JP7167370B1 - Information processing device, information processing method, and information processing program - Google Patents

Abstract

An object of the present invention is to narrow down transaction targets corresponding to a search query. An information processing apparatus according to the present application includes an acquisition unit and a calculation unit. The acquisition unit acquires information on a user's action history with respect to transaction target information provided in response to a search query. The calculation unit calculates a spec score, which is a score for the spec of the transaction target, for each piece of information indicated by the search query, based on the action history information acquired by the acquisition unit. [Selection drawing] Fig. 1

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, there is known a technique for providing users with ranking information in which transaction targets such as product information corresponding to a search query are used as ranking factors (see, for example, Patent Document 1).

Japanese Patent No. 6776072

However, the above conventional techniques have room for improvement. For example, in the conventional technology described above, ranking information is provided to the user using the transaction target corresponding to the search query as a ranking factor. may not be available. Therefore, it is desirable to further narrow down the transaction targets that are the transaction targets corresponding to the search query and used as ranking factors, and there is room for improvement.

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 narrowing down transaction targets corresponding to a search query.

An information processing apparatus according to the present application includes an acquisition unit and a calculation unit. The acquisition unit acquires information on a user's action history with respect to transaction target information provided in response to a search query. The calculation unit calculates a spec score, which is a score for the spec of the transaction target, for each piece of information indicated by the search query, based on the action history information acquired by the acquisition unit.

According to one aspect of the embodiment, there is an effect that the transaction target corresponding to the search query can be narrowed down.

FIG. 1 is a diagram for explaining an information processing method performed by an information processing apparatus according to an embodiment. FIG. 2 is a diagram illustrating an example of content provided to a user from the information processing apparatus according to the embodiment; FIG. 3 is a diagram showing an example of ranking of transaction targets from multiple perspectives in the information processing apparatus according to the embodiment. FIG. 4 is a diagram illustrating an example of search results and ranking information provided by the information processing apparatus according to the embodiment. FIG. 5 is a diagram illustrating another example of ranking information provided by the information processing device according to the embodiment. FIG. 6 is a diagram illustrating a configuration example of an information processing apparatus according to the embodiment; 7 is a diagram illustrating an example of a user information table stored in a user information storage unit according to the embodiment; FIG. FIG. 8 is a diagram showing an example of a transaction target information table stored in a transaction target information storage unit according to the embodiment. 9 is a diagram illustrating an example of a content table stored in a content storage unit according to the embodiment; FIG. 10 is a diagram illustrating an example of perspective determination dictionary information stored in a ranking information storage unit according to the embodiment; FIG. FIG. 11 is a diagram showing another example of perspective determination dictionary information stored in the ranking information storage unit according to the embodiment. FIG. 12 is a diagram illustrating an example of a spec list provided to a user from the information processing apparatus according to the embodiment; 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 hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus according to the embodiment.

Hereinafter, modes for implementing an information processing apparatus, an information processing method, and an information processing program (hereinafter referred to as "embodiments") according to the present application will be described in detail 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.

[1. Example of information processing]
[1.1. Overview of information processing]
First, an information processing method performed by the information processing apparatus according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram for explaining an information processing method performed by an information processing apparatus according to an embodiment.

The information processing device 1 executes information processing related to transaction objects traded in electronic commerce (EC) services. 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. FIG. 1 shows an example of information processing for a transaction target traded on an electronic shopping mall.

FIG. 1 illustrates an example in which the information processing device 1 functions as a search device that provides search results to a terminal device 2 used by a user U who inputs a search query. A search query is entered by entering a search keyword, and a search query including the search keyword is transmitted from the terminal device 2 to the information processing device 1 . Note that the input of the search query is not limited to input using the keyboard displayed on the terminal device 2 , and may be input by designating keyword candidates displayed on the terminal device 2 . In the following description, the search query includes a search keyword, but may include a search image instead of or in addition to the search keyword. Although only one terminal device 2 is illustrated in FIG. 1 , each of the plurality of users U uses the corresponding terminal device 2 among the plurality of terminal devices 2 . The information processing device 1 provides each of the plurality of terminal devices 2 with content including search results corresponding to search queries transmitted from each of the plurality of terminal devices 2 .

The information processing device 1 has a function as a search engine that executes a search process for, for example, a transaction target traded on an electronic shopping mall. For example, the information processing device 1 has a database (also referred to as a "transaction target database") in which transaction targets to be searched using a search query are indexed and stored, and the information in the transaction target database is Execute search processing as a target. For example, the information of the transaction target database is stored in the storage unit 11 (see FIG. 6).

As described above, FIG. 1 illustrates a case in which the information processing device 1 also functions as a search device, that is, the information processing device 1 and the search device are integrated. There may be. In this case, the information processing system 100 (see FIG. 6) includes a search device that performs search processing for a search query and provides a search service that provides search results. For example, the information processing device 1 transmits a search query including a search keyword input by the user U to the search device, receives search results from the search device, and sends content generated using the search results to the user U. Send to the terminal device 2 .

For example, when the external device 3 is a search device, the information processing device 1 transmits a search query including a search keyword input by the user U to the external device 3, receives search results from the external device 3, and performs the search. The content generated using the result is transmitted to the terminal device 2 used by the user U. The above system configuration is merely an example, and the information processing system 100 may have any device configuration as long as desired information can be provided to the user U who has entered a search keyword.

First, the information processing device 1 acquires user information, which is information about the user U, from the external device 3 (step S1). The external device 3 transmits user information to the information processing device 1 . For example, the external device 3 transmits user information including user U attribute information to the information processing device 1 . The attribute information includes, for example, 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 U. FIG. For example, the user information may include a history of actions of the user U, such as actions on the Internet. For example, the user information may include an action history of the user U, such as a viewing history of information about a transaction target in an electronic commercial transaction service such as an electronic shopping mall, and a purchase history.

Further, the information processing device 1 acquires information (also referred to as "transaction target information") regarding the transaction target from the external device 3 (step S2). For example, the information processing device 1 acquires, from the external device 3, transaction target information of a transaction target to be traded on the electronic shopping mall. For example, the information processing device 1 acquires, from the external device 3, transaction target information of a transaction target that is being sold (exhibited) on the electronic shopping mall. For example, the information processing device 1 acquires the transaction target information of the transaction target from the external device 3 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, sale price, image of the transaction target, category, title, description, payment method, sales period, 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 target information includes the period elapsed from the date and time when the transaction target was sold, the number of views of information indicating the transaction target (number of PV (page views)), the number of reviews of the transaction target, the evaluation of the transaction target, 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, the transaction target information may include posted information posted by the user U on the SNS. For example, the posted information includes text information posted by the user U on Twitter (registered trademark), Facebook (registered trademark), Instagram (registered trademark), YouTube (registered trademark), etc., or image information such as images and videos. 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 U 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 1 performs the acquisition process in steps S1 and S2. information may be obtained at the same time.

The information processing device 1 also receives a search query input by the user U from the terminal device 2 (step S3). For example, when the user U inputs a search keyword, the terminal device 2 transmits a search query including the search keyword input by the user U to the information processing device 1 . Thereby, the information processing device 1 acquires the search query input by the user U. FIG.

For example, when the user U inputs "sneakers" as a search keyword into the terminal device 2, the terminal device 2 transmits a search query including the search keyword "sneakers" input by the user U to the information processing device 1. . For example, the user U enters "sneakers" as a search keyword in an input field such as a search box BX1 in FIG. 2, which will be described later.

After receiving the search query, the information processing apparatus 1 generates search results corresponding to the search query by performing search processing using the search query as processing for providing information to the user U (step S4). For example, when the search keyword included in the search query is "sneakers," the information processing apparatus 1 performs search processing using "sneakers" to generate search results corresponding to "sneakers." Hereinafter, a search query including "sneakers" as a search keyword may be referred to as a search query "sneakers."

The information processing device 1 extracts transaction target information corresponding to the search query "sneakers" using information in the transaction target database. For example, the information processing device 1 performs search processing using the search query "sneakers" on the transaction target database, and extracts transaction target information corresponding to the search query "sneakers". For example, the information processing device 1 extracts transaction target information including information such as a character string corresponding to the search query "sneakers" in the transaction target information.

It should be noted that the extraction of information corresponding to the search query is performed using a conventional technique, and any processing may be used as long as the transaction target can be specified, and detailed description thereof will be omitted. When a device (search device) other than the information processing device 1 performs the search process, the information processing device 1 transmits a search query to the search device and receives search results of the search query from the search device. The information processing device 1 generates search results for the search query using the transaction target information extracted as information corresponding to the search query. For example, the information processing device 1 generates list information of transaction targets of the extracted transaction target information as a search result for the search query.

Next, the information processing device 1 generates a plurality of ranking information according to the search query received in step S3 (step S6). For example, based on the search query received in step S3, the information processing device 1 determines the type and order of the plurality of ranking information to be provided to the user U, and based on the determined type and order of the ranking information, A plurality of ranking information to be provided to the user U is generated. The type of ranking information includes, for example, a ranking cutoff and a display format of the ranking information.

The point of view of the ranking is the point of view (point of view) for the transaction target. For example, the perspective (point of view) for the transaction target includes various types of transaction targets, such as the category, brand, usage scene, specifications (e.g., specifications, functions, etc. of the transaction target), and types of specifications to which the transaction target applies. Includes cuts (perspectives). In addition, when the trading object is traded as a set, the specifications of the trading object also include the number of the trading object.

The display format of the ranking information is the arrangement format of the plurality of ranking elements that constitute the ranking information, and includes a list format (an example of the first display format), a grid format (an example of the second display format), and the like. The list format is a display format in which a plurality of ranking elements that make up the ranking information are arranged in a row, and the grid format is a display format in which a plurality of ranking elements are arranged in a matrix of n rows x m columns. . n and m are integers of 2 or more.

The display format of the ranking information may include a display format in which a plurality of ranking elements are arranged in one line instead of or in addition to the second display format. Also, the display format of the ranking information may be divided into a display format including the photograph of the transaction object and a display format not including the photograph of the transaction object.

The information processing device 1 generates a plurality of ranking information based on the determined types of the plurality of ranking information (for example, cuts and display formats; hereinafter sometimes referred to as determination types) and the order of arrangement of the plurality of ranking information. do.

The information processing device 1 extracts or determines transaction objects that are ranking elements from the perspective indicated by the determined type, and performs a process of calculating a score for each extracted or determined transaction object for each determined type. The information processing device 1 uses the calculated score to rank the trading objects for each determination type, and generates ranking information in which a plurality of ranking elements are arranged in a display format indicated by the determination type for each determination type. For example, the information processing device 1 generates ranking information by assigning ranks to ranking elements in descending order of score, and arranging a plurality of ranking elements up to a preset rank from the highest rank.

For example, the information processing device 1 calculates a score of a transaction target extracted or determined as a ranking element based on the transaction target information related to the transaction target for each determination. The information processing apparatus 1 receives transaction target information of a transaction target, and calculates a score of the transaction target using a score function, which is a function that outputs the score of the transaction target. The information processing device 1 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 amount, and the number of views (number of PVs) increase. may

For example, the information processing device 1 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 (hereinafter referred to as "partial score" ) is used to calculate the score of the transaction target. The information processing device 1 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 1 may calculate the average of the partial scores of each of the multiple elements of the transaction target as the score of the transaction target.

In addition, the information processing device 1 calculates the score of the transaction target using aggregated values aggregated for each predetermined period for each of a plurality of elements such as the number of orders of the transaction target, the order amount, and the number of views (number of PV). You may The information processing device 1 may calculate the score of the transaction target using the aggregated value aggregated for each date for each of the multiple elements of the transaction target. In this case, the information processing device 1 calculates the score of the transaction object using the period score obtained by multiplying the weight (coefficient) of each element by the total value of the plurality of elements of the transaction object aggregated for each predetermined period. can be calculated. The information processing device 1 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 calculation time. The information processing apparatus 1 may calculate the score of the transaction target using a value obtained by multiplying the period score of each period by an attenuation coefficient that decreases in value as the period progresses in the past.

Note that the above is only an example, and the information processing device 1 may use any information to calculate the score of the transaction target. The information processing apparatus 1 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 device 1 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.

Here, a case will be described where the determined ranking is based on the specifications of the transaction target. When the determined ranking cutoff is the specification of the transaction target, the information processing device 1 generates ranking information based on the type score and the specification score corresponding to the information indicated by the search query. The type score is a score for a spec type that is the type of spec to be traded, and is calculated for each piece of information indicated by a search query, for example. A spec score is a score for specs of a transaction target, and is calculated for each piece of information indicated by a search query, for example. The information indicated by the search query is the search keyword indicated by the search query.

For example, in the case of the search query “sneakers”, the determined ranking cutoff is the specs of the sneakers. The spec type of the sneaker is, for example, color, cut, and the like. The specs of sneakers whose spec type is color are specific colors such as white, red, blue, and dark blue. The specs of sneakers whose spec type is cut are specific cut types such as low cut, middle cut, and high cut.

The information processing device 1 calculates spec items and spec scores based on the action history information of the user U with respect to the transaction target information, which is the transaction target information provided to the user U from the information processing device 1 in response to the search query. is calculated for each information indicated by the search query.

The transaction target information is, for example, information on a transaction target indicated by search results or information on a transaction target indicated by ranking information, and includes a link to a landing page of the transaction target. When the transaction target information is selected by the user U's click operation, the information processing device 1 provides the user U with information on the landing page of the transaction target indicated by the transaction target information selected by the user U. The landing page is a page (for example, web page) for trading the transaction object, and the user U can trade the transaction object on the landing page.

The action history of the user U with respect to the transaction target information is, for example, at least one of the selection history of the user U with respect to the transaction target information (eg, click history) and the transaction history of the user U with respect to the transaction target (eg, conversion history). On the one hand. For example, the information processing device 1 increases the type score for the spec type included in the transaction target information that is selected more frequently, or increases the type score for the spec type that is included in the transaction target information that is selected more frequently. or In addition, the information processing device 1 increases the specification score for specifications included in transaction target information with a large number of selections, or increases the specification score for specifications included in transaction target information with a large number of transactions.

The information processing apparatus 1 calculates the score of each specification as a specification score, and calculates the score of each specification type as a category score, for example, based on the action history of the user U. For example, in the case of the search query "sneakers", the information processing apparatus 1 calculates the type score of the spec type "color", the type score of the spec type "cut", etc. based on the action history of the user U.

Further, for example, in the case of the search query "sneakers", the information processing apparatus 1 selects color #1, color #2, and color #3 as specs of the spec type "color" based on the action history of the user U. Calculate each spec score. In addition, although the colors of the transaction objects are represented by abstract character strings such as color #1, color #2, and color #3, color #1, color #2, and color #3 are, for example, white, Specific colors such as red and dark blue.

Here, it is assumed that the search query accepted in step S3 is the search query "sneakers", that is, the information indicated by the search query is "sneakers". Also, among the plurality of spec types calculated for the search query "sneakers", the spec type with the highest type score is color, and the spec type with the next highest type score is cut.

In this case, the information processing apparatus 1 determines the spec of the spec type “color” and the spec of the spec type “cut” as a ranking cutoff in the plurality of ranking information to be provided to the user U. FIG. In addition, the information processing device 1 determines the order of arrangement of the plurality of ranking information, the order of the ranking information based on the specification of the specification type "color" and the order of the ranking information based on the specification of the specification type "cut".

Also, the information indicated by the search query is "sneakers", the spec with the highest spec score is the low cut, the spec with the next highest spec score is color #3, and the spec with the next highest spec score is color # 1.

In this case, the information processing apparatus 1 determines the low cut, color #3, and color #1 as ranking cut points in a plurality of ranking information provided to the user U. FIG. In addition, the information processing apparatus 1 arranges the order of the plurality of ranking information as ranking information with low-cut sneakers as a ranking element, ranking information with sneakers of color #3 as a ranking element, and sneakers with color #1 as a ranking element. The order of the ranking information to be displayed is determined.

In addition, the information processing apparatus 1 can determine a spec with the highest spec score for each spec type as a ranking cutoff in a plurality of ranking information provided to the user U. FIG. In this case, the information processing device 1 can determine the order in which the plurality of ranking information items are arranged in descending order of category score.

Further, the information processing apparatus 1 can determine the ranking based on the type score instead of or in addition to the spec score based on the plurality of ranking information to be provided to the user U. For example, the information processing device 1 can determine a plurality of ranking cuts including a cut based on the type score and a cut based on the spec score as the cuts of ranking in the plurality of ranking information provided to the user U. In this case, the information processing apparatus 1 can also determine, for example, the spec of the spec type “color” with the highest spec type score and the low cut with the highest spec score as cut points of a plurality of ranking information to be provided to the user U.

In addition, the information processing device 1 sets the display format of the ranking information in the list format (an example of the first display format), in which the transaction target having the spec with the largest spec score or the spec with the spec score equal to or higher than the threshold is the ranking element, and other , the display format of the ranking information can be changed to a grid format. The information processing apparatus 1 can also increase the number of ranking elements for ranking information of specs with a higher spec score.

Further, the information processing apparatus 1 can arrange the ranking information of the aspects other than the spec type and the specs higher than the spec type or the ranking information of the specs. Ranking information on aspects other than spec types and specs are, for example, ranking information for each category, ranking information for each brand, and the like.

Next, the information processing device 1 generates content to be provided to the user U using the search result corresponding to the search query and a plurality of pieces of ranking information corresponding to the search query (step S6). The information processing device 1 displays a first tab for displaying search results corresponding to the search query and ranking information corresponding to the search query, in addition to search results corresponding to the search query and ranking information corresponding to the search query. and a second tab for displaying the content.

Then, the information processing device 1 transmits the content including the search result corresponding to the search query and the ranking information corresponding to the search query to the terminal device 2 of the user U who entered the search keyword included in the search query ( step S7). When there is a plurality of ranking information corresponding to the search query, the information processing device 1 transmits a part of the plurality of ranking information to the terminal device 2, and then transmits the remaining ranking information according to the display state of the ranking information on the terminal device 2. Although part or all of the information is transmitted to the terminal device 2, it is not limited to such an example. For example, the information processing device 1 can transmit a plurality of pieces of ranking information to the terminal device 2 at once.

An example of content provided to the terminal device 2 will now be described with reference to FIG. FIG. 2 is a diagram showing an example of content provided to the user U from the information processing device 1 according to the embodiment. In FIG. 2, content C provided from information processing device 1 to terminal device 2 and displayed on terminal device 2 includes search box BX1, first tab TB1, second tab TB2, and second tab content C2. . The search box BX1 shown in FIG. 2 shows "sneakers" as a search keyword input by the user U. As shown in FIG. The content C also includes a first tab content C1 (see FIG. 4), which will be described later.

A first tab TB1 shown in FIG. 2 is a GUI (Graphical User Interface) selected to display a first tab content C1 (see FIG. 4) described later on the terminal device 2, and the second tab shown in FIG. TB2 is a GUI selected to cause the terminal device 2 to display the second tab content C2. The first tab content C1 and the second tab content C2 are selectively displayed in the content C display area AR by operating the first tab TB1 or the second tab TB2.

In FIG. 2, when the first tab TB1 is selected by the user U, the first tab content C1 in which the search results of the search query "sneakers" are arranged is displayed in the display area AR. Further, when the user U selects the second tab TB2, the display area AR displays the second tab content C2 in which a plurality of ranking information items of the transaction target corresponding to the search query "sneakers" are arranged. In the example shown in FIG. 2, the ranking information of the trading object corresponding to the search query "sneakers" is ranking information in which the sneakers of color #3 are ranking factors.

FIG. 2 shows a state in which the second tab TB2 is selected, and the terminal device 2 displays the second tab content C2 in which the ranking information of the transaction target corresponding to the search query "sneakers" is arranged in the display area AR. Specifically, in the display area AR of the content C, ranking information in which a plurality of trading objects corresponding to the search query "sneakers" are arranged in descending order of score as ranking elements is displayed as the second tab content C2. be.

In this way, the information processing device 1 switches between the first tab content C1 and the second tab content C2 according to the user U's selection, and displays the content in the display area AR on the terminal device 2 of the user U. offer. As a result, if the user U using the terminal device 2 receiving the provision of the content C wants to simply see the search result, the first tab content C1 is displayed on the terminal device 2 and the ranking information is displayed. causes the terminal device 2 to display the second tab content C2. In the case of the content C displayed by switching the information in this way, the user U using the terminal device 2 switches the display according to the content he/she wants to see, and causes the terminal device 2 to display the content, and confirms the content. can do. Therefore, the information processing device 1 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. 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. Score calculation]
As described above, the information processing device 1 calculates the type score, which is the score of the specification type of the transaction target, and the transaction A spec score, which is a score for the target spec, is calculated. The information processing apparatus 1 calculates the type score of each spec type and the spec score of each spec for each information (search keyword) indicated by a search query.

For example, it is assumed that the search queries accepted by the information processing apparatus 1 include the search query "sneakers", the search query "sneakers brand #1", and the search query "sneakers latest". In this case, for each of "sneakers", "sneakers brand #1", and "sneakers latest", the type score of each spec type and the spec score of each spec are calculated. Here, for convenience, the sneaker brand is represented by an abstract character string such as brand #1.

The specification type is the type of specifications of the transaction target, and is a type preset for each category of the transaction target, but can be added or deleted. For example, when the trading object is sneakers, the spec type includes color, cut, size, shoe material, shoe width, height, detachable type, weight, and, for example, pattern. If the spec type is color, the spec is a specific color such as white, red, blue, dark blue, etc. If the spec type is cut, the spec is a specific cut such as low cut, middle cut, high cut, etc. .

In addition, when the spec type is size, the spec is a specific size such as 26.0 cm, 26.5 cm, 27.0 cm, etc. When the spec type is shoe material, the spec is canvas/cloth, genuine leather. , synthetic leather, suede, nylon and other specific materials. When the spec type is a pattern, the spec is a specific pattern such as solid color, stripe, border, geometric pattern, dot, one-point, or character.

In addition, when the transaction target is a television, for example, the specification type of the transaction target includes screen size, recording function, panel performance, weight, height, depth, installed tuner, and the like. When the spec type of the transaction target is the screen size, the spec is a specific size range such as 20 to 29 inches, 30 to 39 inches, 40 to 49 inches, 50 to 59 inches, and 60 to 69 inches. Also, if the specification type of the transaction target is recording function, the specification is a specific recording function such as built-in HDD, Blu-ray, built-in HDD+Blu-ray, external HDD+Blu-ray.

Here, a method for calculating the type score will be described. The information processing device 1 divides the number of selections by the user U of the transaction target information, which is information on the transaction target having specifications belonging to the specification type, by the number of specification types included in the transaction target information, and obtains a score for each specification type. is performed for each transaction target information. Then, the information processing apparatus 1 calculates a type score for each spec type by summing the calculated individual type scores for each spec type.

For example, it is assumed that the transaction object information selected by the user U is two transaction objects A and B, and these transaction objects A and B are sneakers. Further, assume that the spec types to which the specs included in the information on the transaction target A belong are color, size, and material, and the spec types to which the specs included in the information on the trade target B belong are color and size. It is also assumed that the number of selections by the user U of the information on the transaction target A is 90 times, and the number of selections by the user U of the information on the transaction target B is 40 times.

In this case, in the information of transaction target A, the individual type score for each of the specification types “color”, “size”, and “material” is 30 (=90÷3), and in the information of transaction target B, the specification The individual category score for each of the categories "color" and "size" is 20 (=40/2). Therefore, the type score for each of the spec types “color” and “size” is 50 (=30+20), and the type score for the spec type “material” is 30.

Further, the information processing device 1 can also calculate a type score for each spec type based on the number of transactions of the transaction target by the user U, instead of the number of times the user U selects the transaction target information. For example, the information processing device 1 divides the number of transactions by the user U who is the transaction object having the spec belonging to the spec type by the number of the spec types included in the transaction object information, and divides the individual type score, which is the score for each spec type. is calculated for each transaction target information. Then, the information processing apparatus 1 calculates a type score for each spec type by summing the calculated individual type scores for each spec type.

For example, it is assumed that the transaction objects traded by the user U are two transaction objects A and B, and these transaction objects A and B are sneakers. Further, assume that the spec types to which the specs included in the information on the transaction target A belong are color, size, and material, and the spec types to which the specs included in the information on the trade target B belong are color and size. It is also assumed that the number of transactions by the user U of the information on the transaction target A is five, and the number of transactions by the user U of the information on the transaction target B is two.

In this case, in the information of transaction target A, the individual type score for each of the spec types "color", "size", and "material" is 5/3 (=5÷3), and in the information of transaction target B , the individual type score of each of the spec types “color” and “size” is 1 (=2/2). Therefore, the type score for each of the spec types “color” and “size” is 8/3 (=5/3+1), and the type score for the spec type “material” is 1.

The information processing device 1 can also calculate a type score for each spec type based on the number of times the user U selects the transaction target information and the number of times the user U trades the transaction target. For example, the information processing device 1 weights and adds the type score calculated based on the number of times the user U selects the transaction target information and the type score calculated based on the number of transactions of the transaction target by the user U. , the type score for each spec type can be calculated. In this case, the weight of the category score calculated based on the number of transactions is greater than the weight of the category score calculated based on the number of selections. Then, the information processing apparatus 1 calculates a type score for each spec type by summing the calculated individual type scores for each spec type.

Next, a method for calculating the spec score will be described. First, a method of calculating a spec score for specs included in information of a transaction object that does not have multiple specs as specs of the same spec type will be described. In this case, the spec score calculation method is the same as the type score calculation method.

For example, the information processing device 1 divides the number of selections by the user U of transaction target information, which is transaction target information, by the number of specifications included in the transaction target information to calculate an individual specification score, which is a score for each specification. This process is performed for each transaction target information. Then, the information processing apparatus 1 calculates a spec score for each spec by summing the calculated individual spec scores for each spec.

In addition, the information processing device 1 divides the number of transactions by the user U of the transaction target by the number of specifications included in the transaction target information, which is the information of the transaction target, to calculate an individual spec score, which is a score for each spec. Processing can also be performed for each transaction object information. Then, the information processing apparatus 1 calculates a spec score for each spec by summing the calculated individual spec scores for each spec.

The information processing device 1 can also calculate a spec score for each spec based on the number of times the user U selects the transaction target information and the number of times the user U trades the transaction target. For example, the information processing device 1 weights and adds the spec score calculated based on the number of times the user U selects the transaction target information and the spec score calculated based on the number of transactions of the transaction target by the user U. to calculate the spec score for each spec. In this case, the weight of the spec score calculated based on the number of transactions is greater than the weight of the spec score calculated based on the number of selections.

Next, a method of calculating a spec score for a spec included in information of a transaction object that may have a plurality of specs as specs of the same spec type will be described. In this case, the information processing device 1 calculates the individual spec score by dividing the individual type score by the number of specs included in the same spec type in the transaction target information.

For example, it is assumed that the transaction objects traded by the user U are two transaction objects A and B, and these transaction objects A and B are sneakers. Further, assume that the specs included in the information of transaction target A are color #1, color #2, color #3, and synthetic leather, and the specs included in the information of transaction target B are color #1, synthetic leather. . It is also assumed that the number of selections by the user U of the information on the transaction target A is 50 times, and the number of selections by the user U of the information on the transaction target B is 20 times.

In this case, the information processing device 1 sets the individual specification score of each of the specifications “color #1”, “color #2”, and “color #3” to 25/3 (=50/2/3 ), and the individual spec score of the spec “synthetic leather” is 25 (=50/2). In addition, the information processing device 1 sets the individual spec score of each of the specs “color #1” and “synthetic leather” to 10 (=20/2) for the transaction object B. FIG. Then, the information processing apparatus 1 sets the spec score of the spec “color #1” to 55/3 (=25/3+10), and sets the spec score of each of the specs “color #2” and “color #3” to 25/3. , and the spec score of the spec "synthetic leather" is set to 10.

Note that the information processing device 1 can also correct the spec score and the type score calculated as described above. For example, the information processing device 1 provides the user U with a spec list, which is a list of specs, and provides the user U with information on a plurality of transaction targets belonging to specs selected by the user U from the spec list. In this case, at least one of the spec score and the type score can be corrected based on the spec selection history by the user U. For example, the information processing apparatus 1 corrects the spec score by multiplying the spec score by a coefficient k1 (≧1) according to the number of spec selections by the user U in the spec list. The information processing apparatus 1 can also collect the number of selections of specs in the spec list for each spec type as the number of selections of the spec type, and correct the type score based on the number of times of selection of the spec type.

Further, the information processing apparatus 1 can also use scores obtained by normalizing each of the spec score and the type score calculated as described above as the spec score and the type score.

Further, the information processing apparatus 1 stores the spec score of each spec and the type score of each spec type in association with each piece of information indicated by the search query. Further, the information processing apparatus 1 can also store the intra-type spec score of the spec in association with each piece of information indicated by the search query instead of the spec score. The intra-class spec score of a spec is the score in the spec class to which the spec belongs. For example, the spec type "color" has a type score of 50, the specs "color #1" and "color #2" each have a spec score of 100/3, and the spec "color #3" has a spec score of 50. /3. In this case, the intra-type spec score of each of the specs "color #1" and "color #2" is 2/3, and the intra-type spec score of the spec "color #3" is 1/3.

[1.2.2. Determination of ranking information type and display format]
The information processing device 1 determines the types and order of the plurality of ranking information to be provided to the user U based on the search query. The types of ranking information include, for example, a ranking aspect and a display format of ranking information, but are not limited to such examples.

For example, the information processing device 1 determines the types and order of ranking information based on the spec score of each spec and the type score of each spec type associated with the information indicated by the search query.

For example, the information processing apparatus 1 determines, among a plurality of specs, specs whose spec score satisfies a preset condition as a cut point for ranking. The preset conditions are, for example, the condition that the spec score is a preset number in order from the spec score with the highest spec score, the condition that the spec score is the highest spec score within each spec type, and the like. . Further, the preset condition is, for example, a condition that one or more specs belong to each of a preset number of spec types in order from the spec type with the highest type score among the type scores of each spec type. may

For example, the information processing device 1 determines a preset number of specs in descending order of the spec score with the highest spec score among the spec scores of the specs associated with the information indicated by the search query as cut points in a plurality of ranking information. . In addition, the information processing apparatus 1 determines ranking information for each of the plurality of specified specs in descending order of the spec score.

The information processing apparatus 1 also determines the display format of the ranking information of the spec with the highest spec score to be the list format, and the display format of the other ranking information to be the grid format. When the highest spec score is equal to or greater than a preset threshold value, the information processing apparatus 1 sets the display format of the ranking information of specs with the highest spec score to a list format. The display format of the spec ranking information can also be a grid format.

In addition, the information processing device 1 uses the spec score of each spec associated with the information indicated by the search query to identify the spec with the highest spec score within each spec type, and assigns each of the identified specs to the ranking information. You can decide to cut. In addition, the information processing apparatus 1 determines the order of specification types set in advance as the order of arrangement.

In addition, the information processing apparatus 1 selects one or more spec types belonging to each of a preset number of spec types in order from the spec type with the highest type score among the type scores of the spec types associated with the information indicated by the search query. Specs can also be determined as a cut-off in ranking information. In this case, the information processing apparatus 1 determines, for example, the order of ranking information based on each of the specified specifications in descending order of classification score.

Further, the information processing device 1 determines the display format of the ranking information of the specification with the highest type score to be the list format, and determines the display format of the other ranking information to be the grid format. When the highest category score is equal to or higher than a preset threshold value, the information processing device 1 sets the display format of the ranking information of the specification with the highest category score to a list format. The display format of the spec ranking information can also be a grid format.

Note that the information processing apparatus 1 selects a predetermined number of spec types in order from the spec type with the highest type score among the type scores of the spec types associated with the information indicated by the search query, in order from the plurality of ranking information. can also be determined to In this case, the information processing apparatus 1 determines the ranking information for each of the specified plurality of spec types in descending order of the type score.

When the information processing apparatus 1 stores the intra-type spec score in association with each piece of information indicated by the search query instead of the spec score, the spec score is calculated by multiplying the type score and the intra-type spec score. calculate. For example, assume that the spec type "color" has a type score of 50, and the spec type "color #1" has an intra-type spec score of 2/3. In this case, the spec score of the spec “color #1” is 100/3 (=50×2/3).

The information processing device 1 can also determine both the spec type and the spec as cut points in a plurality of ranking information. For example, the information processing device 1 may include a preset number (1 or more) of spec types in order from the spec type with the highest type score, and a preset number (1 or more) in order of the spec type with the highest spec score. number) can be determined as a cut point in a plurality of ranking information.

The information processing device 1 can also determine a category or a brand as an aspect in at least one piece of ranking information among a plurality of pieces of ranking information based on a search query. The information processing device 1 can use a plurality of cuts including a category, a brand, a spec type, and a spec as cuts of ranking in a plurality of pieces of ranking information.

In this case, the information processing apparatus 1 may determine the ranking information of the aspects other than the spec type and specs in a higher order than the ranking information in terms of the spec type or specs, or determine the ranking information in the opposite order. can be done. Ranking information on aspects other than spec types and specs are, for example, ranking information for each category, ranking information for each brand, and the like.

When categories are classified in a tree-like hierarchical structure, for example, if the category specified by the search query is not the lowest-level category, the ranking information of the category specified by the search query is the category below the specific category. This is ranking information based on categories. Also, the brand ranking information is ranking information from the perspective of the brand to be traded included in the category specified by the search query.

Note that the information processing apparatus 1 can also exclude specs belonging to spec types in which a plurality of specs can be set for the same transaction object from ranking cuts. For specs that belong to a spec type that allows multiple specs to be set for the same transaction target, in the calculation method described above, if multiple specs are included for the same transaction target, the individual spec score will be the spec Proportional according to the number. Therefore, specs that belong to a spec type that allows multiple specs to be set for the same transaction target have a spec score accuracy lower than specs that belong to a spec type that does not allow multiple specs to be set for the same trade target. may be low. In the information processing device 1, by excluding spec types for which a plurality of specs can be set for the same transaction object from the ranking cutoff, specifications of spec types whose spec score accuracy may be low are excluded from the ranking. Can be excluded from cuts.

[1.2.3. Generation of ranking information in the determined cut]
The information processing device 1 ranks the plurality of trading objects according to each of the plurality of different perspectives determined as described above, and generates a plurality of ranking information. FIG. 3 is a diagram showing an example of ranking of transaction targets from multiple perspectives in the information processing apparatus 1 according to the embodiment. In addition, in FIG. 3, the state divided|segmented for every cut is shown for description.

In FIG. 3, abstract character strings such as cut #1, cut #2, . . . are used. This information indicates a specific cut, such as spec "white" and spec "low cut".

For example, the information processing device 1 selects a transaction target corresponding to each of cut #1, cut #2, . determine (identify) For example, the information processing device 1 determines a transaction target corresponding to each of cut #1, cut #2, .

The information processing device 1 ranks the transaction objects corresponding to the cut #1 as the ranking elements of the cut #1, thereby generating the ranking of the cut #1. For example, the information processing device 1 calculates a score for a transaction object corresponding to cut #1, which is a ranking factor, 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 device 1 generates the ranking information of the cut #1 by assigning a higher ranking in descending order of the score.

The list information TA1 shown in FIG. 3 is information 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 trading object with the rank “1st” is the trading object with the trading object ID “M34” and the score is “0.94”. The transaction object with the rank “2nd” is the transaction object with the transaction object ID “M7” and the score is “0.89”. The transaction object with the rank “3rd” is the transaction object with the transaction object ID “M1” and the score is “0.85”. The information processing device 1 generates the ranking information of the cut #1 using the information shown in the list information TA1.

Similarly, the information processing device 1 ranks the transaction objects corresponding to the cut #2 as the ranking elements of the cut #2, thereby generating the ranking of the cut #2. For example, the information processing device 1 calculates a score for a transaction object corresponding to cut #2, which is a ranking factor, and generates ranking information for cut #2 using the calculated score.

The list information TA2 shown in FIG. 3 is information 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 trading object with the rank “1st” is the trading object with the trading object ID “M162” and the score is “0.84”. The transaction object with the rank “2nd” is the transaction object with the transaction object ID “M78” and the score is “0.74”. The transaction object with the rank “3rd” is the transaction object with the transaction object ID “M18” and the score is “0.73”. The information processing device 1 generates the ranking information of the cut #2 using the information shown in the list information TA2.

When there is an aspect other than the aspects #1 and #2, the information processing device 1 generates ranking information for the aspects other than the aspects #1 and #2 by performing the same processing.

[1.2.4. Example of content including search results and multiple ranking information]
Next, an example of search results (first tab content) and ranking information (second tab content) included in content C provided from the information processing device 1 to the terminal device 2 will be described with reference to FIG. FIG. 4 is a diagram showing an example of search results and ranking information provided by the information processing device 1 according to the embodiment.

FIG. 4 shows a first tab content C1 and a second tab content C2 included in content C generated by the information processing device 1 when the search query "sneakers" is transmitted from the terminal device 2 to the information processing device 1. ing. The user U can display the first tab content C1 in the display area AR by selecting the first tab TB1 (see FIG. 2), and by selecting the second tab TB2 (see FIG. 2) , the second tab content C2 can be displayed in the display area AR. Either the information processing device 1 or the terminal device 2 may switch between the first tab content C1 and the second tab content C2.

In the second tab content C2 shown in FIG. 4, ranking information based on the spec "white" as the ranking by color, ranking information based on the spec "low cut" as the ranking by cut, and the like are arranged in order. Each of the ranking information shown in FIG. 4 shows the top six trading objects, and if the user U wants to know the ranking of the trading objects ranked seventh and below, the character string " Select "See 7th place and below". As a result, the second tab content C2 including the ranking information including the ranking of the transaction objects ranked 7th or lower is transmitted from the information processing device 1 to the terminal device 2, and the terminal device 2 ranks the transaction objects ranked 7th or lower. The second tab content C2 containing ranking information is displayed.

In addition, if the user U wants to know the ranking information for the specs other than the "white" among the specs belonging to the spec type "color", the character string "more ranking by color" included in the second tab content C2. Select "View". As a result, the information processing device 1 transmits to the terminal device 2 the second tab content C2 including a plurality of ranking information based on specs other than "white" among the specs belonging to the spec type "color". The terminal device 2 receives the second tab content C2 transmitted from the information processing device 1, and receives the second tab content C2, which includes a plurality of ranking information based on specs other than "white" among the specs belonging to the spec type "color". 2 tab content C2 is displayed.

In addition, when the user U wants to know the ranking information from the perspective of the specs other than the "low cut" among the specs belonging to the spec type "cut", the character string "more cut ranking" included in the second tab content C2. Select "View". As a result, the second tab content C2 including a plurality of ranking information based on specs other than "low cut" among the specs belonging to the spec type "cut" is transmitted from the information processing device 1 to the terminal device 2. FIG. The terminal device 2 receives the second tab content C2 transmitted from the information processing device 1, and includes a plurality of ranking information based on specs other than "low cut" among the specs belonging to the spec type "cut". 2 tab content C2 is displayed.

FIG. 5 is a diagram showing another example of ranking information provided by the information processing device 1 according to the embodiment. In the example shown in FIG. 4, the ranking information based on the specification "white" is displayed in a grid format and the trading targets are ranked up to the 6th place, but in the example shown in FIG. It differs from the example shown in FIG. 4 in that it ranks up to 20th place in the format.

Compared to the grid format, the list format adds more information about the ranking target, the amount of information is large, and the number of ranking elements included is also large. For example, compared to the grid format, the list format includes brand names, product names, colors, materials, and other information (e.g., user evaluation values, user evaluation numbers, etc.), and has a large amount of information. . Therefore, the user U can more clearly grasp what the ranking elements are based on the ranking element information included in the ranking information.

[1.3. summary〕
Through the various types of processing described above, the information processing apparatus 1 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 tabs related to ranking. Therefore, the information processing device 1 can reduce the possibility that the user U who cannot select the transaction target by himself/herself leaves. In addition, the information processing apparatus 1 can promote the migration of the user U (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 the search keyword input by the user U, the user U has little prior knowledge, and is at a loss as to what to buy. In this case, for example, the information processing device 1 provides rankings for each aspect related to categories, specifications, and the like. This makes it easy for the user U to grasp the outline of the transaction target even with a search query with a broad intention, deepen the intention, and naturally narrow down the options.

In addition, the information processing apparatus 1 can facilitate the user U 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 1 can provide the user U with content organized according to specifications, thereby making it easier for the user U to narrow down options based on trends, popularity, and the like.

Further, the information processing device 1 calculates the spec score, which is the score for the spec of the transaction target, based on the information of the action history of the user U with respect to the information of the transaction target provided in response to the search query. Calculated for each As a result, the information processing device 1 can narrow down the transaction targets corresponding to the search query by using the specifications of the transaction targets.

Hereinafter, the configuration of the information processing system 100 including the information processing device 1, the terminal device 2, and the external device 3 that perform such processing will be described in detail.

[2. Configuration of Information Processing System 100]
As shown in FIG. 6 , the information processing system 100 includes an information processing device 1 , a terminal device 2 and an external device 3 . The information processing device 1, the terminal device 2, and the external device 3 are connected via a network N so as to be communicable by wire or wirelessly. Although only one terminal device 2 is illustrated in FIG. 6 , each of the plurality of users U uses the corresponding terminal device 2 among the plurality of terminal devices 2 . Further, the information processing system 100 shown in FIG. 6 may include a plurality of information processing apparatuses 1 and a plurality of external apparatuses 3 .

The terminal device 2 according to the embodiment is an information processing device used by a user U who accesses content such as web pages displayed on a browser and content for applications. For example, the terminal device 2 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 2 is not limited to the above example, and may be, for example, a smart watch or a wearable device.

The external device 3 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 3 provides user information as various information. As another example, the external device 3 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, or a financial product providing site. Provide information about the transaction object in such as.

The information processing device 1 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 1 is communicably connected to various other devices via a network N. FIG.

[3. Configuration of Information Processing Device 1]
An example of the functional configuration of the information processing apparatus 1 will be described below. FIG. 6 is a diagram showing a configuration example of the information processing device 1 according to the embodiment. As shown in FIG. 6 , the information processing device 1 has a communication section 10 , a storage section 11 and a processing section 12 .

[3.1. Communication unit 10]
The communication unit 10 is implemented by, for example, a NIC (Network Interface Card). The communication unit 10 is connected to the network N by wire or wirelessly, and transmits and receives information to and from other various devices. For example, the communication unit 10 transmits and receives information via the network N to and from each of the terminal device 2 and the external device 3 .

[3.2. Storage unit 11]
The storage unit 11 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 11 also has a user information storage unit 20 , a transaction target information storage unit 21 , a content storage unit 22 , and a ranking information storage unit 23 .

[3.2.1. User information storage unit 20]
The user information storage unit 20 stores various user information regarding the user U. FIG. FIG. 7 is a diagram showing an example of a user information table stored in the user information storage unit 20 according to the embodiment. In the example shown in FIG. 7, the user information table stored in the user information storage unit 20 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 the user U. The "attribute information" is attribute information about the attributes of the user U associated with the "user ID". For example, the attribute information includes user U's age, sex, phone number, address, and the like. 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 U associated with the “user ID”. For example, the purchase history includes information on the transaction object purchased by the user U, the type of the transaction object, the number of times the transaction object was purchased, the date and time when the transaction object was purchased, and the like. For example, the "purchase history" is the transaction target indicated by the transaction target information included in the content C provided to the user U in response to the search query sent to the information processing device 1 by the user U using the terminal device 2. It is the transaction history of the user U of , including information (search keywords) indicated by the search query and the transaction history associated with the transaction date and time. Such transaction history (purchase history) may be stored in the transaction target information storage unit 21 instead of the user information storage unit 20 .

The “browsing history” is a history of browsing of content by the user U associated with the “user ID”. For example, the “browsing history” may be a history of content displayed on the user U's terminal device 2 . For example, the viewing history includes information about content viewed (displayed) by the user U, the type of content, the number of times the content was displayed, and information about the date and time the content was displayed. For example, the “browsing history” is the user U's view of the transaction target information included in the content C provided to the user U in response to the search query sent to the information processing device 1 by the user U using the terminal device 2. The selection history includes information (search keywords) indicated by the search query and the selection history associated with the search date and time. Such selection history (browsing history) may be stored in the transaction object information storage unit 21 instead of the user information storage unit 20 .

For example, in FIG. 7, "U1" identified by the user ID has attribute information "CH1", purchase history "PH1", and display history "WA1". In the example shown in FIG. 7, 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 including

It should be noted that the user information storage unit 20 may store various types of information, not limited to the above, depending on the purpose. The user information storage unit 20 may store, for each user, information indicating the number of times the information has been displayed for each transaction object, for example, the number of times the user U has viewed the information.

[3.2.2. Transaction target information storage unit 21]
The transaction target information storage unit 21 stores various transaction target information related to the transaction target. FIG. 8 is a diagram showing an example of a transaction target information table stored in the transaction target information storage unit 21 according to the embodiment. In the example shown in FIG. 8, the transaction target information table stored in the transaction target information storage unit 21 includes "transaction target ID", "transaction target", "transaction target information", "category", and "product specific information". including items such as In FIG. 8, 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 object information storage unit 21 stores information indicating the cut to which each transaction object corresponds in addition to the category. For example, the transaction target information storage unit 21 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. For example, when categories are defined in a hierarchical structure (for example, a tree-like hierarchical structure), the "category" is information on the lowest level category to which the transaction target applies, or information from the highest level category to the lowest level category to which the transaction target Contains information for each category up to the category. 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. 8, "M1" identified by the trading object ID has trading object "MA1". In the example shown in FIG. 8, the transaction target is represented by an abstract code such as "MA1", but the transaction target is a specific character string (such as a product name) indicating the product sold by each seller. ).

In FIG. 8, "M1" identified by the transaction object ID has transaction object information "MD1". In the example shown in FIG. 8, the transaction object information is represented by an abstract code such as "MD1", but the transaction object information may be in a file format or the like containing various information on the transaction object.

Also, in FIG. 8, "M1" identified by the transaction object ID has a category of "CT1". In the example shown in FIG. 8, 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. 8, "M1" identified by the transaction object ID has "PD1" as the product identification information. In the example shown in FIG. 8, 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 target when there is no product corresponding to the transaction target (for example, a flag indicating that there is no corresponding product).

Note that the transaction target information storage unit 21 may store various types of information, not limited to the above, depending on the purpose. For example, the transaction target information storage unit 21 may describe information such as the score and display count corresponding to each transaction target.

[3.2.3. Content storage unit 22]
The content storage unit 22 stores information about content. FIG. 9 is a diagram showing an example of a content table stored in the content storage unit 22 according to the embodiment. In the example shown in FIG. 9, the content table stored in the content storage unit 22 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 introduction site, a web blog site, an SNS site, and the like.

For example, in FIG. 9, "C1" identified by the content ID has content "CO1". In the example shown in FIG. 9, the content and the like are represented by abstract codes such as "CO1", but the content and the like are represented by specific numerical values, specific character strings, and files containing various information. It may be a format or the like.

Note that the content storage unit 22 may store various types of information, not limited to the above, depending on the purpose.

[3.2.4. Ranking information storage unit 23]
The ranking information storage unit 23 stores various kinds of information used to generate rankings. For example, the ranking information storage unit 23 stores perspective judgment dictionary information for determining ranking perspectives and the order of ranking information, ranking reference information indicating ranking criteria (ranking criteria) for transaction targets, and transaction Stores score calculation information and the like used to calculate various scores of a target.

The ranking reference information is, for example, information indicating a ranking reference for ranking in order from the highest score. The score calculation information is, for example, information such as a score function used to calculate various scores of transaction targets.

The perspective determination dictionary information is information in which spec types, specs, type scores, spec scores, and the like are associated with each piece of information indicated by a search query. FIG. 10 is a diagram showing an example of perspective determination dictionary information stored in the ranking information storage unit 23 according to the embodiment. In the example shown in FIG. 10, the perspective determination dictionary information stored in the ranking information storage unit 23 includes "query ID", "query content", "spec type", "spec", "type score", "spec Includes items such as "score".

"Query ID" is a unique identifier for each piece of information indicated by a search query. “Query content” is information indicated by a search query, and may be referred to as “query content” below. The "spec type" is information indicating the spec type of the transaction target. "Spec" is information indicating the specifications of the transaction target. The “type score” is information indicating the type score, and the “spec score” is information indicating the spec score.

For example, in FIG. 10, the query content of the query ID "Q1" is "QK1". In the example shown in FIG. 10, the query content is represented by an abstract code such as "QK1", but the query content is a character string included as a search keyword in the search query. Also, when a search query includes multiple character strings as search keywords, the query content is a plurality of character strings. For example, when the search keyword is "sneakers ladies", the query content is "sneakers ladies".

In the example shown in FIG. 10, the spec type is represented by an abstract code such as "SK1", but when the traded object is sneakers, for example, the spec type indicates the spec type such as color, cut, size, etc. string information. In addition, in the example shown in FIG. 10, specs are represented by abstract codes such as "SK1#1" and "SK1#2". It is information of a specific character string indicating the spec.

The perspective determination dictionary information is not limited to the example shown in FIG. FIG. 11 is a diagram showing another example of perspective determination dictionary information stored in the ranking information storage unit 23 according to the embodiment. The perspective determination dictionary information shown in FIG. 11 is different from the perspective determination dictionary information shown in FIG. 10 in that it includes "intra-type spec score" instead of "spec score". The result of multiplying the type score by the intra-type spec score is the spec score, and the result of dividing the spec score by the type score is the intra-type spec score.

Note that the ranking information storage unit 23 may store various types of information, not limited to the above, depending on the purpose.

[3.3. processing unit 12]
The processing unit 12 is a controller, and for example, various programs (information processing An example of a program) is implemented by executing the RAM as a work area. Also, the processing unit 12 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. 6, the processing unit 12 includes an acquisition unit 30, a calculation unit 31, a reception unit 32, a generation unit 33, and a provision unit 34, and functions and actions of information processing described below. realize or perform Note that the internal configuration of the processing unit 12 is not limited to the configuration shown in FIG. 6, and may be another configuration as long as it performs information processing to be described later.

[3.3.1. Acquisition unit 30]
The acquisition unit 30 acquires various types of information. The acquisition unit 30 acquires various types of information from the storage unit 11 . The acquisition unit 30 acquires various types of information from the user information storage unit 20, the transaction target information storage unit 21, the content storage unit 22, the ranking information storage unit 23, and the like.

The acquisition unit 30 receives various types of information from an external information processing device via the communication unit 10 . The acquisition unit 30 receives various information from the terminal device 2 or the external device 3 . For example, the acquisition unit 30 acquires user information about the user U from the external device 3 . In FIG. 1, the acquisition unit 30 acquires user information such as attribute information of the user U, purchase history on Internet shopping, electronic shopping malls, auction sites, flea market sites, etc., display history of content, etc. Get from The acquisition unit 30 then stores the user information in the user information storage unit 20 . For example, the acquisition unit 30 acquires user information from the external device 3 and updates the user information stored in the user information storage unit 20 every predetermined period. The acquisition unit 30 also acquires user information stored in the user information storage unit 20 . For example, the acquisition unit 30 acquires from the user information storage unit 20 information on the user U's action history (for example, the above-described selection history and purchase history) with respect to the transaction target information provided in response to the search query. . Hereinafter, the action history of the user U with respect to the transaction target information provided in response to the search query may be simply referred to as the action history.

Also, the acquisition unit 30 acquires information about the transaction target from the external device 3 . For example, the acquisition unit 30 acquires from the external device 3 information about a transaction target traded at an auction site or a flea market site. Then, the acquisition unit 30 stores the information about the transaction object in the transaction object information storage unit 21 . For example, the acquisition unit 30 acquires information on the transaction object from the external device 3 and updates the information on the transaction object stored in the transaction object information storage unit 21 every predetermined period.

The acquisition unit 30 acquires transaction target information regarding a transaction target. The acquisition unit 30 acquires transaction target information including the sales history of the transaction target. The acquisition unit 30 acquires transaction target information including the number of orders for the transaction target. The acquisition unit 30 acquires transaction object information including a period that has passed since the date and time when the transaction object was sold. The acquisition unit 30 acquires transaction target information including the number of sales of the transaction target. The acquisition unit 30 acquires transaction target information including the number of times information indicating the transaction target has been browsed.

The acquisition unit 30 acquires transaction target information including the number of reviews for the transaction target. The acquisition unit 30 acquires transaction target information including an evaluation of the transaction target. The acquisition unit 30 acquires transaction target information including external factors related to the transaction target. The acquisition unit 30 acquires transaction target information including posts about transaction targets on the SNS. The acquisition unit 30 acquires transaction target information including the number of searches related to the transaction target. The acquisition unit 30 acquires transaction target information including internal factors related to the transaction target. The acquisition unit 30 acquires transaction target information including an incentive for the transaction target. The acquisition unit 30 acquires transaction target information including coupons for transaction targets. The acquisition unit 30 acquires transaction target information including price reductions related to transaction targets.

The acquisition unit 30 acquires element information regarding a plurality of elements included in transaction target information. The acquisition unit 30 acquires element information indicating tendencies of a plurality of elements included in transaction target information. Acquisition unit 30 acquires a score corresponding to each of the plurality of elements.

The acquisition unit 30 acquires element information indicating trends of a plurality of elements including the number of orders to be traded. The acquisition unit 30 acquires element information indicating the tendency of a plurality of elements including the number of views of information indicating a transaction target. The acquisition unit 30 acquires element information indicating trends of a plurality of elements including the number of reviews for the transaction target. The acquisition unit 30 acquires element information indicating trends of a plurality of elements including the number of reservations for transactions.

The acquisition unit 30 acquires element information indicating trends of a plurality of elements including external factors related to the transaction target. The acquisition unit 30 acquires element information indicating a tendency of a plurality of elements including posts related to transaction targets on the SNS. The acquisition unit 30 acquires element information indicating trends of a plurality of elements including the number of searches for a transaction target. The acquisition unit 30 acquires element information indicating trends of a plurality of elements including internal factors related to the transaction target. The acquisition unit 30 acquires element information indicating trends of a plurality of elements including incentives targeted at trade targets. The acquisition unit 30 acquires element information indicating trends of a plurality of elements including coupons targeted for transactions. The acquisition unit 30 acquires element information indicating a tendency of a plurality of elements including price reductions related to transaction objects.

In addition, the acquisition unit 30 acquires from the terminal device 2 information indicating the number of times the transaction target has been displayed (the number of times the user U has browsed). For example, the acquisition unit 30 acquires from the terminal device 2 the number of times the content has been displayed and the number of times each transaction object has been displayed. In addition, the acquisition unit 30 acquires control information for acquiring the number of times of display provided in advance together with the content. Then, the acquisition unit 30 stores the display count in the transaction target information storage unit 21 .

[3.3.2. calculation unit 31]
Based on the action history information acquired by the acquisition unit 30, the calculation unit 31 calculates a spec score, which is a score for the spec of the transaction target, for each piece of information indicated by the search query.

For example, the calculation unit 31 calculates the specification score for each piece of information indicated by the search query, using the selection history information of the user U for the transaction target information provided in response to the search query as the action history information. The calculation unit 31 may also calculate the spec score for each piece of information indicated by the search query, using the transaction history information of the user U for the transaction target for which information is provided in response to the search query as the action history information. can. Further, the calculation unit 31 calculates information of the selection history of the user U with respect to the information of the transaction object provided in response to the search query and information of the transaction history of the user U with respect to the transaction object information provided in response to the search query. can be used as action history information to calculate a spec score for each piece of information indicated by a search query.

Based on the action history information acquired by the acquisition unit 30, the calculation unit 31 also calculates a type score, which is a score for the spec type of the transaction target, for each piece of information indicated by the search query.

For example, the calculating unit 31 calculates the type score for each piece of information indicated by the search query, using the selection history information of the user U for the transaction target information provided in response to the search query as the action history information. The calculation unit 31 may also calculate a type score for each piece of information indicated by a search query, using information on the transaction history of the user U with respect to the transaction target for which information is provided in response to the search query as information on the action history. can. Further, the calculation unit 31 calculates information of the selection history of the user U with respect to the information of the transaction object provided in response to the search query and information of the transaction history of the user U with respect to the transaction object information provided in response to the search query. can be used as action history information to calculate a type score for each piece of information indicated by a search query.

Based on the spec score of each spec and the type score of each spec type calculated for each piece of information indicated by the search query, the calculation unit 31 calculates perspective determination dictionary information stored in the ranking information storage unit 23 (for example, FIG. 10 reference) is generated and updated.

The calculation unit 31 can also calculate an intra-type spec score for each piece of information indicated by a search query, instead of the spec score, based on the action history information acquired by the acquisition unit 30 .

For example, the calculation unit 31 calculates the intra-type specification score for each piece of information indicated by the search query, using the selection history information of the user U for the transaction target information provided in response to the search query as the action history information. . In addition, the calculation unit 31 calculates an intra-type spec score for each piece of information indicated by the search query, using the information of the transaction history of the user U for the transaction target for which information is provided in response to the search query as the information of the action history. can also Further, the calculation unit 31 calculates information of the selection history of the user U with respect to the information of the transaction object provided in response to the search query and information of the transaction history of the user U with respect to the transaction object information provided in response to the search query. can also be used as action history information to calculate an intra-type spec score for each piece of information indicated by a search query.

The calculation unit 31 calculates perspective judgment dictionary information stored in the ranking information storage unit 23 (for example, 11) can be generated and updated.

When the approach determination dictionary information is in the state shown in FIG. 11, the calculation unit 31 uses the approach determination dictionary information (for example, see FIG. 11) when the search query is received by the receiving unit 32, Calculate the spec score for each corresponding spec. For example, the type score of each spec type associated with the information indicated by the search query received by the receiving unit 32 and the spec score within the type of each spec are generated by the generating unit 33 as cut-point determination dictionary information (see, for example, FIG. 11). obtained from Then, the calculation unit 31 calculates the spec score by multiplying the type score and the spec score acquired by the generation unit 33 .

Note that the calculation unit 31 can also correct the spec score and type score calculated as described above. For example, the calculation unit 31 can correct the type score based on the selection history of the spec type by the user U from among the plurality of spec types included in the spec type list provided to the user U. For example, the calculation unit 31 corrects the spec score by multiplying the spec score by a coefficient k1 (≧1) according to the number of spec selections by the user U in the spec list.

Further, the calculation unit 31 can correct the spec score based on the selection history of specs by the user U from among the specs included in the spec list provided to the user U. For example, the calculation unit 31 corrects the spec score by multiplying the spec score by a coefficient k1 (≧1) according to the number of spec selections by the user U in the spec list.

[3.3.3. reception unit 32]
The reception unit 32 receives various requests. The reception unit 32 receives various requests from an external information processing device. The reception unit 32 receives information indicating various requests from an external information processing device via the communication unit 10 . For example, the receiving unit 32 receives requests from the terminal device 2 or the external device 3 . The accepting unit 32 accepts a search query including the search keyword input by the user U from the terminal device 2 .

[3.3.4. generation unit 33]
The generation unit 33 executes generation processing for generating various information. For example, the generation unit 33 executes generation processing based on various information acquired by the acquisition unit 30, various information stored in the storage unit 11, or various information received from an external information processing device.

The generation unit 33 generates, for example, the content C described above including the first tab TB1, the second tab TB2, the search box BX1, the first tab content C1, and the second tab content C2.

For example, the generation unit 33 generates the first tab content C1 in which search results corresponding to search queries including search keywords input by the user U are arranged. The generation unit 33 generates the first tab content C1 in which the search results obtained by the search process using the search keyword input by the user U are arranged.

The search process is performed, for example, by extracting transaction targets from transaction target information including search keywords. For example, when the search keyword included in the search query is "television", the generation unit 33 extracts the transaction target information corresponding to the search query "television" from the transaction target information storage unit 21 in the search process. It should be noted that the extraction of information corresponding to the search query is performed using a conventional technique, and any processing may be used as long as the transaction target can be specified, and detailed description thereof will be omitted.

Also, when the search process is performed by a device (search device) other than the information processing device 1, the acquisition unit 30 transmits a search query to the search device and receives search results of the search query from the search device. The generation unit 33 generates a search result of the search query using the transaction target information extracted as information corresponding to the search query. For example, the generation unit 33 generates the list information of the transaction target of the extracted transaction target information as the search result of the search query.

Also, the generating unit 33 generates a plurality of pieces of ranking information based on the search query received by the receiving unit 32 . For example, the generating unit 33 determines the types and order of the plurality of ranking information to be provided to the user U based on the search query received by the receiving unit 32 . The type of ranking information includes, for example, a ranking cutoff and a display format of the ranking information. The types of ranking information also include the number of ranking candidates included in the ranking information.

The generating unit 33 generates the spec score of each spec associated with the information indicated by the search query received by the receiving unit 32 and each Get the type score for a spec type.

The generation unit 33 can also use the perspective determination dictionary information shown in FIG. 11 instead of the perspective determination dictionary information shown in FIG. In this case, the generation unit 33 acquires the intra-type spec score of each spec and the type score of each spec type associated with the information indicated by the search query from the perspective determination dictionary information (see FIG. 11). The spec score for each spec is calculated by multiplying the spec score within the type of each spec by the spec score for each spec. Such calculation is performed by the calculator 31 .

Then, the generating unit 33 determines, among the plurality of specs, specs whose spec score satisfies a condition set in advance as a cut point for ranking. The preset conditions are, for example, a condition that the spec score is a preset number of specs in descending order of the spec score, or a condition that the spec score is the highest spec score within each spec type. Further, the preset condition is, for example, a condition that one or more specs belong to each of a preset number of spec types in order from the spec type with the highest type score among the type scores of each spec type. may

For example, the generating unit 33 determines a preset number of specs in descending order of the spec scores of the specs associated with the information indicated by the search query, starting from the spec score with the highest spec score, as cut points in the plurality of ranking information. The generating unit 33 also determines the ranking information for each of the plurality of specified specs in descending order of the spec score.

The generating unit 33 also determines the display format of the ranking information of the spec with the highest spec score to be the list format, and the display format of the other ranking information to be the grid format. Note that the generation unit 33 sets the display format of the ranking information of the specs with the highest spec score to a list format when the highest spec score is equal to or higher than a preset threshold value, and otherwise, sets the spec with the highest spec score. The display format of the ranking information may be a grid format.

In addition, the generation unit 33 uses the spec score of each spec associated with the information indicated by the search query to identify the spec with the highest spec score within each spec type, and uses each of the identified specs as a cut point in the ranking information. can decide. In addition, the generation unit 33 determines the order of spec types set in advance as the order of arrangement. The generation unit 33 can also determine the order of arrangement of a plurality of pieces of ranking information with the specified specifications as a starting point, in descending order of the specification type.

In addition, the generating unit 33 generates one or more specs belonging to each of a preset number of spec types in order from the spec type with the highest type score among the type scores of each spec type associated with the information indicated by the search query. can also be determined as a cut in the ranking information. In this case, the generation unit 33 determines, for example, the ranking information for each of the plurality of specified specs in order of descending classification score. Note that the generation unit 33 can also determine one or more specs belonging to each spec type with a type score equal to or greater than a preset threshold value as a cut point in the ranking information, instead of a preset number of spec types. .

In addition, the generating unit 33 determines the display format of the ranking information of the spec with the highest type score to be the list format, and the display format of the other ranking information to be the grid format. Note that the generation unit 33 sets the display format of the ranking information of the specifications with the highest category score to the list format when the highest category score is equal to or higher than a preset threshold value, and otherwise sets the specification of the highest category score to the list format. The display format of the ranking information may be a grid format.

In addition, the generation unit 33 selects a predetermined number of spec types in order from the spec type with the highest type score among the type scores of the spec types associated with the information indicated by the search query, and uses them as cut points in a plurality of ranking information. can also decide. In this case, the generating unit 33 determines the ranking information for each of the specified plurality of spec types in descending order of the type score. Note that the generation unit 33 can also determine the spec type with a type score equal to or greater than a preset threshold value as a cut point in the ranking information instead of the preset number of spec types.

The generation unit 33 can also determine both the spec type and the spec as cut points in a plurality of ranking information. For example, the generating unit 33 generates a preset number (1 or more) of spec types in order from the spec type with the highest type score, and a preset number (1 or more) in order from the spec type with the highest spec score. ) can be determined as cut points in a plurality of ranking information.

Moreover, the generation unit 33 can also determine a category or a brand as an aspect in at least one piece of ranking information among the plurality of pieces of ranking information based on the search query. The generating unit 33 can use a plurality of cuts including categories, brands, spec types, and specs as ranking cuts in a plurality of pieces of ranking information.

In this case, the generation unit 33 may determine the ranking information of the cuts other than the spec type and specs in higher order than the ranking information cut in terms of the spec type or specs, or may decide the ranking information in the opposite order. can. Ranking information on aspects other than spec types and specs are, for example, ranking information for each category, ranking information for each brand, and the like.

In addition, the generation unit 33 can also exclude specs belonging to a spec type in which a plurality of specs can be set for the same transaction object from the ranking cut. By excluding spec types that can set multiple specs for the same trading target from the ranking, it is possible to exclude the specifications of the spec type that may reduce the accuracy of the spec score from the ranking. can.

The generation unit 33 executes a process of generating a plurality of ranking information based on the determined types and order of the plurality of ranking information and the transaction target information related to the transaction target. For example, the generation unit 33 performs a process of calculating a score for each transaction target that is a ranking element from the perspective indicated by the determined ranking information type for each determined type.

For example, the generating unit 33 uses a function (score function) for outputting the score of the transaction target, using as input the transaction target information of the transaction target corresponding to the cut indicated by the determined ranking information type. Calculate the score. For example, the generation unit 33 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 generation unit 33 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 generation unit 33 uses the calculated score to rank the transaction objects for each determination type, and generates ranking information in which a plurality of transaction objects are arranged in the display format indicated by the determination type for each determination type. For example, the generating unit 33 generates the ranking information by ranking the transaction objects in descending order of score and arranging the transaction objects in descending order in the determined display format.

Then, the generation unit 33 generates the second tab content C2 in which the plurality of ranking information are arranged in the determined order. For example, when the display format is a list format (an example of a first display format), the generating unit 33 generates a plurality of transaction information (ranking element), set a large amount of information for each.

The generating unit 33 generates a screen (content C) to be provided to the terminal device 2 by appropriately using various techniques related to image generation, image processing, and the like. For example, the generation unit 33 appropriately uses various techniques such as Java (registered trademark) to generate a screen (content C) to be provided to the terminal device 2 . Note that the generation unit 33 may generate a screen (content C) to be provided to the terminal device 2 based on CSS, JavaScript (registered trademark), or HTML format. Further, for example, the generation unit 33 may generate screens (contents) in various formats such as JPEG (Joint Photographic Experts Group), GIF (Graphics Interchange Format), and PNG (Portable Network Graphics).

[3.3.5. providing unit 34]
The providing unit 34 provides various information. The providing unit 34 transmits various types of information to an external information processing device via the communication unit 10 . The providing unit 34 transmits various information to the terminal device 2 or the external device 3 . The providing unit 34 transmits content to the terminal device 2 . The providing unit 34 transmits information about the transaction target to the terminal device 2 .

For example, the providing unit 34 provides information generated by the generating unit 33 . For example, the providing unit 34 provides content C generated by the generating unit 33 . Provision of the content C is performed by transmitting the content C to the terminal device 2, for example. Note that, instead of the content C, the providing unit 34 can independently provide the same content as the first tab content C1 and the same content as the second tab content C2.

The content transmitted from the providing unit 34 to the terminal device 2 is displayed on the terminal device 2 . For example, the terminal device 2 can display content C provided by the providing unit 34, as shown in FIG.

Also, the providing unit 34 provides the user U with a spec list. The specification list is provided by, for example, transmitting the specification list to the terminal device 2 . FIG. 12 is a diagram showing an example of a specification list provided to the user U from the information processing device 1 according to the embodiment.

In the example shown in FIG. 12, contents C3 and C4 are displayed on the terminal device 2. In the example shown in FIG. The content C3 is a content showing a spec list, and the spec list shows spec types and specs in a hierarchical structure. By operating the terminal device 2, the user U selects a specification included in the specification list, and the content C4 including the information of the transaction object corresponding to the selected specification is sent from the providing unit 34 to the user U. provided.

For example, the user U operates the terminal device 2 to select a spec included in the spec list, and information on the spec selected by the user U is transmitted from the terminal device 2 to the information processing device 1 . Information on the specifications selected by the user U is stored in the storage unit 11 (for example, the user information storage unit 20, the transaction target information storage unit 21, or the like). The providing unit 34 transmits to the terminal device 2 the content C<b>4 including the information of the transaction target of the specifications selected by the user U based on the information of the selected specifications. As a result, the terminal device 2 displays the content C<b>4 including the information of the transaction target of the specifications selected by the user U.

Although the content C3 described above is a spec information list including spec types, it is not limited to such an example, and may be a spec list that does not include spec types, for example.

[4. Processing procedure]
Next, the procedure of information processing executed by the information processing apparatus 1 according to the embodiment will be described with reference to FIGS. 13 and 14. FIG. 13 and 14 are flowcharts showing an example of the flow of information processing executed by the information processing apparatus 1. FIG.

First, FIG. 13 will be described. FIG. 13 shows an example of score calculation processing performed by the information processing device 1 . As shown in FIG. 13, the processing unit 12 of the information processing device 1 acquires the action history of the user U from the storage unit 11 (step S10). The processing unit 12 calculates the spec score or the intra-type spec score and the type score based on the action history of the user U acquired in step S10 (step S11).

Then, the processing unit 12 generates or updates the perspective determination dictionary information based on the spec score or the intra-type spec score and the type score calculated in step S11 (step S12), and ends the processing shown in FIG.

Next, FIG. 14 will be described. FIG. 14 shows an example of processing in which the information processing apparatus 1 provides the content C to the user U after receiving a search query. As shown in FIG. 14, the processing unit 12 of the information processing device 1 receives a search query from the terminal device 2 via the network N and the communication unit 10 (step S20). Then, the processing unit 12 acquires the approach determination dictionary information stored in the storage unit 11, and uses the acquired approach determination dictionary information to obtain the type score and the type score corresponding to the information indicated by the search query received in step S20 A spec score is acquired (step S21).

Next, the processing unit 12 determines the type and order of ranking information based on the type score and spec score acquired in step S21 (step S22).

Next, the processing unit 12 generates the content C including the second tab content C2 in which the ranking information of the type determined in step S22 is arranged in the order determined in step S22 (step S23). Then, the processing unit 12 provides the content C generated in step S23 (step S24), and ends the processing shown in FIG.

[5. Modification]
The information processing apparatus 1 described above may be implemented in various different forms other than the above embodiment. Therefore, other embodiments of the information processing apparatus 1 will be described below.

[5.1. User U]
In the above embodiment, the user U who is 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 U may be any user U, for example, a user U 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 that is traded through Internet shopping, an auction site, a flea market site, or the like. Further, the search target and ranking target by the search query are not limited to the transaction target, and may be other than the transaction target.

[5.3. Provide information on the transaction object]
In the above-described embodiment, an example of information processing in which the information processing device 1 provides content to the terminal device 2 has been described, but it is not necessary to be limited to the above example. For example, an external server may provide content to the terminal device 2 . In this case, the information processing device 1 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 device 1 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.

[6. Hardware configuration]
The information processing device 1 or the terminal device 2 according to the embodiments described above is implemented by a computer 80 configured as shown in FIG. 15, for example. The information processing apparatus 1 will be described below as an example. FIG. 15 is a hardware configuration diagram showing an example of a computer 80 that implements the functions of the information processing apparatus 1 according to the embodiment. The computer 80 includes a CPU 81, a RAM 82, a ROM (Read Only Memory) 83, a HDD (Hard Disk Drive) 84, a communication interface (I/F) 85, an input/output interface (I/F) 86, and a media interface (I/F). ) 87.

The CPU 81 operates based on programs stored in the ROM 83 or HDD 84 and controls each section. The ROM 83 stores a boot program executed by the CPU 81 when the computer 80 is started, a program depending on the hardware of the computer 80, and the like.

The HDD 84 stores programs executed by the CPU 81, data used by these programs, and the like. The communication interface 85 receives data from other devices via the network N (see FIG. 6), sends the data to the CPU 81, and transmits data generated by the CPU 81 to other devices via the network N. FIG.

The CPU 81 controls output devices such as a display and a printer and input devices such as a keyboard and a mouse through an input/output interface 86 . The CPU 81 acquires data from the input device via the input/output interface 86 . The CPU 81 also outputs the generated data to the output device via the input/output interface 86 .

The media interface 87 reads programs or data stored in the recording medium 88 and provides them to the CPU 81 via the RAM 82 . The CPU 81 loads the program from the recording medium 88 onto the RAM 82 via the media interface 87 and executes the loaded program. The recording medium 88 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. and so on.

For example, when the computer 80 functions as the information processing apparatus 1 according to the embodiment, the CPU 81 of the computer 80 implements the functions of the processing unit 12 by executing programs loaded on the RAM 82 . Further, the data in the storage unit 11 is stored in the HDD 84 . The CPU 81 of the computer 80 reads these programs from the recording medium 88 and executes them, but as another example, these programs may be acquired via the network N from another device.

[7. 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. For example, the terminal device 2 can partially determine the types and order of the plurality of ranking information, and in this case, the information processing device 1 and part of the terminal device 2 function as the information processing device.

[8. effect〕
As described above, the information processing device 1 according to the embodiment includes the acquisition unit 30 and the calculation unit 31 . The acquisition unit 30 acquires information on the action history of the user U with respect to transaction target information provided in response to a search query. Based on the action history information acquired by the acquisition unit 30, the calculation unit 31 calculates a spec score, which is a score for the spec of the transaction target, for each piece of information indicated by the search query. As a result, the information processing device 1 can easily narrow down the transaction targets corresponding to the search query by using the specifications as a starting point.

The action history information includes selection history information of the user U with respect to transaction target information, and the calculation unit 31 calculates a specification score based on the selection history information. As a result, the information processing apparatus 1 can increase the spec score of specs that are frequently selected by the user U, for example.

Further, the action history information includes information on the transaction history of the user U with respect to the transaction object indicated by the transaction object information, and the calculation unit 31 calculates the spec score based on the transaction history information. . Thereby, the information processing apparatus 1 can increase the spec score of the spec with which the user U has a high transaction frequency, for example.

The information processing device 1 also includes a generating unit 33 and a providing unit 34 . The generation unit 33 generates ranking information that ranks a plurality of transaction objects having specs that satisfy a condition in which spec scores are preset among a plurality of specs. The providing unit 34 provides the user U with the ranking information generated by the generating unit 33 . As a result, the information processing device 1 can provide the user U with ranking information in which the transaction targets corresponding to the search query are ranked according to the specifications, for example.

The information processing device 1 also includes a reception unit 32 that receives search queries. The generating unit 33 generates ranking information based on the spec score corresponding to the information indicated by the search query received by the receiving unit 32 among the spec scores for each information indicated by the search query. As a result, the information processing device 1 can provide the user U with ranking information in which transaction targets corresponding to the search query are ranked according to appropriate specifications corresponding to the search query, for example.

The generating unit 33 generates ranking information for each of a plurality of specs belonging to different spec types, and the providing unit 34 provides the user U with the plurality of ranking information in a preset order of spec types. As a result, the information processing apparatus 1 can provide the user U with ranking information based on specs belonging to a plurality of spec types.

Further, the calculation unit 31 calculates a type score, which is a score for the spec type of the transaction target, based on the action history information acquired by the acquisition unit 30 . The generation unit 33 generates ranking information for each of a plurality of specs belonging to different spec types. The providing unit 34 provides the user U with a plurality of pieces of ranking information in descending order of classification score. As a result, the information processing apparatus 1 can provide the user U with ranking information in which specifications belonging to a plurality of specification types are used as a starting point, in descending order of the frequency of behavior of the user U, for example.

The providing unit 34 also provides the user U with a spec list including a plurality of specs, and provides the user U with information on a plurality of transaction targets belonging to specs selected by the user U from the spec list. The calculation unit 31 corrects at least one of the spec score and the type score based on the spec selection history by the user U. Thereby, the information processing apparatus 1 can appropriately correct the spec score and the type score.

The generation unit 33 also generates ranking information for each of a plurality of specs belonging to the same spec type. The providing unit 34 provides the user U with a plurality of pieces of ranking information in descending order of spec score. As a result, the information processing apparatus 1 can provide the user U with ranking information, for example, based on a plurality of specifications, in descending order of the behavior frequency of the user U. As shown in FIG.

In addition, the generation unit 33 excludes specs belonging to a spec type in which a plurality of specs can be set for the same transaction object, from ranking information generation targets. As a result, the information processing device 1 excludes spec types for which a plurality of specs can be set for the same transaction object from the ranking cutoff, thereby allowing the spec types of the spec types whose spec score accuracy may be low. can be excluded from the ranking cut.

Further, the information on the transaction target includes information on the transaction target to be traded in electronic commerce. As a result, the information processing apparatus 1 can easily narrow down the transaction targets corresponding to the search query, which are traded in electronic commerce as the transaction targets corresponding to the search query, by using the specifications as a starting point.

As described above, the embodiments of the present application have been described in detail with reference to the drawings, but these are examples, and various modifications and improvements, including the aspects described in the section of the disclosure of the invention, can be made based on the knowledge of those skilled in the art. It is possible to implement the invention in other forms.

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.

1 information processing device 2 terminal device 3 external device 10 communication unit 11 storage unit 12 processing unit 20 user information storage unit 21 transaction target information storage unit 22 content storage unit 23 ranking information storage unit 30 acquisition unit 31 calculation unit 32 reception unit 33 generation unit 34 provision unit 100 information processing system

Claims (12)

an acquisition unit that acquires action history information including at least one of the number of times a user selects information on a transaction target provided in response to a search query and the number of transactions by the user of the transaction target ;
Based on at least one of the number of selections and the number of transactions included in the action history information acquired by the acquisition unit, a spec score, which is a score for the spec of the transaction target, is indicated in the search query. an information processing apparatus, comprising: a calculating unit that calculates for each piece of information that is obtained. The calculation unit
The specification score is set higher as the specification included in the information of the transaction object has a higher number of at least one of the number of selections and the number of transactions.
The information processing apparatus according to claim 1, characterized by: a generation unit that generates ranking information in which a plurality of transaction objects having specifications satisfying a condition for which the specification score satisfies a preset condition among the plurality of specifications, and ranking information;
3. The information processing apparatus according to claim 1, further comprising a providing unit that provides the ranking information generated by the generating unit to the user. A reception unit that receives the search query,
The generating unit
The ranking information is generated based on a spec score corresponding to the information indicated by the search query received by the receiving unit, among the spec scores for each information indicated by the search query. 4. The information processing device according to 3 . The generating unit
generating the ranking information for each of the plurality of specs belonging to different spec types;
The providing unit
5. The information processing apparatus according to claim 3 , wherein the plurality of ranking information are provided to the user in order of spec types set in advance. The calculation unit
calculating a type score, which is a score for the spec type of the transaction target, based on the action history information obtained by the obtaining unit;
The generating unit
generating the ranking information for each of the plurality of specs belonging to different spec types;
The providing unit
5. The information processing apparatus according to claim 3 , wherein the plurality of pieces of ranking information are provided to the user in descending order of the category score. The providing unit
providing the user with a spec list including a plurality of the spec types, providing the user with information on a plurality of the transaction targets belonging to the spec selected by the user from the spec list;
The calculation unit
7. The information processing apparatus according to claim 6 , wherein at least one of said spec score and type score is corrected based on a selection history of said spec by said user. The generating unit
generating the ranking information for each of the plurality of specs belonging to the same spec type;
The providing unit
The information processing apparatus according to any one of claims 3 to 7 , wherein the plurality of ranking information are provided to the user in descending order of the spec score. The generating unit
The information processing according to any one of claims 3 to 8 , wherein specs belonging to a spec type in which a plurality of said specs can be set for the same transaction object are excluded from targets for generating said ranking information. Device. The information on the trading object is
10. The information processing device according to any one of claims 1 to 9 , wherein the information processing device includes information on a transaction object to be traded in electronic commerce. A computer-executed information processing method comprising:
an acquisition step of acquiring action history information including at least one of the number of times a user selects information on a transaction object provided in response to a search query and the number of transactions by the user of the transaction object ;
Based on at least one of the number of selections and the number of transactions included in the action history information acquired by the acquiring step, a spec score, which is a score for the spec of the transaction target, is indicated in the search query. and a calculating step of calculating for each piece of information obtained. an acquisition procedure for acquiring action history information including at least one of the number of times a user selects information on a transaction target provided in response to a search query and the number of transactions by the user of the transaction target ;
Based on at least one of the number of selections and the number of transactions included in the action history information acquired by the acquisition procedure, a spec score, which is a score for the spec of the transaction target, is indicated in the search query. An information processing program characterized by causing a computer to execute a calculation procedure for calculating each piece of information obtained.

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