which the product availability ranking corresponding to the search query "birth celebration" is arranged. Send to device 10 . The terminal device 10 that has received the content from the information processing device 100 displays the received content. The terminal device 10 displays information of transaction objects G11, G12, and G13 corresponding to one product "wrap W" when one product "wrap W" in the displayed product availability ranking is selected by the user. do.

[1-2-5-1. Processing image, release of limitation]
The processing image and the release of the limitation described above will be described below. First, a processing image will be described with reference to FIG. FIG. 8 is a diagram illustrating the concept of product-based ranking.

FIG. 8 shows, as an example, a processing image PS1 for four commodities A, B, C, and D to be traded. In FIG. 8, the information processing apparatus 100 determines that the product A and the product C are the same product X. In FIG. Further, the information processing device 100 determines that the product B is an individual transaction object (non-product). Also, the information processing apparatus 100 determines that the product D is the product Y. FIG. For example, if there is another product that is the product Y in addition to the product D, the information processing apparatus 100 determines that the other product and the product D are the same product Y.

Then, the information processing apparatus 100 generates rankings (rankings with products) with the product X, the product B, and the product Y as ranking targets. Note that when the product Y is only the product D, the information processing apparatus 100 may set the product D as a ranking target.

The process described above is merely an example of the process of generating the product availability ranking, and the information processing apparatus 100 may generate the product availability ranking using various information as appropriate. The release of limitations in this regard is described below.

The information processing device 100 may calculate the score of the seller who sells the transaction object (seller score) and the score of the transaction object itself (transaction object score). The information processing apparatus 100 may calculate various scores such as a first score and a second score (product score) using the seller score and the transaction target score. The information processing device 100 may use the sum of the seller score and the transaction target score as the score.

The information processing device 100 may correct the product score based on the number of transaction targets that are the same product. The information processing apparatus 100 may correct the product score based on the number of sales of the same product to be traded. The information processing apparatus 100 may correct the product score based on the evaluation of the sales source (store) that sells the same product as the transaction target. For example, the information processing apparatus 100 may reduce the amount of correction even if the evaluation of one of the sellers is bad, if the evaluation of the other sellers is high.

The information processing device 100 may calculate a score based on the review content for each transaction target. The information processing apparatus 100 may analyze the review content, estimate the evaluation of the seller and the evaluation of the transaction target, and calculate the score from the evaluation of the transaction target.

The information processing device 100 generates a product availability ranking based on transaction target information. The information processing device 100 generates a product availability ranking based on the respective rankings of transaction objects and products. The information processing apparatus 100 may calculate the transaction target score based on the evaluation of the seller. Even if one of the sellers selling the same product is bad, the information processing apparatus 100 ranks the same product higher if it is estimated that the product has a high reputation. good too. If one of the sellers selling the same product is bad, the information processing apparatus 100 may calculate the product score by excluding the score of the transaction target of that seller. The information processing apparatus 100 may perform scoring according to the number of trade targets that constitute one product.

The information processing apparatus 100 may calculate the product score by estimating the evaluation of the product (evaluation excluding the evaluation of the distributor) from the evaluation (score, etc.) of the transaction target. The information processing apparatus 100 may exclude transaction targets of sellers (stores) with poor evaluations from the targets of processing. The information processing apparatus 100 may perform product evaluation (score calculation, etc.) using an average review score. The information processing apparatus 100 may exclude, from the target of processing, a transaction target of a sales source whose value divergence is clearly greater than or equal to a threshold value.

The information processing apparatus 100 may perform language analysis of the content of the review to evaluate the transaction target (product) (score calculation, etc.). The information processing apparatus 100 may consider the number of sales. The information processing apparatus 100 may generate the ranking in consideration of the number of sellers, the number of sales, the price, and the like. The information processing apparatus 100 may generate a product ranking by scoring the number of sales, PV, etc. for each product and each transaction target. The information processing apparatus 100 may calculate a median value from evaluations of reviews for each vendor, and perform weighting that integrates product and transaction target scores. The information processing apparatus 100 may estimate whether it is a product search or a transaction target search from the search query, and change the weighting. The information processing device 100 may estimate the product. The information processing apparatus 100 may determine a group of business objects to be the same product by character analysis or image analysis of business object information. The information processing device 100 may treat the set sale as one transaction target.

[1-2-6. Transaction target according to the user]
The information processing apparatus 100 may determine a transaction target (also referred to as a “target transaction target”) to be displayed as a ranking based on the user information of the user who entered the search query. In other words, the information processing device 100 may provide a ranking in which the target transaction object varies according to the user information. This point will be described below. For example, the information processing apparatus 100 displays transaction objects (target transaction objects) as ranking based on user information among transaction objects (search result transaction objects) included in search results of search processing using a search query. may be determined. In this case, the information processing device 100 generates a ranking for the determined target transaction target. For example, the information processing apparatus 100 generates content including the second tab content in which the ranking generated for the target transaction object is arranged.

Then, the information processing device 100 provides content indicating the ranking generated for the target transaction object. For example, the information processing apparatus 100 provides content including second tab content in which rankings generated for the target transaction object are arranged.

The information processing apparatus 100 may determine the target transaction object based on user information including user attribute information. The information processing apparatus 100 may determine a transaction object selected by a similar user who is similar to the user's attribute as a target transaction object. The information processing apparatus 100 may determine a group of transaction objects selected in the past by similar users who are similar to the user U1 as target transaction objects.

The information processing apparatus 100 may determine a transaction object purchased by a similar user having similar attributes of the user as a target transaction object. The information processing apparatus 100 may determine a group of transaction objects purchased in the past by similar users who are similar to the user U1 as target transaction objects.

If the user to whom the ranking is to be provided is a male in his 30s, the information processing apparatus 100 may determine the transaction object included in the purchase history of the similar user corresponding to the male in his 30s as the target transaction object. If the user U1 who has entered the search query "vacuum cleaner" is a woman in her twenties, the information processing apparatus 100 determines the transaction target included in the search result of the search process using the search query "vacuum cleaner" (search result transaction target ), a transaction object that has a sales history to a similar user corresponding to a woman in her twenties may be determined as the target transaction object.

The information processing apparatus 100 may provide content indicating rankings corresponding to other rankings provided to similar users who are similar to the attributes of the user. The information processing apparatus 100 selects a group of transaction objects included in the ranking provided to the user U2 when the user U2 similar to the user U1 who entered the search query "YYYY" entered the search query "YYYY" in the past. is determined as an object transaction object (object transaction object TG). Then, the information processing device 100 generates a ranking of the target transaction target TG, and provides the generated ranking to the user U1.

The information processing device 100 may provide content indicating rankings corresponding to other rankings provided when similar users select transaction targets. The information processing apparatus 100 provided the user U2 with the transaction target when the user U2 who is similar to the user U1 who entered the search query "YYYY" selected the transaction target from the search results of the search query "YYYY" in the past. A group of trading objects included in the ranking is determined as a target trading object (target trading object TG). Then, the information processing device 100 generates a ranking of the target transaction target TG, and provides the generated ranking to the user U1.

For example, the information processing apparatus 100 may display the first tab content in which the search results of the search query are arranged and the target transaction determined (narrowed down) based on the user information among the search result transaction targets corresponding to the search query. The content including the second tab content in which the ranking generated with the target as the target (population) is arranged is transmitted to the terminal device 10 . The terminal device 10 that has received the content from the information processing device 100 displays the received content.

In addition, the information processing apparatus 100 may provide content indicating the reason for the ranking of the target transaction object. The information processing apparatus 100 may switch the reason for each attribute of the user. The information processing apparatus 100 may determine which reason to provide for each user, depending on whether quality (specifications) is emphasized or price is emphasized. The information processing apparatus 100 may determine to provide the element "spec" as a reason for the ranking of the target transaction object if the user is a quality-oriented user.

Through the above processing, the information processing apparatus 100 can appropriately determine transaction targets to be ranked. Accordingly, the information processing apparatus 100 can provide appropriate content. Note that the above is merely an example, and the information processing apparatus 100 may determine the target transaction object using various information as appropriate.

As described above, the information processing apparatus 100 determines (selects) the target transaction object according to the attribute of the user. For example, the information processing device 100 selects the transaction object selected by the similar user as the target transaction object. For example, the information processing apparatus 100 selects a transaction object purchased by a similar user as a target transaction object.

Further, the information processing apparatus 100 may generate rankings of types according to user attributes. The information processing apparatus 100 may generate a ranking of the type (perspective) displayed when a user similar to the user selects a transaction target. The information processing device 100 may display the reasons for ranking. The information processing apparatus 100 may generate content including a reason according to the attribute of the user.

As described above, the information processing apparatus 100 provides a ranking of transaction targets according to user attributes. For example, the information processing device 100 generates rankings of transaction targets according to new users, gender, and age. For example, the information processing apparatus 100 generates a ranking only for items purchased by similar users corresponding to attributes of the user. For example, the information processing apparatus 100 determines, as target transaction objects, transaction objects browsed by the user having similar attributes corresponding to the user's attribute, transaction objects added to the cart, and the like, and generates a ranking. In addition, the information processing device 100 determines a target transaction target (population) based on individual feature information such as the user's family structure, purchase history, purchase price range, etc., and generates a ranking of the population. good too.

The information processing apparatus 100 may generate a ranking of an aspect corresponding to a user attribute among rankings of a plurality of aspects (viewpoints). The information processing apparatus 100 may generate a ranking of the perspectives determined based on the user information among the plurality of perspectives. The information processing device 100 generates rankings selected (clicked) by the user or similar users who are similar to the user's attributes from among the rankings of each aspect such as brand and price, and provides the rankings to the user. do. It may be a user to be displayed. The information processing apparatus 100 may generate content that displays the reason displayed when a person of the age of the user selects (clicks) the transaction object, or displays the reason corresponding to the attribute. Content may be generated.

[1-2-7. boost]
The information processing apparatus 100 determines a boost target, which is a target of a boost process for boosting the ranking, among the trade targets, and generates a ranking reflecting the result of the boost process performed on the boost target. good too. This point will be described below. For example, the information processing apparatus 100 determines a boost target, and generates content including second tab content in which a ranking reflecting the result of the boost processing performed on the determined boost target is arranged.

Then, the information processing apparatus 100 provides content indicating a ranking reflecting the results of the boost processing performed on the boost target. For example, the information processing apparatus 100 provides content including second tab content in which rankings reflecting the results of boost processing performed on boost targets are arranged.

For example, the information processing device 100 determines a boost target based on transaction target information relating to the transaction target. The information processing device 100 may determine the boost target based on the sales history of the transaction target. The information processing device 100 may determine the boost target based on the number of sales of the transaction target. The information processing device 100 may determine the boost target based on the transition of the sales volume of the transaction target. For example, the information processing apparatus 100 determines the transaction target as a boost target when the transition of the sales volume of the transaction target is on an upward trend. For example, when the rate of increase in the number of sales of a transaction target is equal to or greater than a predetermined value, the information processing apparatus 100 determines the transaction target as a boost target.

The information processing device 100 may determine the boost target based on the number of times information indicating the transaction target is viewed. For example, the information processing apparatus 100 determines the transaction target as a boost target when the transition of the number of views of the information indicating the transaction target is on an upward trend. For example, when the rate of increase in the number of views of information indicating a transaction target is equal to or greater than a predetermined value, the information processing apparatus 100 determines the transaction target as a boost target.

The information processing device 100 may determine the boost target based on the number of reviews for the transaction target. For example, the information processing apparatus 100 determines the transaction target as a boost target when the number of reviews for the transaction target is on an upward trend. For example, when the rate of increase in the number of reviews for a transaction object is equal to or greater than a predetermined value, the information processing apparatus 100 determines the transaction object as a boost target.

Further, the information processing apparatus 100 may determine boost targets based on external factors such as SNS and the number of searches. For example, the information processing apparatus 100 determines the transaction target as a boost target when the number of postings on the SNS for the transaction target is on an upward trend. For example, when the rate of increase in the number of postings on the SNS for a transaction target is equal to or greater than a predetermined value, the information processing apparatus 100 determines the transaction target as a boost target. For example, when there is an upward trend in the number of searches for a transaction object, the information processing apparatus 100 determines that transaction object as a boost target. For example, when the rate of increase in the number of searches for a transaction target is equal to or greater than a predetermined value, the information processing apparatus 100 determines that transaction target as a boost target.

Further, the information processing apparatus 100 may determine a boost target based on internal factors such as coupons and price reductions. The information processing apparatus 100 may determine a transaction target for which a coupon has been provided within a predetermined period as a boost target. The information processing apparatus 100 may determine a transaction target whose price has been reduced within a predetermined period as a boost target.

Further, the information processing apparatus 100 may determine the boost target according to the user to whom the ranking is provided. The information processing apparatus 100 may determine, as a boost target, a transaction target for which the user to whom the ranking is provided has browsed information most recently (for example, within one day after the ranking was provided). The information processing apparatus 100 may determine a transaction target purchased recently (for example, within three days after the ranking is provided) by a similar user similar to the user to whom the ranking is provided, as a boost target.

Further, the information processing device 100 may determine the timing of the boost process based on the transaction target information. The information processing device 100 may determine the timing of the boost process that varies depending on the transaction target. When the number of sales of the transaction target periodically fluctuates, the information processing apparatus 100 may determine the timing of the boost process according to the periodic fluctuation. When the peak sales volume of a certain transaction object is October 31, the information processing device 100 determines the time before the peak (for example, September 1) as the start timing of boost processing for the transaction object. You may

The information processing apparatus 100 may determine the timing of the boost process according to the seasonal variation in the sales volume of the transaction target. When the number of sales of a certain transaction target is on an upward trend toward the peak at the end of the year (end of December), the information processing device 100 determines the start timing of boost processing for the transaction target several months before the peak (for example, October). You may Further, when the number of sales of a certain transaction object is on an upward trend toward the peak at the end of the year (end of December), the information processing apparatus 100 performs boost processing for the transaction object from several months before the peak to the end of the year. You may decide to target

Note that the above is merely an example, and the information processing apparatus 100 may determine the boost target and the timing of the boost process using various information as appropriate. The information processing apparatus 100 generates a ranking that reflects the result of the boost processing performed on the determined boost target.

For example, the information processing apparatus 100 generates a ranking by performing a process of increasing the rank of a boost target in the ranking as a boost process. For example, the information processing device 100 increases the rank of the transaction object G23 when the transaction object G23 is determined as the boost target in the rankings in the order of the transaction objects G21, G22, G23, and G24.

In this case, for example, the information processing apparatus 100 may perform boost processing for the transaction object G23 and generate a ranking in which the transaction objects G21, G23, G22, and G24 are ranked in this order. Further, the information processing device 100 may perform boost processing for the transaction object G23 and generate a ranking in which the transaction objects G23, G21, G22, and G24 are ranked in this order. Note that the above-described process is merely an example of the boost process, and the information processing apparatus 100 may perform any process as the boost process as long as it can change (increase) the order of the boost target in the ranking. .

For example, the information processing apparatus 100 may generate a ranking by performing a process of increasing the score of a boost target in the ranking as a boost process. In this case, the information processing device 100 determines the order of each transaction object using the score after boost processing. For example, the information processing device 100 multiplies the score of the transaction target determined to be boosted by a predetermined coefficient (for example, 1.2), and ranks each transaction target using the boosted score. may be determined and a ranking generated.

For example, the information processing apparatus 100 includes first tab content in which search results of a search query are arranged and second tab content in which rankings corresponding to the search query and subjected to boost processing are arranged. to the terminal device 10 . The terminal device 10 that has received the content from the information processing device 100 displays the received content.

Through the above-described processing, the information processing device 100 determines a transaction target (boost target) to be boosted in the ranking, and generates a ranking that reflects the result of the boost processing performed on the determined boost target. do. Accordingly, the information processing apparatus 100 can provide appropriate content. Note that the above is merely an example, and the information processing apparatus 100 may use various types of information as appropriate to determine boost targets, execute boost processing, and generate rankings.

As described above, the information processing apparatus 100 may determine a boost target in consideration of seasonality. The information processing apparatus 100 may determine, as a boost target, a transaction target whose transaction target information includes information indicating seasonality, such as “spring XX” and “summer XX”. For example, the information processing apparatus 100 determines a transaction target approaching a peak as a boost target according to transaction target information including sales history, search count, PV count, SNS post count, price, and the like. The information processing device 100 may determine the period for performing the boost process according to the type (category) of the transaction target. The information processing apparatus 100 may determine a boost target or a period for performing the boost process according to the result of actually performing the boost process.

The information processing apparatus 100 may postpone the transaction target that has passed the peak without making it a boost target according to the sales history. The information processing apparatus 100 may advance the target of the transaction that is likely to reach its peak and determine it as the boost target. The information processing apparatus 100 may determine a transaction target whose sales have increased rapidly as a boost target ahead of schedule. The information processing device 100 may determine the boost target according to the ratio of the same type (category) of transaction targets.

The information processing apparatus 100 may perform boost processing for a transaction target at the timing when any element of the transaction target, such as the number of sales, the number of searches, or the number of PV, increases even slightly. Further, the information processing apparatus 100 may perform boost processing for a certain transaction object at the timing when any element such as the number of sales, the number of searches, or the number of PV of the transaction object increases by a predetermined threshold or more. Note that the information processing device 100 may change the timing according to the transaction target.

The information processing apparatus 100 may determine the timing of the boost process according to the change in the fluctuation factor for the transaction target such as a weather-related product that has a fluctuation factor as the cause of the peak. The information processing apparatus 100 may determine the timing of the boost process according to the non-variable factor for a transaction target that has a non-variable factor as the cause of the peak, such as a seasonal product such as a Halloween product. . In this way, the information processing apparatus 100 may use various information as appropriate to determine the timing of performing the boost process.

[1-3. summary〕
Through the above-described various types of processing, the information processing apparatus 100 can propose a search method of selecting from content that can be the decisive factor of “ranking” at a conspicuous position in the first view by providing a tab related to ranking in the content. Therefore, the information processing device 100 can reduce the possibility that a user who cannot select a transaction target by himself/herself will withdraw from the search result. In addition, the information processing apparatus 100 can promote the excursion of a user (light user) whose use time is shorter than the predetermined time.

For example, a use case is assumed in which there are many options (transaction targets) corresponding to a search query input by the user, the user has little prior knowledge, and is at a loss as to what to buy. In this case, for example, the information processing apparatus 100 provides rankings for each category, specification, and the like. This makes it easy for users to get an overview of transaction targets, deepen their intentions, and naturally narrow down their options, even for queries with broad intentions. In addition, since the information processing apparatus 100 does not forcibly narrow down to a specific category, it is possible to widen the range of proposals to the user and reduce the possibility that the user will withdraw.

In addition, the information processing apparatus 100 can make it easier for the user to embody the image of purchasing the transaction object by providing the content in which the transaction object is organized for each aspect. In addition, the information processing apparatus 100 provides content arranged according to brands or the like, thereby making it easier for the user to narrow down options based on trends, popularity, and the like.

For example, in the case of an expensive transaction object or a particular item (transaction object) that the user wants to examine by himself, a use case of wanting to compare the transaction object and purchase the transaction object without failure is assumed. In this case, for example, the information processing apparatus 100 provides content including a ranking of transaction objects that takes into account trends, post-purchase satisfaction, etc., based on transaction objects purchased by other users in the past. For example, the information processing device 100 aggregates and ranks the sales results of a plurality of sales sources (stores), thereby suppressing duplication of presentation of transaction targets and providing a ranking in which products and non-products are listed side by side. can do. As a result, the information processing apparatus 100 can compare the rankings with the user's satisfaction because the transaction targets with high comprehensiveness are lined up. In addition, the information processing apparatus 100 can separate the differences for each sales source (store) by setting the same product as one ranking target, and can appropriately provide options for comparing.

In this way, the information processing apparatus 100 can provide appropriate content by providing rankings through various processes.

[2. Configuration of information processing system]
As shown in FIG. 9 , the information processing system 1 includes a terminal device 10 , an external device 20 and an information processing device 100 . The terminal device 10, the external device 20, and the information processing device 100 are connected via a network N so as to be communicable by wire or wirelessly. The information processing system 1 shown in FIG. 9 may include a plurality of terminal devices 10, a plurality of external devices 20, and a plurality of information processing devices 100. FIG.

The terminal device 10 according to the embodiment is an information processing device used by a user who accesses content such as web pages displayed on a browser and content for applications. For example, the terminal device 10 is a desktop PC (Personal Computer), a notebook PC, a tablet terminal, a mobile phone, a PDA (Personal Digital Assistant), or the like. Note that the terminal device 10 is not limited to the above example, and may be, for example, a smart watch or a wearable device.

The external device 20 according to the embodiment is an information processing device that provides various types of information, and is realized by, for example, a server device or a cloud system. For example, the external device 20 provides user information as various information. As another example, the external device 20 may be an Internet shopping site, an electronic shopping mall, a flea market site, an auction site, a travel or restaurant reservation site, a credit card contract site, a financial product providing site, or the like. provide information about traded objects in

The information processing device 100 according to the embodiment is an information processing device that can communicate with various devices via a predetermined network N such as the Internet, and is realized by, for example, a server device or a cloud system. For example, the information processing device 100 is communicably connected to various other devices via a network N. FIG.

[3. Configuration of Information Processing Device]
An example of the functional configuration of the information processing apparatus 100 described above will be described below. FIG. 9 is a diagram illustrating a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 9, the information processing apparatus 100 has a communication section 110, a storage section 120, and a control section .

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information to and from other various devices.

(storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 also has a user information storage unit 121 , a transaction target information storage unit 122 , a content storage unit 123 , and a ranking information storage unit 124 .

(User information storage unit 121)
The user information storage unit 121 stores various user information about users. 10 is a diagram illustrating an example of a user information storage unit according to the embodiment; FIG. In the example shown in FIG. 10, the user information storage unit 121 has items such as "user ID" and "user information". For example, "user information" includes items such as "attribute information", "purchase history", and "browsing history".

"User ID" is an identifier that identifies a user. The "attribute information" is attribute information related to attributes of the user associated with the "user ID". For example, the attribute information includes age, gender, phone number, address, etc. of the user. In addition, the attribute information described above is only an example, and various information such as information indicating demographic attributes such as occupation other than age and gender, information indicating psychographic attributes such as interests and lifestyles, etc. may be included.

“Purchase history” is the purchase history of purchases made by the user associated with the “user ID”. For example, the purchase history includes information on the transaction object purchased by the user, the type of transaction object, the number of purchases of the transaction object, information on the date and time when the transaction object was purchased, and the like.

"Browsing history" is a history of content being browsed by the user associated with the "user ID". For example, the “browsing history” may be a history of content displayed on the terminal device 10 used by the user. For example, the browsing history includes information on content browsed (displayed) by the user, the type of content, the number of times the content was displayed, and information on the date and time the content was displayed.

For example, in FIG. 10, "U1" identified by the user ID has attribute information "CH1", purchase history "PH1", and display history "WA1". Note that in the example shown in FIG. 10, the attribute information and the like are represented by abstract codes such as "CH1", but the attribute information and the like are represented by specific numerical values, specific character strings, and various types of information. It may be a file format or the like that includes.

It should be noted that the user information storage unit 121 may store various types of information, not limited to the above, depending on the purpose. The user information storage unit 121 may store, for each user, information indicating the number of times the information is displayed for each transaction target, for example, the number of times the user views the information.

(Transaction target information storage unit 122)
The transaction target information storage unit 122 stores various transaction target information related to the transaction target. 11 is a diagram illustrating an example of a transaction target information storage unit according to the embodiment; FIG. In the example shown in FIG. 11, the transaction target information storage unit 122 includes items such as "transaction target ID", "transaction target", "transaction target information", "category", and "product specific information". In FIG. 11, in order to explain the "category" and "product specific information", they are described as separate items from the "transaction target information", but the category information and product information are included in the transaction target information. may

Further, although illustration is omitted, the transaction target information storage unit 122 stores information indicating the perspective to which each transaction target corresponds in addition to the category. For example, the transaction target information storage unit 122 stores information indicating a plurality of aspects such as the category, brand, usage scene, specifications, problems that can be solved by the transaction target, and human concerns that can be resolved by the transaction target to which each transaction target corresponds. is associated with each transaction object and stored.

"Transaction object ID" is an identifier for identifying a transaction object. “Transaction object” indicates a transaction object associated with the “transaction object ID”. The “transaction object information” is the transaction object information of the transaction object identified by the “transaction object ID”.

"Category" is information on the category to which the transaction object identified by the "transaction object ID" corresponds. The “product identification information” is information related to the product to which the transaction object identified by the “transaction object ID” corresponds.

For example, in FIG. 11, "M1" identified by the trading object ID has trading object "MA1". In the example shown in FIG. 11, the transaction target is represented by an abstract code such as "MA1", but the transaction target is a specific character string (product name, etc.) indicating the product etc. sold by each seller. ).

Further, in FIG. 11, "M1" identified by the transaction object ID has transaction object information "MD1". In the example shown in FIG. 11, the transaction target information is represented by an abstract code such as "MD1", but the transaction target information may be in a file format or the like containing various information on the transaction target.

Also, in FIG. 11, "M1" identified by the transaction object ID has a category of "CT1". In the example shown in FIG. 11, the category is represented by an abstract code such as "CT1", but the category is information indicating the category of the transaction object.

Further, in FIG. 11, "M1" identified by the transaction object ID has "PD1" as the product identification information. In the example shown in FIG. 11, the product identification information is represented by an abstract code such as "PD1". It is information (for example, JAN code, etc.). Further, the product identification information is information indicating that there is no product corresponding to the transaction object (for example, a flag or the like indicating that there is no such product) when there is no product corresponding to the transaction object.

Note that the transaction object information storage unit 122 may store various types of information, not limited to the above, depending on the purpose. For example, the transaction target information storage unit 122 may describe information such as the score and display count corresponding to each transaction target.

(Content storage unit 123)
The content storage unit 123 stores information about content. 12 is a diagram illustrating an example of a content storage unit according to the embodiment; FIG. In the example shown in FIG. 12, the content storage unit 123 has items such as "content ID" and "content".

“Content ID” is an identifier for identifying content. "Content" is information about the content associated with the "content ID". Specifically, the content may indicate information about the contents of the content.

For example, the content is content related to a portal site. As another example, the content may be content related to a news site, an auction site, a weather forecast site, a shopping site, a finance (stock price) site, or the like.

Also, the content may be content related to a route search site, a map providing site, a travel site, a restaurant introducing site, a web blog site, an SNS site, or the like.

For example, in FIG. 12, "C1" identified by the content ID has content "CO1". In the example shown in FIG. 12, the contents and the like are represented by abstract codes such as "CO1", but the contents and the like are represented by specific numerical values, specific character strings, and files containing various information. format or the like.

Note that the content storage unit 123 may store various types of information, not limited to the above, depending on the purpose.

(Ranking information storage unit 124)
The ranking information storage unit 124 stores various kinds of information used to generate rankings. The ranking information storage unit 124 stores information indicating criteria for ranking transaction targets (ranking criteria). The ranking information storage unit 124 stores information indicating a ranking criterion that ranks are ranked in descending order of score. For example, the ranking information storage unit 124 stores information used for calculating various scores of transaction targets. The ranking information storage unit 124 stores score functions used to calculate various scores of transaction targets.

Note that the ranking information storage unit 124 may store various types of information, not limited to the above, depending on the purpose.

(control unit 130)
The control unit 130 is a controller, and for example, various programs (information processing programs) stored in a storage device inside the information processing apparatus 100 are controlled by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. example) is implemented by executing the RAM as a work area. Also, the control unit 130 is a controller, and is implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 9, the control unit 130 includes an acquisition unit 131, a reception unit 132, a determination unit 133, an estimation unit 134, a generation unit 135, and a provision unit 136, and has information described below. Realize or perform the function or action of a process. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 9, and may be another configuration as long as it performs information processing to be described later.

(Acquisition unit 131)
Acquisition unit 131 acquires various types of information. Acquisition unit 131 acquires various types of information from storage unit 120 . The acquisition unit 131 acquires various types of information from the user information storage unit 121, the transaction target information storage unit 122, the content storage unit 123, the ranking information storage unit 124, and the like.

Acquisition unit 131 receives various types of information from an external information processing device via communication unit 110 . The acquisition unit 131 receives various information from the terminal device 10 or the external device 20 . For example, the acquisition unit 131 acquires user information about the user from the external device 20 . In FIG. 1, the acquisition unit 131 obtains, as user information, user attribute information, purchase history on Internet shopping, electronic shopping malls, auction sites, flea market sites, etc., content display history, etc. from the external device 20. get. Then, the acquisition unit 131 stores this user information in the user information storage unit 121 . For example, the acquisition unit 131 acquires user information from the external device 20 and updates the user information stored in the user information storage unit 121 every predetermined period.

Also, the acquisition unit 131 acquires information about the transaction target from the external device 20 . For example, the acquisition unit 131 acquires from the external device 20 information about a transaction target traded at an auction site or a flea market site. Then, the acquisition unit 131 stores the information about the transaction object in the transaction object information storage unit 122 . For example, the acquisition unit 131 acquires information on the transaction object from the external device 20 and updates the information on the transaction object stored in the transaction object information storage unit 122 every predetermined period.

The acquisition unit 131 acquires transaction target information regarding a transaction target. The acquisition unit 131 acquires transaction target information including the sales history of the transaction target. The acquisition unit 131 acquires transaction target information including the number of orders for the transaction target. The acquisition unit 131 acquires transaction object information including a period that has passed since the date and time when the transaction object was sold. The acquisition unit 131 acquires transaction target information including the number of sales of the transaction target. The acquisition unit 131 acquires transaction target information including the number of times information indicating the transaction target has been viewed.

The acquisition unit 131 acquires transaction target information including the number of reviews for the transaction target. The acquisition unit 131 acquires transaction target information including evaluation of the transaction target. The acquisition unit 131 acquires transaction target information including external factors related to the transaction target. The acquisition unit 131 acquires transaction target information including a post about a transaction target on the SNS. The acquisition unit 131 acquires transaction target information including the number of searches related to the transaction target. The acquisition unit 131 acquires transaction target information including internal factors related to the transaction target. The acquisition unit 131 acquires transaction target information including an incentive for the transaction target. The acquisition unit 131 acquires transaction target information including coupons for transaction targets. The acquisition unit 131 acquires transaction target information including price reductions related to transaction targets.

The acquisition unit 131 acquires element information regarding a plurality of elements included in transaction target information. The acquisition unit 131 acquires element information indicating the tendency of a plurality of elements included in transaction target information. Acquisition unit 131 acquires a score corresponding to each of the plurality of elements.

The acquisition unit 131 acquires element information indicating trends of a plurality of elements including the number of orders to be traded. The acquisition unit 131 acquires element information indicating trends of a plurality of elements including the number of views of information indicating a transaction target. The acquisition unit 131 acquires element information indicating trends of a plurality of elements including the number of reviews for the transaction target. The acquisition unit 131 acquires element information indicating trends of a plurality of elements including the number of reservations for transactions.

The acquisition unit 131 acquires element information indicating trends of a plurality of elements including external factors related to the transaction target. The acquisition unit 131 acquires element information indicating a tendency of a plurality of elements including posts related to transaction targets on the SNS. The acquisition unit 131 acquires element information indicating trends of a plurality of elements including the number of searches for a transaction target. The acquisition unit 131 acquires element information indicating trends of a plurality of elements including internal factors related to the transaction target. Acquisition unit 131 acquires element information indicating trends of a plurality of elements including incentives for trade targets. The acquisition unit 131 acquires element information indicating trends of a plurality of elements including coupons targeted for transactions. The acquisition unit 131 acquires element information indicating trends of a plurality of elements including price reductions related to transaction targets.

In addition, the acquisition unit 131 acquires from the terminal device 10 information indicating the number of times the trade object is displayed (the number of times the user browses). For example, the acquisition unit 131 acquires the display count of the content and the display count of each transaction target from the terminal device 10 . In addition, the acquisition unit 131 acquires control information for acquiring the number of times of display provided in advance together with the content. Then, the acquisition unit 131 stores the display count in the transaction object information storage unit 122 .

(Reception unit 132)
The reception unit 132 receives various requests. The reception unit 132 receives various requests from an external information processing device. The reception unit 132 receives information indicating various requests from an external information processing device via the communication unit 110 . For example, the receiving unit 132 receives requests from the terminal device 10 or the external device 20 . The accepting unit 132 accepts a search query (query) input by the user from the terminal device 10 . For example, the reception unit 132 receives a search query (query) input by the user from the terminal device 10 as a request for provision of content related to the query.

(Determination unit 133)
The determination unit 133 executes determination processing for determining various pieces of information. For example, the determination unit 133 executes determination processing based on various information acquired by the acquisition unit 131 . The determination unit 133 executes determination processing based on various information stored in the storage unit 120 . For example, the determination unit 133 executes determination processing based on various information received from an external information processing device.

For example, the determination unit 133 executes determination processing based on information estimated by the estimation unit 134 . For example, the determination unit 133 executes determination processing based on information generated by the generation unit 135 .

The determining unit 133 determines a related aspect, which is an aspect that satisfies a predetermined condition in relation to the search query, among the plurality of aspects corresponding to the transaction target. The determination unit 133 determines a perspective having a high degree of relevance to the search query among the plurality of perspectives as a relevant perspective. The determining unit 133 determines, among the plurality of perspectives, a perspective having a score indicating a degree of relevance to the search query equal to or higher than a predetermined threshold as a relevant perspective.

The determination unit 133 determines a related aspect from among a plurality of aspects including aspects relating to the category of the transaction object. The determination unit 133 determines a related aspect from among a plurality of aspects including aspects related to the brand to be traded. The determination unit 133 determines a related aspect from among a plurality of aspects including aspects related to usage scenes of the transaction target. The determination unit 133 determines a related aspect from among a plurality of aspects including aspects related to the specifications of the transaction target. The determination unit 133 determines a related aspect from among a plurality of aspects including aspects related to issues that can be solved by the transaction target. The determination unit 133 determines a related aspect from among a plurality of aspects including aspects related to a person's worries that can be resolved by the transaction object.

The determination unit 133 determines the target transaction object, which is the transaction object to be displayed as a ranking, based on the transaction object information regarding the transaction object. The determination unit 133 determines the target transaction object based on the transaction object information including the sales history of the transaction object. The determination unit 133 determines a target transaction object based on the transaction object information including the number of orders of the transaction object. The determination unit 133 determines the target transaction object based on the transaction object information including the period that has passed since the date and time when the transaction object was sold.

The determining unit 133 determines the target transaction object based on the transaction object information including the number of sales of the transaction object. The determination unit 133 determines a target transaction object based on the transaction object information including the number of times the information indicating the transaction object has been browsed. The determining unit 133 determines a target transaction object based on transaction object information including the number of reviews for the transaction object. The determining unit 133 determines the target transaction object based on the transaction object information including the evaluation of the transaction object.

The determination unit 133 determines a target transaction object based on transaction object information including external factors related to the transaction object. The determination unit 133 determines a target transaction object based on transaction object information including a post about a transaction object on the SNS. The determination unit 133 determines the target transaction object based on the transaction object information including the number of searches related to the transaction object. The determination unit 133 determines a target transaction object based on transaction object information including internal factors related to the transaction object. The determination unit 133 determines a target transaction object based on transaction object information including an incentive for the transaction object. The determination unit 133 determines a target transaction object based on transaction object information including a coupon for the transaction object. The determination unit 133 determines the target transaction object based on the transaction object information including the price reduction related to the transaction object.

The determination unit 133 determines a group of transaction objects to be the same product among the plurality of transaction objects corresponding to the search query. The determination unit 133 determines a group of transaction objects based on the transaction object information of each of the plurality of transaction objects. The determining unit 133 determines a group of transaction objects based on transaction object information including identification information associated with each of a plurality of transaction objects. The determining unit 133 determines a group of transaction objects based on transaction object information including identification information associated with each of a plurality of transaction objects. The decision unit 133 decides a transaction object with matching identification information as a transaction object group. The determination unit 133 determines a group of transaction objects among a plurality of transaction objects to be traded in electronic commerce.

Based on the user information of the user who has input the search query, the determination unit 133 determines a target transaction target, which is a transaction target displayed as a ranking, from the transaction targets corresponding to the search query. The determination unit 133 determines a target transaction object based on user information including user attribute information. The determination unit 133 determines the transaction object selected by the similar user who is similar to the user's attribute as the target transaction object. The determining unit 133 determines a transaction object purchased by a similar user having similar attributes of the user as a target transaction object.

The determination unit 133 determines a boost target, which is a target of a boost process for boosting the ranking, among the target of the transaction. The determination unit 133 determines a boost target based on the transaction target information regarding the transaction target.

The determining unit 133 determines the boost target based on the transaction target information including the sales history of the transaction target. The determination unit 133 determines the boost target based on the transaction target information including the number of sales of the transaction target. The determining unit 133 determines the boost target based on the transaction target information including the transition of the sales volume of the transaction target. The determination unit 133 determines a boost target based on the transaction target information including the number of times the information indicating the transaction target has been viewed. The determination unit 133 determines a boost target based on transaction target information including the number of reviews for the transaction target.

The determination unit 133 determines a boost target based on transaction target information including external factors related to the transaction target. The determination unit 133 determines a boost target based on transaction target information including postings related to the transaction target on the SNS. The determination unit 133 determines a boost target based on the transaction target information including the number of searches related to the transaction target.

The determination unit 133 determines the timing of the boost process based on the transaction target information. The determination unit 133 determines the timing of the boost process that varies according to the transaction target. The decision unit 133 decides the timing of the boost process when the trading object has a variable factor.

The determination unit 133 determines a boost target according to the user to whom the ranking is provided. The determination unit 133 determines a boost target based on user information about the user. The determination unit 133 determines a boost target among transaction targets traded in electronic commerce.

(Estimation unit 134)
The estimation unit 134 performs estimation processing for estimating various information. For example, the estimation unit 134 executes estimation processing based on various information acquired by the acquisition unit 131 . The estimation unit 134 executes estimation processing based on various information stored in the storage unit 120 . The estimation unit 134 executes estimation processing based on various information received from an external information processing device.

For example, the estimation unit 134 performs estimation processing based on information determined by the determination unit 133 . For example, the estimation unit 134 performs estimation processing based on information generated by the generation unit 135 .

The estimating unit 134 estimates the reason for the order of the target transaction object, which is the transaction object displayed as the ranking, based on the transaction object information about the transaction object. The estimating unit 134 estimates the reason based on trends of multiple elements included in the transaction target information. The estimation unit 134 estimates the reason based on the score corresponding to each of the multiple elements. The estimating unit 134 estimates the reason based on the element with the highest degree of influence among the plurality of elements.

The estimating unit 134 estimates a target transaction target based on trends of a plurality of factors including the number of orders for the transaction target. The estimating unit 134 estimates the target transaction object based on the tendency of a plurality of elements including the number of views of the information indicating the transaction object. The estimating unit 134 estimates the target transaction target based on trends of a plurality of factors including the number of reviews for the transaction target. The estimating unit 134 estimates a target transaction target based on trends of a plurality of elements including the number of reservations for the transaction target.

The estimating unit 134 estimates a target transaction target based on trends of a plurality of elements including external factors related to the transaction target. The estimating unit 134 estimates the target transaction target based on the tendency of a plurality of elements including posts related to the transaction target on the SNS. The estimating unit 134 estimates the target transaction object based on the tendency of a plurality of factors including the number of searches related to the transaction object. The estimating unit 134 estimates the target transaction target based on the tendency of a plurality of elements including internal factors related to the transaction target. The estimating unit 134 estimates a target transaction target based on trends of a plurality of elements including an incentive for target transaction targets. The estimating unit 134 estimates a target transaction target based on trends of a plurality of elements including coupons targeted for the transaction target. The estimating unit 134 estimates the target transaction object based on trends of a plurality of elements including price reductions related to the transaction object.

(Generating unit 135)
The generation unit 135 executes generation processing for estimating various information. For example, the generation unit 135 executes generation processing based on various information acquired by the acquisition unit 131 . The generation unit 135 executes generation processing based on various information stored in the storage unit 120 . The generation unit 135 executes generation processing based on various information received from an external information processing device.

For example, the generation unit 135 executes generation processing based on information determined by the determination unit 133 . For example, the generation unit 135 executes generation processing based on information generated by the generation unit 135 .

The generation unit 135 generates a ranking based on the transaction target information regarding the transaction target. The generation unit 135 generates a ranking based on transaction target information including the sales history of the transaction target. The generation unit 135 generates a ranking based on transaction target information including the number of orders for the transaction target. The generation unit 135 generates a ranking based on transaction object information including a period that has passed since the date and time when the transaction object was sold. The generation unit 135 generates a ranking based on transaction target information including the number of sales of the transaction target. The generation unit 135 generates a ranking based on the transaction target information including the number of times the information indicating the transaction target has been viewed. The generation unit 135 generates a ranking based on transaction target information including the number of reviews for the transaction target. The generation unit 135 generates a ranking based on transaction object information including evaluations of transaction objects.

The generation unit 135 generates a ranking based on transaction target information including external factors related to the transaction target. The generation unit 135 generates rankings based on transaction target information including posts about transaction targets on the SNS. The generation unit 135 generates a ranking based on transaction target information including the number of searches related to the transaction target. The generation unit 135 generates a ranking based on transaction target information including internal factors related to the transaction target. The generation unit 135 generates a ranking based on transaction target information including coupons for transaction targets. The generation unit 135 generates a ranking based on transaction target information including price reductions related to transaction targets.

The generation unit 135 calculates the score of the transaction object based on the transaction object information related to the transaction object. The generation unit 135 receives the transaction target information of the transaction target and calculates the score of the transaction target using a function (score function) that outputs the score of the transaction target. The generation unit 135 generates a ranking of the transaction target based on the calculated score.

The generation unit 135 calculates a partial score corresponding to each of the multiple elements included in the transaction target information. The generation unit 135 receives as input information of a plurality of elements included in the transaction target information, and uses a function (score function) that outputs a partial score of the element to generate a portion of each of the plurality of elements included in the transaction target information. Calculate the score. For example, the generation unit 135 calculates the average value of the partial scores corresponding to each of the multiple elements included in the transaction object information as the score of the transaction object. For example, the generation unit 135 calculates the score of the transaction object by summing the partial scores corresponding to each of the multiple elements included in the transaction object information.

Generation unit 135 generates content including a first tab and a second tab. The generation unit 135 generates content including a first tab on which search results corresponding to the search query are arranged and a second tab on which rankings of transaction targets corresponding to the search query are arranged. The generation unit 135 generates content in which either the first tab or the second tab is displayed in a predetermined display area of the content according to the user's selection. The generation unit 135 generates content including a first tab and a second tab for the search query input by the user.

The generation unit 135 generates content indicating the ranking of the transaction target based on the relevant aspect and the search query determined by the determination unit 133 . When there are a plurality of relevant aspects determined by the determining unit 133, the generation unit 135 generates content including a plurality of rankings based on each of the plurality of related aspects and the search query. When the determination unit 133 determines that there is one related aspect, the generating unit 135 generates content including one ranking based on the one related aspect and the search query. The generation unit 135 generates content to be traded in electronic commerce. The generation unit 135 generates content to be displayed by switching between the first tab and the second tab according to the user's selection.

The generation unit 135 generates content indicating the ranking of the target transaction determined by the determination unit 133 . The generation unit 135 generates content for a target transaction to be traded in electronic commerce.

The generation unit 135 generates content indicating the reason for the target transaction estimated by the estimation unit 134 . The generation unit 135 generates content in which the reason is arranged near the information indicating the target transaction target in the ranking. The generation unit 135 generates content indicating the reason for the target transaction subject to be traded in electronic commerce.

The generation unit 135 generates a ranking with the transaction target group determined by the determination unit 133 as one product. The generation unit 135 generates a ranking in which one transaction target group is treated as one product. The generation unit 135 generates rankings for individual transaction objects, which are transaction objects that are not the same product, and products corresponding to the transaction object group. The generation unit 135 generates a ranking in which individual transaction targets and products are mixed.

The generation unit 135 generates a ranking using the first score of the individual transaction target and the second score of the product. The generator 135 generates a ranking using a first score and a second score based on scores calculated for each of a plurality of transaction targets. The generation unit 135 generates a ranking using the second score of the product calculated based on the number of sales of each of the transaction target group. The generating unit 135 generates a ranking using the second score of the product calculated based on the review of each of the trading object group. The generation unit 135 generates a ranking using the second score of the product calculated based on the evaluation of the seller who sells each of the plurality of transaction targets.

The generation unit 135 generates content indicating rankings corresponding to other rankings provided to similar users who are similar to the attributes of the user. The generating unit 135 generates content indicating rankings corresponding to other rankings provided when similar users select transaction targets. The generating unit 135 generates a ranking that reflects the result of the boost processing performed on the boost target determined by the determining unit 133 .

The generating unit 135 appropriately uses various techniques to generate various information such as a screen (content) to be provided to an external information processing apparatus. The generation unit 135 generates a screen (content) and the like to be provided to the terminal device 10 . For example, the generation unit 135 generates a screen (content) and the like to be provided to the terminal device 10 based on information stored in the storage unit 120 . The generation unit 135 generates each content such as the content CT1 and CT2. The generation unit 135 may generate a screen (content) or the like by any process as long as the screen (content) or the like to be provided to an external information processing apparatus can be generated. For example, the generation unit 135 generates a screen (content) to be provided to the terminal device 10 by appropriately using various techniques related to image generation, image processing, and the like. For example, the generation unit 135 generates a screen (content) to be provided to the terminal device 10 using various technologies such as Java (registered trademark) as appropriate. Note that the generation unit 135 may generate a screen (content) to be provided to the terminal device 10 based on CSS, JavaScript (registered trademark), or HTML format. Further, for example, the generating unit 135 may generate screens (contents) in various formats such as JPEG (Joint Photographic Experts Group), GIF (Graphics Interchange Format), PNG (Portable Network Graphics), and the like.

(Providing unit 136)
The providing unit 136 provides various information. The providing unit 136 transmits various types of information to an external information processing device via the communication unit 110 . The providing unit 136 transmits various information to the terminal device 10 or the external device 20 . The providing unit 136 transmits content to the terminal device 10 . The providing unit 136 transmits information about the transaction target to the terminal device 10 .

The providing unit 136 provides information generated by the generating unit 135 . The providing unit 136 provides content including information generated by the generating unit 135 . The providing unit 136 provides content including rankings of trading objects. The providing unit 136 transmits the content C1 of FIG. 2 to the terminal device 10. FIG.

The providing unit 136 provides content including a first tab in which search results corresponding to a search query are arranged and a second tab in which rankings of transaction targets corresponding to the search query are arranged. The providing unit 136 provides content generated by the generating unit 135 . The providing unit 136 provides content including a second tab in which rankings of trading objects traded in electronic commerce are arranged.

The providing unit 136 transmits content to the terminal device 10 used by the user. The providing unit 136 transmits the content to the terminal device 10 that displays either the first tab or the second tab in a predetermined display area of the content according to the user's selection. The providing unit 136 provides the terminal device 10 with content including a first tab and a second tab targeted for the search query input by the user.

The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information regarding transaction targets are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including the sales history of the transaction target are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including the number of orders of the transaction target are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction object information including a period of time elapsed since the date and time when the transaction object was sold are arranged.

The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including the number of sales of the transaction target are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including the number of views of information indicating the transaction target are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including the number of reviews for the transaction target are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including evaluation of the transaction target are arranged.

The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including external factors related to the transaction target are arranged. The provision unit 136 provides content including a second tab in which rankings generated based on transaction target information including posts about transaction targets on the SNS are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including the number of searches related to the transaction target are arranged.

The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including internal factors related to the transaction target are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including coupons for transaction targets are arranged. The providing unit 136 provides content including a second tab in which rankings generated based on transaction target information including price reductions related to transaction targets are arranged.

The providing unit 136 provides content indicating the ranking of transaction targets based on the relevant aspect and the search query determined by the determining unit 133 . When there are a plurality of relevant aspects determined by the determining unit 133, the providing unit 136 provides content including a plurality of rankings based on each of the plurality of related aspects and the search query. The providing unit 136 provides content including one ranking based on one related aspect and the search query when the determining unit 133 determines one related aspect. The providing unit 136 provides contents to be traded in electronic commerce. The providing unit 136 transmits the content to the terminal device 10 that switches between the first tab and the second tab according to the user's selection.

The providing unit 136 provides content indicating the ranking of the target transaction determined by the determining unit 133 . The providing unit 136 provides contents for transactions to be made in electronic commerce.

The provision unit 136 provides content indicating the reason for the target transaction estimated by the estimation unit 134 . The providing unit 136 transmits the content including the ranking to the terminal device 10 used by the user. The providing unit 136 transmits the content in which the reason is arranged near the information indicating the target transaction target in the ranking. The providing unit 136 provides content indicating the reason for the target transaction subject to be traded in electronic commerce.

The providing unit 136 provides content indicating the ranking generated by the generating unit 135 . The providing unit 136 provides content including a first tab on which search results corresponding to a search query are arranged and a second tab on which rankings are arranged.

The providing unit 136 provides a ranking with the trading object group as one product. The providing unit 136 provides a ranking in which one transaction target group is treated as one product. The providing unit 136 provides a ranked ranking for individual transaction objects, which are transaction objects that are not the same product, and products corresponding to the transaction object group. The providing unit 136 provides a ranking in which individual transaction targets and products are mixed.

The providing unit 136 provides content indicating rankings corresponding to other rankings provided to similar users who are similar to the attributes of the user. The providing unit 136 provides content indicating rankings corresponding to other rankings provided when similar users select transaction targets.

The providing unit 136 provides content indicating a ranking reflecting the results of the boost processing. The providing unit 136 transmits the content indicating the ranking reflecting the result of the boost processing to the terminal device 10 used by the user.

[4. Processing procedure]
Next, the procedure of information processing executed by the information processing apparatus 100 according to the embodiment will be described with reference to FIGS. 13 to 19. FIG. 13 to 19 are flowcharts showing an example of the flow of information processing executed by the information processing apparatus.

First, FIG. 13 will be described. For example, FIG. 13 shows an example of processing performed by the information processing apparatus 100 from acquisition of a search query from a user to provision of content. In FIG. 13, the information processing apparatus 100 acquires a search query from the user (step S101). Then, the information processing apparatus 100 generates content including a first tab in which search results corresponding to the search query are arranged and a second tab in which rankings of trading objects corresponding to the search query are arranged (step S102). Then, the information processing apparatus 100 renders content including the first tab and the second tab (step S103).

Next, FIG. 14 will be described. For example, FIG. 14 shows an example of providing rankings based on related aspects of queries performed by the information processing apparatus 100 . In FIG. 14 , the information processing apparatus 100 determines a relevant aspect that is an aspect that satisfies a predetermined condition in relation to the search query, among a plurality of aspects corresponding to the transaction target (step S201). Then, the information processing apparatus 100 provides content indicating the ranking of the transaction target based on the related aspect and the search query (step S202).

Next, FIG. 15 will be described. For example, FIG. 15 shows an example of providing rankings for narrowed down transaction targets performed by the information processing apparatus 100 . In FIG. 15, the information processing apparatus 100 determines the target transaction object, which is the transaction object to be displayed as a ranking, based on the transaction object information regarding the transaction object (step S301). Then, the information processing device 100 provides content indicating the ranking of the target transaction object (step S302).

Next, FIG. 16 will be described. For example, FIG. 16 shows an example of the ranking provided by the information processing apparatus 100 indicating the reason for the ranking. In FIG. 16, the information processing apparatus 100 estimates the reason for the order of the target transaction object, which is the transaction object displayed as the ranking, based on the transaction object information about the transaction object (step S401). Then, the information processing device 100 provides content indicating the reason for the target transaction (step S402).

Next, FIG. 17 will be described. For example, FIG. 17 shows an example of ranking generation performed by the information processing apparatus 100 with the same product (trade target) as one ranking target. In FIG. 17, the information processing apparatus 100 determines a group of business objects to be the same product among the plurality of business objects corresponding to the search query (step S501). Then, the information processing apparatus 100 generates a ranking with the trading object group as one product (step S502). For example, the information processing device 100 provides the generated content.

Next, FIG. 18 will be described. For example, FIG. 18 shows an example of providing rankings for transaction targets according to users performed by the information processing apparatus 100 . In FIG. 18, the information processing apparatus 100 determines the target transaction object, which is the transaction object to be displayed as a ranking, from the transaction object corresponding to the search query based on the user information of the user who entered the search query (step S601). Then, the information processing apparatus 100 provides content indicating the ranking of the target transaction object (step S602).

Next, FIG. 19 will be described. For example, FIG. 19 shows an example of boosted ranking generation for a specific trading object by boost processing performed by the information processing apparatus 100 . In FIG. 19, the information processing apparatus 100 determines a target transaction target, which is a target transaction target for boost processing for boosting ranking, among the transaction targets (step S701). Then, the information processing device 100 generates a ranking that reflects the result of the boost processing performed on the target transaction object (step S702). For example, the information processing device 100 provides the generated content.

[5. Modification]
The information processing apparatus 100 described above may be embodied in various forms other than the above embodiment. Therefore, other embodiments of the information processing apparatus 100 will be described below.

[5-1. user〕
In the above embodiment, a user registered as a member of a predetermined service has been described as an example, but it is not necessary to be limited to the above example. For example, the user may be any user, for example, a user who is not registered as a member of a predetermined service.

[5-2. Transaction target]
In the above embodiment, an example of a transaction target that is traded on an electronic shopping mall has been described, but the above example does not have to be limited. For example, the trading object may be any trading object. For example, the trading object may be a limited quantity trading object. Also, the transaction object may be a transaction object traded through Internet shopping, an auction site, a flea market site, or the like.

[5-3. Provide information on the transaction object]
In the above embodiment, an example of information processing in which the information processing device 100 provides content to the terminal device 10 has been described, but the above example may not be limiting. For example, an external server may provide content to the terminal device 10 . In this case, the information processing device 100 may provide the external server with information on the transaction target.

For example, the external server provides content regarding portal sites as an example of content. In this case, the information processing apparatus 100 may provide the external server with an image of the transaction object, information on the layout when arranged in the content, etc., as the information on the transaction object.

[5-4. program〕
Also, the information processing apparatus 100 according to the above-described embodiment is implemented by, for example, a computer 1000 configured as shown in FIG. FIG. 20 is a diagram illustrating an example of a hardware configuration; A computer 1000 is connected to an output device 1010 and an input device 1020, and an arithmetic device 1030, a primary storage device 1040, a secondary storage device 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected via a bus 1090. have

The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The primary storage device 1040 is a memory device such as a RAM that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used for various calculations by the arithmetic device 1030 and various databases are registered. It is realized by

The output IF 1060 is an interface for transmitting information to be output to the output device 1010 that outputs various types of information such as a monitor and a printer. It is realized by a connector conforming to a standard such as HDMI (registered trademark) (High Definition Multimedia Interface). Also, the input IF 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, scanner, etc., and is realized by, for example, USB.

Note that the input device 1020 includes, for example, optical recording media such as CDs (Compact Discs), DVDs (Digital Versatile Discs), PDs (Phase change rewritable discs), magneto-optical recording media such as MOs (Magneto-Optical discs), and tapes. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like. Also, the input device 1020 may be an external storage medium such as a USB memory.

Network IF 1080 receives data from other devices via network N and sends the data to arithmetic device 1030, and also transmits data generated by arithmetic device 1030 via network N to other devices.

The arithmetic device 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070 . For example, arithmetic device 1030 loads a program from input device 1020 or secondary storage device 1050 onto primary storage device 1040 and executes the loaded program.

For example, when the computer 1000 functions as the information processing device 100 , the arithmetic device 1030 of the computer 1000 implements the functions of the control unit 130 by executing a program loaded on the primary storage device 1040 .

[5-5. others〕
Further, among the processes described in the above embodiments and modifications, all or part of the processes described as being performed automatically can be performed manually, or described as being performed manually. All or part of the processing can also be performed automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

Also, the above-described embodiments and modifications can be appropriately combined within a range that does not contradict the processing content.

Also, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

[6. effect〕
As described above, the information processing device 100 according to the embodiment has the estimating unit 134 and the providing unit 136 . The estimating unit 134 estimates the reason for the order of the target transaction object, which is the transaction object displayed as the ranking, based on the transaction object information about the transaction object. The provision unit 136 provides content indicating the reason for the target transaction estimated by the estimation unit 134 .

As described above, the information processing apparatus 100 according to the embodiment estimates the reason for the order of the target transaction object, which is the transaction object displayed as the ranking, based on the transaction object information related to the transaction object, and estimates the reason for the estimated target transaction object. It is possible to provide content that indicates the reason for the ranking by providing content that indicates the reason for the ranking.

Further, in the information processing apparatus 100 according to the embodiment, the providing unit 136 transmits content including rankings to the terminal device used by the user.

As described above, the information processing apparatus 100 according to the embodiment can provide the ranking together with the reason for the target transaction by transmitting the content including the ranking to the terminal device used by the user. You can provide content that shows

Further, in the information processing apparatus 100 according to the embodiment, the provision unit 136 transmits content in which the reason is arranged near the information indicating the target transaction target in the ranking.

As described above, the information processing apparatus 100 according to the embodiment transmits the content in which the reason is arranged near the information indicating the target transaction target in the ranking, so that the reason for the target transaction target is arranged in an appropriate position. Content can be provided and content can be provided that indicates the reasons for the ranking.

Also, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the reason based on trends of multiple elements included in the transaction target information.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the reason based on the tendencies of the multiple elements included in the transaction target information.

Also, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the reason based on scores corresponding to each of the plurality of elements.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the reason based on the score corresponding to each of the multiple elements.

Also, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the reason based on an element having a high degree of influence among the plurality of elements.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the reason based on the factor having the highest degree of influence among the plurality of factors.

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction object based on trends of a plurality of factors including the number of orders of the transaction object.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of factors including the number of orders of the transaction target.

Also, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction object based on the tendency of a plurality of elements including the number of views of the information indicating the transaction object.

As described above, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including the number of times the information indicating the transaction target is viewed. can.

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction target based on trends of a plurality of elements including the number of reviews for the transaction target.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including the number of reviews for the transaction target.

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction object based on the trends of a plurality of factors including the number of reservations for the transaction object.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including the number of reservations for the transaction target.

Also, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction object based on the tendency of a plurality of elements including external factors related to the transaction object.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including external factors related to the transaction target.

Further, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction target based on the tendency of a plurality of elements including the posts related to the transaction target on the SNS.

As described above, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including the posting regarding the transaction target on the SNS.

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction object based on the tendency of a plurality of factors including the number of searches related to the transaction object.

As described above, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction object based on the tendency of a plurality of factors including the number of searches related to the transaction object.

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction object based on the tendency of a plurality of elements including internal factors related to the transaction object.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including internal factors related to the transaction target.

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction target based on the tendency of a plurality of elements including incentives targeting the transaction target.

As described above, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including incentives targeting the transaction target. .

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction target based on the tendency of a plurality of elements including coupons targeting the transaction target.

As described above, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction target based on the tendency of a plurality of elements including coupons targeting the transaction target. .

In addition, in the information processing apparatus 100 according to the embodiment, the estimation unit 134 estimates the target transaction object based on the tendency of a plurality of factors including price reduction related to the transaction object.

In this way, the information processing apparatus 100 according to the embodiment can appropriately estimate the reason by estimating the target transaction object based on the tendency of a plurality of elements including the price reduction related to the transaction object.

In addition, in the information processing apparatus 100 according to the embodiment, the providing unit 136 provides content indicating the reason for the target transaction subject to be traded in electronic commerce.

As described above, the information processing apparatus 100 according to the embodiment can provide content indicating the reason for ranking by providing content indicating the reason for the target transaction subject to be traded in electronic commerce.

As described above, some of the embodiments of the present application have been described in detail based on the drawings. It is possible to carry out the invention in other forms with modifications.

N network 1 information processing system 10 terminal device 20 external device 100 information processing device 110 communication unit 120 storage unit 121 user information storage unit 122 transaction target information storage unit 123 content storage unit 124 ranking information storage unit 130 control unit 131 acquisition unit 132 reception unit 133 determination unit 134 estimation unit 135 generation unit 136 provision unit

Claims (18)

an estimating unit for estimating the reason for the order of the target transaction object, which is the transaction object to be displayed as a ranking, based on the transaction object information about the transaction object;
a provision unit for providing content including a ranking character string indicating the ranking and indicating the reason for the target transaction target estimated by the estimation unit;
with
The estimation unit
Based on a plurality of partial scores corresponding to each of a plurality of elements included in the transaction object information, the element with the largest partial score among the plurality of elements is the reason for the ranking of the target transaction object. An information processing device characterized by estimating that The providing unit
2. The information processing apparatus according to claim 1, wherein said content including said ranking is transmitted to a terminal device used by a user. The providing unit
3. The information processing apparatus according to claim 2, wherein said content in which said reason is arranged near information indicating said target transaction object in said ranking is transmitted. The estimation unit
4. The information processing apparatus according to any one of claims 1 to 3, wherein said reason is estimated based on an element having a high degree of influence among said plurality of elements. The estimation unit
The information processing apparatus according to any one of claims 1 to 4 , wherein the reason for the target transaction object is estimated based on trends of the plurality of elements including the number of orders for the transaction object. The estimation unit
The information according to any one of claims 1 to 5 , wherein the reason for the target transaction object is estimated based on the tendency of the plurality of elements including the number of views of the information indicating the transaction object. processing equipment. The estimation unit
The information processing apparatus according to any one of claims 1 to 6 , wherein the reason for the target transaction object is estimated based on trends of the plurality of elements including the number of reviews for the transaction object. The estimation unit
The information processing apparatus according to any one of claims 1 to 7 , wherein the reason for the target transaction object is estimated based on trends of the plurality of elements including the number of reservations for the transaction object. The estimation unit
The information processing apparatus according to any one of claims 1 to 8 , wherein the reason for the target transaction object is estimated based on trends of the plurality of elements including external factors related to the transaction object. . The estimation unit
10. The information processing apparatus according to claim 9 , wherein the reason for the target transaction target is estimated based on trends of the plurality of elements including postings related to the transaction target on an SNS (Social Networking Service). The estimation unit
The information processing apparatus according to claim 9 or 10 , wherein the reason for the target transaction object is estimated based on trends of the plurality of elements including the number of searches related to the transaction object. The estimation unit
The information processing apparatus according to any one of claims 1 to 11 , wherein the reason for the target transaction object is estimated based on trends of the plurality of elements including internal factors related to the transaction object. . The estimation unit
13. The information processing apparatus according to claim 12 , wherein the reason for the target transaction target is estimated based on the tendency of the plurality of factors including incentives targeting the target transaction target. The estimation unit
The information processing apparatus according to claim 12 or 13 , wherein the reason for the target transaction object is estimated based on the tendency of the plurality of elements including coupons targeting the transaction object. The estimation unit
15. The information processing apparatus according to any one of claims 12 to 14 , wherein said reason for said target transaction object is estimated based on trends of said plurality of elements including price reductions relating to said transaction object. The providing unit
16. The information processing apparatus according to any one of claims 1 to 15 , wherein the content indicating the reason for the target transaction subject to be traded in electronic commerce is provided. A computer-executed information processing method comprising:
an estimating step of estimating the reason for the order of the target transaction object, which is the transaction object to be displayed as a ranking, based on the transaction object information about the transaction object;
a providing step of providing content including a ranking character string indicating the ranking and indicating the reason for the target transaction target estimated by the estimating step;
including
The estimation step includes
Based on a plurality of partial scores corresponding to each of a plurality of elements included in the transaction object information, the element with the largest partial score among the plurality of elements is the reason for the ranking of the target transaction object. presumed to be
An information processing method characterized by: an estimation procedure for estimating the reason for the order of the target transaction object, which is the transaction object to be displayed as a ranking, based on the transaction object information about the transaction object;
a provision step of providing content including a ranking character string indicating the ranking and indicating the reason for the target transaction target estimated by the estimation step;
on the computer, and
The estimation procedure includes:
Based on a plurality of partial scores corresponding to each of a plurality of elements included in the transaction object information, the element with the largest partial score among the plurality of elements is the reason for the ranking of the target transaction object. An information processing program characterized by estimating that

Images