JP7045515B1 - Information processing equipment, information processing methods and information processing programs - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing device, an information processing method and an information processing program for improving the convenience of a search service.
An information processing device 10 realized by a server device, a cloud system, or the like that provides various information related to real estate information to a user terminal is a content information acquisition unit 131 that acquires content information related to the content to be searched. When the number of contents corresponding to the generation unit 132 that analyzes the content information acquired by the content information acquisition unit 131 and generates a search query related to the content and the search query generated by the generation unit 132 is equal to or more than a predetermined number. , A presentation unit 136 that presents a search query as a search word to the user.
[Selection diagram] Fig. 2

Description

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

Conventionally, for example, on an EC site, there is an information processing device that generates a search query for a product from word-of-mouth information about the product posted by a user (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2020-135392

However, in the prior art, for example, it merely generates a search query, and there is room for improvement in improving the convenience of the search service.

The present invention has been made in view of the above, and an object of the present invention is to provide an information processing apparatus, an information processing method, and an information processing program capable of improving the convenience of a search service.

In order to solve the above-mentioned problems and achieve the object, the information processing apparatus according to the present invention includes a content information acquisition unit, a generation unit, and a presentation unit. The content information acquisition unit acquires content information related to the content to be searched. The generation unit analyzes the content information acquired by the content information acquisition unit and generates a search query for the content. When the content corresponding to the search query generated by the generation unit is a predetermined number or more, the presentation unit presents the search query to the user as a search word.

According to the present invention, the convenience of the search service can be improved.

FIG. 1 is a diagram showing an example of information processing according to an embodiment. FIG. 2 is a block diagram showing a configuration example of the information processing apparatus according to the embodiment. FIG. 3 is a diagram showing an example of information stored in the real estate information storage unit according to the embodiment. FIG. 4 is a diagram showing an example of information stored in the content information storage unit according to the embodiment. FIG. 5 is a diagram showing an example of information stored in the user information storage unit according to the embodiment. FIG. 6 is a diagram showing an example of information stored in the user attribute storage unit according to the embodiment. FIG. 7 is a diagram showing an example of the time transition of the search query according to the embodiment. FIG. 8 is a flowchart showing an example of the search word generation process according to the embodiment. FIG. 9 is a flowchart showing an example of the search word presentation process according to the embodiment. FIG. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing apparatus according to the embodiment.

Hereinafter, an information processing apparatus, an information processing method, and an embodiment for implementing an information processing program according to the present application (hereinafter, referred to as “embodiments”) will be described in detail with reference to the drawings. Note that this embodiment does not limit the information processing apparatus, information processing method, and information processing program according to the present application.

[Embodiment]
[1. Information processing]
First, an example of information processing according to an embodiment will be described with reference to FIG. FIG. 1 is a diagram showing an example of information processing according to an embodiment. In the following, a case where the content to be searched is real estate information will be described as an example. The content is not limited to real estate information, but may be a product or the like provided on an EC site, or may be a moving image content such as a movie.

As shown in FIG. 1, the information processing device 10 according to the embodiment has, for example, a real estate information storage unit, and is an information processing device that provides various information related to real estate information to a user terminal 50 that is a client terminal. Is. The information processing device 10 is realized by, for example, a server device, a cloud system, or the like.

Real estate includes buildings and land. In addition, the real estate information here includes information on the rental or sale of various real estate such as a residence, a store rental contract, a residence, a store sales contract, a land rental contract or a sales contract.

Further, the information processing apparatus 10 has a content information storage unit, and the content information storage unit stores word-of-mouth information (an example of content information) about real estate stored in the real estate information storage unit.

The user terminal 50 is a terminal device owned by the user U, and provides various information about the real estate stored in the real estate information storage unit of the information processing device 10 to the user U by data communication with the information processing device 10. The user terminal 50 is various client terminals having a communication function, such as a smartphone, a tablet terminal, a personal computer, and a wearable terminal.

By the way, for example, by generating a search query related to the content based on word-of-mouth information about the content, it is possible to generate a flexible search query from the user's point of view. However, in this case, for example, it is assumed that there is only one content corresponding to the generated search query, so the generated search query is not always useful.

Further, for example, it is assumed that the user U accesses the real estate site provided by the information processing apparatus 10 and searches for a property. In this case, the user U operates the user terminal 50 and inputs the search conditions for the desired property. However, for example, there are cases where the user U does not know what condition should be used as the search criterion to input the search condition.

Therefore, in the information processing according to the embodiment, a new search query is generated from the content information, and the search query satisfying a predetermined condition is presented to the user U as a search word serving as a search axis.

For example, the information processing apparatus 10 acquires word-of-mouth information from the user terminal 50 of the user U (step S01). The word-of-mouth information here is, for example, a word-of-mouth about the property or the area around the property by a predetermined user U. For example, the predetermined user U includes current or past residents, residents in the vicinity, employees of a real estate company, persons who have viewed the property, and the like. The word-of-mouth information corresponds to an example of content information related to the content to be searched.

Subsequently, the information processing apparatus 10 stores the acquired word-of-mouth information in the content information storage unit, analyzes the word-of-mouth information, and generates a search query for the corresponding property (step S02). For example, the information processing apparatus 10 analyzes word-of-mouth information for each property and generates frequently-used words and positive words as search queries.

Here, the frequent word refers to a word in which the rate of appearance exceeds a predetermined value among the word-of-mouth related to the target real estate. Further, the positive word is a keyword such as an evaluation of the real estate itself to be commented such as "high ceiling", and is a word indicating a favorable evaluation. Further, the positive word may be a keyword such as an evaluation regarding a real estate-related object to be commented such as "fireworks are beautiful", and may be a word indicating a favorable evaluation.

That is, a positive word is a keyword that is determined to be favorable by various arbitrary determination means, and is a concept that includes a keyword for the real estate itself or an object related to the real estate (for example, a surrounding area). ..

Subsequently, the information processing apparatus 10 presents, for example, a search query having a predetermined number or more of properties corresponding to the search query to the user U as a search word among the generated search queries (step S03).

That is, the information processing apparatus 10 repeatedly executes the processes of steps S01 and S02, and when the generated search query becomes highly versatile, presents it to the user U as a search word.

In the example shown in the figure, the case where the search word is "property where fireworks can be seen" is shown. For example, when the user U selects a search word, the information processing apparatus 10 performs a search process based on the search condition including the search word, and the search result is displayed on the user terminal 50.

Here, the search word is for proposing a new search cut for the content to the user U. In addition, for example, the search word may be optimized by using the personal data of the user U so as to be the search axis when the user U searches the content.

That is, for example, a search query that the user U may be interested in may be inferred and presented as a search word. The search word may be paraphrased as a search condition, or the search word may be presented as one of the search categories. For example, when presented as a search category, it is possible to easily search for content corresponding to the newly generated search query such as "property in which fireworks can be seen" as described above. That is, it is possible to propose a flexible and new search axis to the user U.

As described above, in the information processing according to the embodiment, word-of-mouth information (an example of content information) related to the content is acquired, and a search query for the content is generated based on the word-of-mouth information.

Then, the information processing apparatus 10 according to the embodiment presents as a search word a search query in which the corresponding content is a predetermined number or more among the generated search queries. Therefore, according to the information processing according to the embodiment, a new search query with high versatility is presented as a search word that can be a search axis, so that the convenience of the search service can be improved.

[2. Configuration example of information processing device]
Next, a configuration example of the information processing apparatus 10 will be described with reference to FIG. FIG. 2 is a block diagram showing a configuration example of the information processing apparatus 10 according to the embodiment. As shown in FIG. 2, the information processing apparatus 10 includes a communication unit 110, a storage unit 120, and a control unit 130.

The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Then, the communication unit 110 connects various wireless communication networks such as 4G (Generation), 5G, LTE (Long Term Evolution), WiFi (registered trademark), wireless LAN (Local Area Network), and various wired communication networks. Information is sent and received to and from an external device via the device.

The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. Further, the storage unit 120 includes a real estate information storage unit 121, a content information storage unit 122, a user information storage unit 123, a user attribute storage unit 124, and a feedback information storage unit 125.

The real estate information storage unit 121 stores various information related to the real estate provided by the information processing device 10. FIG. 3 is a diagram showing an example of information stored in the real estate information storage unit 121 according to the embodiment.

As shown in FIG. 3, for example, the real estate information storage unit 121 stores information of items such as “property ID”, “property data”, “search query”, and “search word” in association with each other. The "property ID" is an identifier for identifying the property, and the "property data" is created by the real estate agent or data on the contents of the property (property name, address, age, area, distance to the station, etc.). It is data about the surrounding environment (for example, a quiet residential area). The property data is, for example, data posted by a real estate agent, but may be data edited on the information processing apparatus 10 side based on the posted data.

The "search query" is a search query associated with the corresponding property data. The search query may be an excerpt from the property data, or may be arbitrarily set on the information processing apparatus 10 side. That is, the information processing apparatus 10 may generate a search query with a different perspective from the content posted by the real estate agent.

The "search word" is a search query in which the number of applicable properties is a predetermined number or more among the search queries. Note that, for example, the search word is not limited to the search query generated by the information processing apparatus 10 from the content information as described above, and may include, for example, a search query posted by a real estate agent.

Returning to the description of FIG. 2, the content information storage unit 122 will be described. The content information storage unit 122 stores various content information related to the property stored in the real estate information storage unit 121. FIG. 4 is a diagram showing an example of information stored in the content information storage unit 122 according to the embodiment.

As shown in FIG. 4, the content information storage unit 122 stores information of items such as “property ID”, “word-of-mouth information”, “area information”, and “view information” in association with each other. As described above, the "property ID" is an identifier for identifying the property.

"Word-of-mouth information" is a word-of-mouth posted for the corresponding property. The "area information" is, for example, information regarding an area in which a corresponding property exists, and includes, for example, information regarding crime prevention and disaster prevention in the area.

The "view information" is information on the view of the property, and includes, for example, three-dimensional map data that reproduces the buildings around the property, information on the topography of the property, and the like.

Returning to the description of FIG. 2, the user information storage unit 123 will be described. The user information storage unit 123 is a storage unit that stores user information regarding the user U. FIG. 5 is a diagram showing an example of information stored in the user information storage unit 123 according to the embodiment. In the example shown in FIG. 5, the user information storage unit 123 stores information of items such as "user ID", "annual income", "work location", "site browsing history", and "card usage history" in association with each other. ..

The "user ID" indicates an identifier for identifying the user U, and the "annual income" indicates the annual income of the user U. Further, the "work location" indicates the work location of the user U. For example, the information regarding the "annual income" and the "work location" may be the information registered by the user U in the information processing apparatus 10 via the user terminal 50, and the information registered by the user U in the cooperation service described later may be used. It may be diverted.

The "site browsing history" indicates the browsing history of the user U on the Internet. The site browsing history includes, for example, browsing history of a real estate site provided by the information processing apparatus 10, browsing history of a linked service (for example, a portal site, etc.), and information about a search query in the linked service. You may try to do it. Further, the site browsing history may include, for example, a purchase history on a shopping site and a viewing history of news and videos.

Further, the "card usage history" indicates the usage history of the user U's credit card. For example, the information related to "card usage history" is information obtained from a linked credit card company, for example, information about a store where user U paid with a credit card, information about payment amount, information about payment date and time, and the like. included. Further, in addition to the card usage history, the payment history of other electronic payments (for example, QR code (registered trademark) payment, etc.) may be stored in the user information storage unit 123.

In addition, the user information storage unit 123 may store information about the family structure of the user U, the place of work (or school, etc.) of the cohabitant, and the current residence in association with each other. The family structure may be estimated from, for example, the site browsing history and the card usage history.

As an example, if there is data on baby products or childcare in the site browsing history, or if there is data purchased at a baby products store in the card usage history, it may be estimated that there is a child.

Returning to the description of FIG. 2, the user attribute storage unit 124 will be described. The user attribute storage unit 124 is a storage unit that stores information related to the attributes of the user U. The user attribute here is information about the characteristics of the user U.

FIG. 6 is a diagram showing an example of information stored in the user attribute storage unit 124 according to the embodiment. In the example shown in FIG. 6, the user attribute storage unit 124 associates information on items such as "user ID", "annual income", "family structure", "along the railway line", "hobby", and "store used" with each other. Remember.

The "user ID" indicates an identifier for identifying the user U. "Annual income" indicates the annual income attribute of the user U, and the attributes are classified according to the annual income. The annual income attribute is, for example, in increments of 1 million yen. “Family composition” indicates the family composition attributes of the user U, and for example, the attributes are classified according to the age, gender, and the like of the entire family.

“Along the line” indicates the attributes along the line of the train or bus used by the user U, and for example, the attributes are classified according to the place of work. The "hobby" indicates the hobby attribute of the user U, for example, the hobby is estimated by the above-mentioned "site browsing history", and the attribute is classified according to the estimated hobby.

Further, the "use store" indicates the use store attribute regarding the store used by the user U, and the attribute is classified according to the store frequently used by the user U. For example, the store attributes used are classified based on the location information of the user U, the above-mentioned "card usage history", and the like.

Returning to the description of FIG. 2, the feedback information storage unit 125 will be described. The feedback information storage unit 125 stores feedback information regarding the behavior of the user U with respect to the search result for each user attribute.

The feedback information here includes, for example, information such as whether or not a search result regarding real estate information is clicked, whether or not an inquiry is made to real estate, whether or not a material is requested for real estate information, and whether or not a preview is reserved.

For example, the feedback information is information about various actions taken by the user U with respect to the search result on the site, and the feedback information storage unit 125 classifies and stores the feedback information for each user attribute.

The control unit 130 is, for example, a controller, and various programs stored in a storage device inside the information processing device 10 by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like have a RAM as a work area. It is realized by executing as. Further, the control unit 130 is a controller, and is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 2, the control unit 130 includes a content information acquisition unit 131, a generation unit 132, a user information acquisition unit 133, a user attribute classification unit 134, a feedback information acquisition unit 135, and a presentation unit 136. It has a search unit 137.

The content information acquisition unit 131 acquires content information regarding real estate (an example of content) to be searched. For example, the content information acquisition unit 131 acquires word-of-mouth information posted to a real estate site provided by the information processing apparatus 10 as content information. For example, the content information acquisition unit 131 may acquire the information posted on the SNS (Social Networking Service) as word-of-mouth information.

Further, the content information acquisition unit 131 may acquire, for example, information about the location area of the property as content information. The information about the location area here is, for example, information about security and disaster prevention. Information on security here includes, for example, information on incidents that occurred in the location area, information on the number of reports to the police, information on the content of reports, etc., and information on disaster prevention includes information on disaster prevention maps and hazard maps in the location area. Is done.

The information on the location area may include, for example, information on vital statistics by age, information on the income level of the location area, and the like. That is, information on the attributes of the inhabitants living in the location area may be acquired as content information. For example, the search word to be presented may be determined so that the attribute of the inhabitant and the attribute of the user U match.

Further, the content information acquisition unit 131 may acquire the view information regarding the view of the property as the content information. For example, the view information is map information that reproduces information such as the height of the structure around the property and the topography around the property.

Then, the content information acquisition unit 131 writes the acquired content information in the content information storage unit 122.

The generation unit 132 analyzes the content information acquired by the content information acquisition unit 131 and generates a search query for the property. For example, the generation unit 132 analyzes word-of-mouth information for each property and generates a frequent word having a frequency of frequent occurrence of a predetermined number or more as a search query for the corresponding property.

Further, the generation unit 132 may extract a positive word from the word-of-mouth information and generate the positive word as a search query. For example, in this case, the generation unit 132 extracts a positive word by performing a predetermined language analysis process on the word-of-mouth information. More specifically, for example, the generation unit 132 extracts a positive word by performing a series of processes such as phrase extraction, context determination, viewpoint expansion, synonym conversion, and representative notation conversion on word-of-mouth information.

Further, the generation unit 132 may analyze the content information regarding the location area and generate a search query common to the properties existing in the location area. The generation unit 132 generates, for example, a search query such as "safety" for a property corresponding to a location area where the number of reports to the police (the number of incidents) is equal to or less than a predetermined value.

Further, the generation unit 132 generates, for example, a search query such as "low disaster prevention risk" for a property corresponding to a location area outside the disaster estimation area based on a hazard map. In addition, the generation unit 132 may generate a search query based on information about the number of parks in the location area and stores such as restaurants. For example, the generation unit 132 generates a search query such as "area with many green spaces" when there are a plurality of parks in the location area, and "there are many restaurants in the neighborhood" when there are a plurality of restaurants. Generate a search query such as.

Further, the generation unit 132 may, for example, analyze the view information as the content information and generate a search query. For example, the generation unit 132 simulates the view from the property based on the view information, and generates a search query based on the simulation result.

For example, the simulation is performed by mapping the target property to three-dimensional map data and calculating the view from the property. Then, the generation unit 132 generates a search query by classifying the simulation results into a predetermined category. Examples of a predetermined category here include "excellent view", "beautiful night view", and "you can see a symbol (for example, Mt. Fuji)". The word to be registered as a category may be acquired from various websites such as SNS. As an example, for example, a word may be used to register hashtags having a predetermined number of posts or more as a category. Further, for example, the generation unit 132 may generate a search query related to sunlight or the like from the above simulation result.

In addition, the generation unit 132 may generate a search query by comparing the rent market price around the property with the rent of the property. For example, in this case, the generation unit 132 calculates the surrounding rent market price based on the data stored in the real estate information storage unit 121, compares it with the rent of the corresponding property, and says, "It is more profitable than the rent market price." Generate a search query. Further, the generation unit 132 may generate a search query based on the initial cost of the property. For example, in this case, the generation unit 132 may generate a search query such as "profitable brokerage fee", "no deposit key money", and the like.

Further, the generation unit 132 may change the weight of the search query associated with each property information according to the time when the content information that is the source of the search query is created. FIG. 7 is a schematic diagram showing an example of the time transition of the search query according to the embodiment. Note that FIG. 7 shows a case where a frequently-used word "quiet" is generated as a search query from word-of-mouth information about a predetermined area.

For example, as shown in FIG. 7, when the number of posts of word-of-mouth information including "quiet" decreases with the passage of years, the generation unit 132 sets the weight of the search query "quiet" associated with a predetermined area low. do.

The weight here corresponds to, for example, the priority when displaying as a search result, and when the weight is lowered, the priority when displaying as a search result is lowered. The generation unit 132 may delete the search query "quiet" associated with a predetermined area.

That is, for example, the environment surrounding the property changes depending on the development status of the area, demographics, and the like, and the generation unit 132 changes the weight of the search query according to the change. This makes it possible to properly maintain the correspondence between the current situation and the search query associated with the property.

As shown in FIG. 7, the generation unit 132 decides to reduce the weight of the search query "quiet" when, for example, the number of posts of word-of-mouth information including "lively" which contradicts "quiet" increases. You may.

Further, the generation unit 132 is not limited to the time when the content information is created, and may change the weighting of the search query according to, for example, the creator of the content information. For example, if the poster of the word-of-mouth information is a current resident, the weight may be increased, and if the poster is a past resident, the weight may be decreased. That is, the generation unit 132 may set the weighting of each search query so that the current state is more reflected.

The user information acquisition unit 133 acquires various user information regarding the user U. For example, the user information acquisition unit 133 acquires user information from various linked services. For example, the user information acquisition unit 133 acquires information on the family structure, annual income, work location (location of the company where the company works), and credit card usage history from the credit card company. Further, for example, the user information acquisition unit 133 acquires information about a Web page viewed by the user U through the portal site, a search query entered on the portal site, and the like from a portal site provider.

The user information acquisition unit 133 may acquire the history of location information as user information from the user terminal 50, for example. Further, the user information acquisition unit 133 writes various acquired user information in the user information storage unit 123.

The user attribute classification unit 134 classifies the attributes of the user U based on the user information. For example, the user attribute classification unit 134 classifies the attributes of the user U based on the user information stored in the user information storage unit 123.

For example, the user attribute classification unit 134 classifies the annual income attribute of the user U from the user information regarding the annual income, and classifies the family composition attribute of the user U from the user attribute regarding the family composition. Further, the user attribute classification unit 134 classifies the attributes along the line of the user U from the user information regarding the movement tendency of the work location and the location information. For example, the railway line attribute is a railroad track or a bus line that makes it easy to access the work place, but in the case of car commuting, it indicates an arterial road that makes it easy to access the work place.

Further, the user attribute classification unit 134 classifies the hobby attributes of the user U based on the user information regarding the site browsing history. For example, the user attribute classification unit 134 classifies the hobbies of the user U by performing a predetermined analysis on the site browsing history. The hobby of the user U determined by the user attribute classification unit 134 may be one or a plurality for each user U. Further, when a plurality of hobbies are assigned to one user U, the user attribute classification unit 134 may be weighted for each hobby.

The user attribute classification unit 134 determines, for example, the store attribute of the user U based on the user information regarding the card usage history. For example, the user attribute classification unit 134 classifies the used store attributes by performing a predetermined analysis on the card usage history.

When the user attribute classification unit 134 classifies each user attribute, the user attribute classification unit 134 writes the classification result in the user attribute storage unit 124. The user attribute classification unit 134 may classify the user attributes at any time by performing the above determination process at a predetermined cycle, or the user attributes may be classified based on the time-series change of the classified user attributes. It may be determined. For example, the user attribute classification unit 134 may classify a series of changes between fishing and camping as user attributes when the user U whose hobby is fishing subsequently becomes a hobby.

The feedback information acquisition unit 135 acquires feedback information regarding the user's behavior with respect to the search result by the search unit 137 for each user attribute that classifies the user U based on the user information.

For example, the feedback information acquisition unit 135 acquires information on the action taken by the user U as feedback information in response to the search result by the search query or the search word specified by the user U. For example, in the feedback information, whether or not there is a click (access) to the individual page of the property displayed as a search result, whether or not there is a request for materials regarding the property, whether or not there is an inquiry about the property, whether or not there is a preview reservation for the property, and whether or not there is a contract for the property. Information such as is included.

The feedback information acquisition unit 135 may acquire, for example, the position information of the user U from the user terminal 50, and acquire information regarding whether or not the user U has actually visited the property as feedback information. Further, for example, the feedback information acquisition unit 135 may acquire information on the search content obtained by the user U searching around the property as feedback information. For example, if the user U searches for "area name + security" around the property, the feedback information acquisition unit 135 may analyze that the user U attaches great importance to "security".

The feedback information acquisition unit 135 analyzes the property browsing tendency and contract tendency for each user attribute according to the user attribute based on the acquired feedback information, and writes the analysis result in the feedback information storage unit 125. That is, the feedback information acquisition unit 135 analyzes the trend regarding the property and the search query for each user attribute based on the feedback information.

The feedback information acquisition unit 135 analyzes browsing tendency and contract tendency by analyzing, for example, the characteristics of the property that the user U is interested in for each user attribute and the characteristics of the wording displayed on the Web page of the corresponding property. do.

In this way, the feedback information acquisition unit 135 classifies the feedback information according to the user attribute and analyzes the tendency of the feedback information, so that the property or property page of the property or property page that the other user U having the same lifestyle as the user U is interested in. You can infer information about search queries that show features or interests.

When the content corresponding to the search query generated by the generation unit 132 is a predetermined number or more, the presentation unit 136 presents the search query to the user U as a search word. For example, the presentation unit 136 calculates the number of contents corresponding to the search query generated by the generation unit 132 in a predetermined cycle, and treats the search query in which the number of the contents exceeds the predetermined number as a search word.

For example, the presentation unit 136 determines a search word to be presented to the user U based on the user information acquired by the user information acquisition unit 133. For example, the presentation unit 136 refers to the feedback information storage unit 125, and determines a search word to be presented to the user U based on the analysis result regarding the user attribute of the user U.

For example, the presentation unit 136 refers to the feedback information storage unit 125, and determines a search query that is likely to be of interest to the user U as a search word. In other words, the presentation unit 136 determines as a search word a search query that is likely to be selected by the user from the attributes of the user. The presentation unit 136 may determine, for example, a search query selected by the user U in the past as a search word.

The search unit 137 searches for the content to be searched based on the search conditions specified by the user U and the search words selected by the user U. For example, the search unit 137 searches the real estate information storage unit 121 based on the information about the search condition received from the user terminal 50, and outputs the information about the real estate that matches the search condition as the search result. The search result by the search unit 137 is transmitted to the user terminal 50 and displayed on the user terminal 50. Note that, for example, the search word selected by the presentation unit 136 may be transmitted to the user terminal 50 together with the search result.

[3. Processing flow]
Next, an example of the processing procedure executed by the information processing apparatus 10 according to the embodiment will be described with reference to FIGS. 8 and 9. FIG. 8 is a flowchart showing an example of the search word generation process according to the embodiment. FIG. 9 is a flowchart showing an example of the search word presentation process according to the embodiment.

As shown in FIG. 8, first, the information processing apparatus 10 acquires the content information (step S101) and generates a search query based on the content information (step S102). Subsequently, the information processing apparatus 10 determines whether or not the generated search query satisfies a predetermined condition (step S103).

When the information processing apparatus 10 determines that the generated search query satisfies a predetermined condition (step S103; Yes), the information processing apparatus 10 registers the search query as a search word (step S104), and ends the search word generation process.

Further, in the determination of step S103, if the generated search query does not satisfy the predetermined condition (step S103; No), the information processing apparatus 10 ends the search word generation process.

Next, the processing procedure of the search word presentation processing will be described with reference to FIG. 9. As shown in FIG. 9, first, the information processing apparatus 10 acquires the user information (for example, the user ID) of the user U who is the searcher (step S201).

Subsequently, the information processing apparatus 10 determines a search word to be presented to the user U (step S202), presents the determined search word (step S203), and ends the search word presentation process.

[4. Modification example]
In the above-mentioned information processing apparatus 10, the search service related to real estate has been described as an example, but the present invention is not limited to this, and the present invention may be applied to the search of various services such as online shopping. good.

[5. effect〕
The information processing apparatus 10 according to the above-described embodiment analyzes the content information acquired by the content information acquisition unit 131 for acquiring the content information related to the content to be searched and the content information acquired by the content information acquisition unit 131, and makes a search query for the content. It includes a generation unit 132 to be generated, and a presentation unit 136 to present the search query as a search word to the user U when the content corresponding to the search query generated by the generation unit 132 is a predetermined number or more. Therefore, in the information processing apparatus 10 according to the embodiment, a new search query with high versatility can be presented as a search word, so that the convenience of the search service can be improved.

In addition, the content information acquisition unit 131 according to the embodiment acquires word-of-mouth information about the content as content information. Therefore, according to the information processing apparatus 10 according to the embodiment, it is possible to generate a flexible search query from the user's point of view.

In addition, the generation unit 132 according to the embodiment generates frequently-used words frequently appearing in a plurality of content information related to the same content as a search query. Therefore, according to the information processing apparatus 10 according to the embodiment, it is possible to generate a search query suitable for the content.

Further, the generation unit 132 according to the embodiment generates a positive word extracted from the content information as a search query. Therefore, according to the information processing apparatus 10 according to the embodiment, it is possible to generate a search query that favorably captures the content, so that it is possible to generate a highly practical search query.

Further, the information processing apparatus 10 according to the embodiment includes a user information acquisition unit 133 for acquiring user information about the user, and the presentation unit 136 to the user U based on the user information acquired by the user information acquisition unit 133. Determine the search word to present. Therefore, according to the information processing apparatus 10 according to the embodiment, it is possible to present a search word suitable for the user U.

Further, the information processing apparatus 10 according to the embodiment includes a search unit 137 for searching content based on a search query or a search word designated by the user U, and the presentation unit 136 classifies the user U based on the user information. The search word to be presented is determined based on the feedback information regarding the behavior of the user U with respect to the search result by the search unit 137 for each user attribute. Therefore, according to the information processing apparatus 10 according to the embodiment, it is possible to present a search query that is likely to be of interest to the user U as a search word.

Further, the generation unit 132 according to the embodiment changes the weighting of the generated search query according to the creation time when the content information is created. Therefore, according to the information processing apparatus 10 according to the embodiment, the weight of the search query can be updated to an appropriate value.

Further, the content information acquisition unit 131 according to the embodiment acquires the content information related to the real estate content, and the presentation unit 136 presents the search word regarding the real estate content. Therefore, according to the information processing apparatus 10 according to the embodiment, the convenience of the real estate site can be improved.

Further, the content information acquisition unit 131 according to the embodiment acquires information regarding the location area of the real estate as content information, and the generation unit 132 generates a search query based on the information regarding the location area. Therefore, according to the information processing apparatus 10 according to the embodiment, it is possible to generate a search query for real estate based on information not only on real estate but also on surrounding areas.

Further, the content information acquisition unit 131 according to the embodiment acquires information on the view from the real estate as the content information, and the generation unit 132 generates a search query based on the information on the view. Therefore, according to the information processing apparatus 10 according to the embodiment, a search query related to the view can be automatically generated.

Further, the information processing method according to the embodiment is an information processing method executed by a computer, and the content information acquisition step of acquiring the content information related to the content to be searched and the content information acquired by the content information acquisition step are obtained. A generation process that analyzes and generates a search query for content, and a presentation process that presents the search query as a search word to the user when the number of contents corresponding to the search query generated by the generation process is a predetermined number or more. include. Therefore, according to the information processing method according to the embodiment, a new search query with high versatility can be presented as a search word, so that the convenience of the search service can be improved.

Further, the information processing program according to the embodiment analyzes the content information acquisition procedure for acquiring the content information related to the content to be searched and the content information acquired by the content information acquisition procedure, and generates a search query for the content. The computer is made to execute the procedure and the presentation procedure of presenting the search query as a search word to the user when the content corresponding to the search query generated by the generation procedure is a predetermined number or more. Therefore, according to the information processing program according to the embodiment, a new search query with high versatility can be presented as a search word, so that the convenience of the search service can be improved.

[6. Hardware configuration]
Further, the information processing apparatus 10 according to the above-described embodiment is realized by, for example, a computer 1000 having a configuration as shown in FIG. FIG. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing apparatus 10 according to the embodiment. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400, and controls each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started, a program depending on the hardware of the computer 1000, and the like.

The HDD 1400 stores a program executed by the CPU 1100, data used by such a program, and the like. The communication interface 1500 receives data from another device via the network (communication network) N and sends it to the CPU 1100, and transmits the data generated by the CPU 1100 to the other device via the network N.

The CPU 1100 is referred to as an output device such as a display or a printer, and an input device such as a keyboard or a mouse (in FIG. 10, the output device and the input device are collectively referred to as an “input / output device” via the input / output interface 1600. ) Is controlled. The CPU 1100 acquires data from the input device via the input / output interface 1600. Further, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the program or data to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable Disk), a magneto-optical recording medium such as MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. And so on.

For example, when the computer 1000 functions as the information processing apparatus 10 according to the embodiment, the CPU 1100 of the computer 1000 realizes the function of the control unit 130 by executing the program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, these programs may be acquired from another device via the network N.

Although some of the embodiments of the present application have been described in detail with reference to the drawings, these are examples, and various modifications are made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure column of the invention. It is possible to carry out the present invention in other modified forms.

[7. others〕
Further, among the processes described in the above-described embodiments and modifications, all or part of the processes described as being automatically performed can be manually performed, or are described as being manually performed. It is also possible to automatically perform all or part of the processed processing by a known method. 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 figure is not limited to the information shown in the figure.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of them may be functionally or physically distributed / physically distributed in any unit according to various loads and usage conditions. Can be integrated and configured.

Further, the above-described embodiments and modifications can be appropriately combined as long as the processing contents do not contradict each other.

Further, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the content information acquisition unit 131 can be read as a content information acquisition means or a content information acquisition circuit.

10 Information processing device 50 User terminal 121 Real estate information storage unit 122 Content information storage unit 123 User information storage unit 124 User attribute storage unit 125 Feedback information storage unit 131 Content information acquisition unit 132 Generation unit 133 User information acquisition unit 134 User attribute classification unit 135 Feedback information acquisition unit 136 Presentation unit 137 Search unit

Claims (15)

The content information acquisition unit that acquires content information related to the content to be searched,
A generation unit that analyzes the content information acquired by the content information acquisition unit and generates a search query for the content, and a generation unit.
An information processing device including a presentation unit that presents the search query to the user as one of the search categories when the content corresponding to the search query generated by the generation unit is a predetermined number or more. .. The content information acquisition unit
The information processing apparatus according to claim 1, wherein word-of-mouth information about the content is acquired as the content information. The generator is
The information processing apparatus according to claim 1 or 2, wherein frequently-used words frequently appearing in a plurality of the content information related to the same content are generated as the search query. The generator is
The information processing apparatus according to claim 1, 2 or 3, wherein a positive word extracted from the content information is generated as the search query. A user information acquisition unit for acquiring user information about the user is provided.
The presentation unit is
The information processing apparatus according to any one of claims 1 to 4, wherein the search category to be presented to the user is determined based on the user information acquired by the user information acquisition unit. A search unit for searching the content based on the search query or the search category specified by the user is provided.
The presentation unit is
The fifth aspect of claim 5, wherein the search category to be presented is determined based on the feedback information regarding the user's behavior with respect to the search result by the search unit for each user attribute that classifies the user based on the user information. Information processing equipment. The generator is
The information processing apparatus according to any one of claims 1 to 6, wherein the weighting of the generated search query is changed according to the creation time when the content information is created. The content information acquisition unit
Acquire the above content information about real estate content related to real estate,
The presentation unit is
The information processing apparatus according to any one of claims 1 to 7, wherein the search category for the real estate content is presented. The content information acquisition unit
As the content information, information on the location area of the real estate is acquired, and
The generator is
The information processing apparatus according to claim 8, wherein the search query is generated based on the information about the location area. The content information acquisition unit
As the content information, information on the view from the real estate is acquired, and
The generator is
The information processing apparatus according to claim 8 or 9, wherein the search query is generated based on the information regarding the view. It is an information processing method executed by a computer.
The content information acquisition process for acquiring content information related to the content to be searched, and
A generation step of analyzing the content information acquired by the content information acquisition step and generating a search query for the content, and a generation step.
An information processing method including a presentation step of presenting the search query as one of the search categories to the user when the content corresponding to the search query generated by the generation step is a predetermined number or more. .. Content information acquisition procedure to acquire content information related to the content to be searched, and
A generation procedure that analyzes the content information acquired by the content information acquisition procedure and generates a search query for the content, and a generation procedure.
When the content corresponding to the search query generated by the generation procedure is a predetermined number or more, the computer is made to execute a presentation procedure for presenting the search query to the user as one of the search categories. Information processing program. The content information acquisition unit that acquires content information related to the content to be searched,
A generation unit that analyzes the content information acquired by the content information acquisition unit and generates a search query for the content, and a generation unit.
A presenting unit that presents the search query as a search word to the user when the content corresponding to the search query generated by the generation unit is a predetermined number or more.
Equipped with
The generator is
The weight of the generated search query is changed according to the time when the content information was created.
An information processing device characterized by this. It is an information processing method executed by a computer.
The content information acquisition process for acquiring content information related to the content to be searched, and
A generation step of analyzing the content information acquired by the content information acquisition step and generating a search query for the content, and a generation step.
A presentation step of presenting the search query as a search word to the user when the number of the contents corresponding to the search query generated by the generation step is a predetermined number or more.
Including
The production step is
The weight of the generated search query is changed according to the time when the content information was created.
An information processing method characterized by that. Content information acquisition procedure to acquire content information related to the content to be searched, and
A generation procedure that analyzes the content information acquired by the content information acquisition procedure and generates a search query for the content, and a generation procedure.
A presentation procedure for presenting the search query as a search word to the user when the number of the contents corresponding to the search query generated by the generation procedure is a predetermined number or more.
Let the computer run
The generation procedure is
The weight of the generated search query is changed according to the time when the content information was created.
An information processing program characterized by this.

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