JP2020098458A - Information processing apparatus, information processing method, and information processing program - Google Patents

Abstract

To extract information appropriately.SOLUTION: An information processing apparatus according to the present application includes an acquisition unit and an estimation unit. The acquisition unit acquires input information input by a user. A generation unit extracts, from the input information, a first keyword corresponding to a target and a second keyword related to the property of the target, thereby extracting transition information indicating the temporal transition of the second keyword.SELECTED DRAWING: Figure 4

Description

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

In recent years, with the dramatic spread of the Internet, for example, a technique related to analysis using various information on the Internet has been provided. For example, there is known a technique of analyzing a customer in consideration of a trend of a period using purchase history data or the like.

JP, 2005-146145, A

However, in the above-mentioned conventional technique, it is not always possible to appropriately extract information. For example, in some cases, it is not possible to appropriately extract the information regarding the property of the target only by performing a comparison using the customer group generated based on the purchase history data of the store to be analyzed.

The present application has been made in view of the above, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program that appropriately extract information.

An information processing apparatus according to the present application extracts an input unit that acquires input information input by a user, a first keyword corresponding to a target, and a second keyword related to the property of the target from the input information, An extraction unit that extracts transition information indicating a temporal transition of the second keyword.

According to one aspect of the embodiment, there is an effect that information can be appropriately extracted.

FIG. 1 is a diagram illustrating an example of information processing according to the embodiment. FIG. 2 is a diagram illustrating an example of information processing according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the information processing system according to the embodiment. FIG. 4 is a diagram illustrating a configuration example of the information processing device according to the embodiment. FIG. 5 is a diagram illustrating an example of the company information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of the user information storage unit according to the embodiment. FIG. 7 is a diagram illustrating an example of the behavior information storage unit according to the embodiment. FIG. 8 is a diagram illustrating an example of a needs information storage unit according to the embodiment. FIG. 9 is a flowchart showing an example of information processing according to the embodiment. FIG. 10 is a diagram illustrating an example of information processing according to the embodiment. FIG. 11 is a diagram illustrating an example of information processing according to the embodiment. FIG. 12 is a flowchart showing an example of information processing according to the embodiment. FIG. 13 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device.

Hereinafter, modes (hereinafter, referred to as “embodiments”) for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited by this embodiment. Further, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicated description will be omitted.

(Embodiment)
[1. Information processing]
An example of information processing according to the embodiment will be described with reference to FIGS. 1 and 2. First, an example of extracting information about needs from user input information will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of information processing according to the embodiment. Further, in the example of FIG. 2, a case will be described in which transition information indicating the temporal transition of the second keyword regarding the property of the target is extracted, but details will be described later.

In FIG. 1, the information processing apparatus 100 extracts information about a user's needs for a predetermined target based on a keyword included in input information input by the user. The information processing apparatus 100, based on the first keyword corresponding to the target provided by the predetermined business operator included in the input information and the second keyword related to the property of the target, information regarding the needs for the target corresponding to the first keyword. To extract. The property mentioned here is a property (feature) of the target, and the property is a concept including a function of the target, specifications of the target, value evaluation of the target, and the like. In the example of FIG. 1, as the input information of the user, information about the needs for the target is extracted based on the keyword (hereinafter, also referred to as “search query” or “query”) used by the user for the search. In the example illustrated in FIG. 1, a search query used by the user for search is described as an example of the input information input by the user, but the input information is not limited to the search query, and the user may enter the social networking service (SNS: SNS: It may be various information such as information (posted information) posted in Social Networking Service).

Further, FIG. 1 shows a case where the information processing apparatus 100 provides information to a business operator. The enterprises referred to here may include various enterprises such as individuals (natural persons) and corporations as long as they are engaged in business. For example, the business operator is a business operator who designates a product or a product category for which information is requested to be provided. For example, the business operator may be a company that provides (sells) products or services. In the example of FIG. 1, the case where the business operator who specifies the product or the category of the product is the automobile manufacturer MA is shown. The product here may include services (services) provided by the business operator. In the following, products or services may be collectively referred to as “products”. In the example of FIG. 1, the information processing apparatus 100 provides target demand information that is information about needs for a target corresponding to information (hereinafter, also referred to as “target information”) indicating a product or a product category specified by a business. To provide to others. Further, in FIG. 1, the information processing apparatus 100 acquires the target information from the automobile manufacturer MA and provides the information on the target demand information corresponding to the acquired target information to the automobile manufacturer MA.

[Configuration of information processing system]
First, the information processing system 1 shown in FIGS. 1 and 3 will be described. As shown in FIG. 3, the information processing system 1 includes a terminal device 10, a business entity device 20, and an information processing device 100. The terminal device 10, the business entity device 20, and the information processing device 100 are connected via a predetermined network N so as to be communicable by wire or wirelessly. FIG. 3 is a diagram illustrating a configuration example of the information processing system according to the embodiment. Note that the information processing system 1 illustrated in FIG. 3 may include a plurality of terminal devices 10, a plurality of business entity devices 20, and a plurality of information processing devices 100.

The terminal device 10 is an information processing device used by a user. The terminal device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. In the example illustrated in FIG. 1, the terminal device 10 is a smartphone used by a user. In addition, below, the terminal device 10 may be described as a user. That is, in the following, the user can be read as the terminal device 10. Specifically, FIG. 1 illustrates a case where the terminal device 10 is a smartphone used by a user identified by a user ID “U1” (hereinafter, sometimes referred to as “user U1”).

The terminal device 10 may detect various sensor information by various sensors, not limited to the GPS sensor and the like. Further, the terminal device 10 has a function of an acceleration sensor, and detects and acquires acceleration information (sensor information) when the user moves. Further, the terminal device 10 may have various functions such as a temperature sensor and an atmospheric pressure sensor, and may be able to detect and acquire environmental information such as temperature and atmospheric pressure in which the user is placed. Further, the terminal device 10 may have various functions such as a heartbeat sensor and may be able to detect and acquire biometric information of the user. For example, the user who uses the terminal device 10 may acquire the context information of the user himself/herself by the terminal device 10 by wearing a wearable device that can communicate with the terminal device 10. For example, a user who uses the terminal device 10 wears a wristband-type wearable device that can communicate with the terminal device 10, so that the terminal device 10 acquires information about the user's own heartbeat (pulse) by the terminal device 10. It may be possible.

In the example illustrated in FIG. 1, the terminal device 10 will be described as the terminal devices 10-1 to 10-5 according to the user who uses the terminal device 10. For example, the terminal device 10-1 is the terminal device 10 used by the user (user U1) identified by the user ID “U1”. Further, for example, the terminal device 10-2 is the terminal device 10 used by (user U2) identified by the user ID “U2”. Further, in the following, the terminal devices 10-1 to 10-5 will be referred to as the terminal device 10 in the case of being described without particular distinction.

The information processing apparatus 100 extracts the first keyword corresponding to the target and the second keyword related to the property of the target from the input information input by the user to obtain the transition information indicating the temporal transition of the second keyword. This is an information processing device to be extracted. The information processing apparatus 100 extracts the second keyword whose input tends to increase with the passage of time, as the rising second keyword. The information processing apparatus 100 also acquires various types of behavior information of the user. For example, the information processing apparatus 100 acquires the behavior information of the user from the terminal device 10 of the user. For example, the information processing apparatus 100 acquires user behavior information from an external device such as a service providing device that provides a service to the user. The information processing apparatus 100 stores the acquired user behavior information in the storage unit 120 (see FIG. 4) such as the behavior information storage unit 123 (see FIG. 7).

The information processing apparatus 100 is an information processing apparatus that extracts information about needs for a target based on a first keyword included in input information input by a user and a second keyword included in the input information. For example, the information processing apparatus 100 extracts the needs for the target corresponding to the first keyword based on the relationship between the first keyword and the second keyword included in the input information input by the user.

In addition, the information processing apparatus 100 provides a search service that provides the terminal device 10 with a search result for a query (search query) acquired from the terminal device 10. In the example of FIG. 1, the information processing apparatus 100 provides predetermined information corresponding to the query as a search result to the terminal device 10 that is the transmission source of the query.

Although FIG. 1 shows the case where the information processing apparatus 100 provides the search service, the information processing apparatus 100 may not provide the search service when an external information processing apparatus provides the search service. In this case, the information processing apparatus 100 may acquire various information from an external information processing apparatus or the like that provides a search service and only provide the information to the business operator.

The business entity apparatus 20 is an information processing apparatus used by a business entity (company). In the example of FIG. 1, the business entity apparatus 20 is an information processing apparatus used by the administrator M1 of the automobile manufacturer MA who is the business entity. For example, the administrator M1 of the automobile manufacturer MA uses the business entity apparatus 20 to specify the keyword with respect to the information processing apparatus 100. Further, the business entity apparatus 20 is realized by, for example, a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or the like. FIG. 1 shows a case where the business entity apparatus 20 is a notebook PC.

First, the information processing apparatus 100 acquires a query from the terminal device 10-1 used by the user U1 (step S11-1). In the example of FIG. 1, the information processing apparatus 100 acquires the query “car X width” from the terminal device 10-1 at the date and time dt11-1. Then, the information processing device 100 provides the search result corresponding to the query “car X width” to the terminal device 10-1 (step S12-1). In addition, the information processing apparatus 100 stores, in the behavior information storage unit 123, behavior information indicating that the user U1 performed the search using the query “car X horizontal width” at the date and time dt11-1.

In addition, the information processing device 100 acquires a query from the terminal device 10-2 used by the user U2 (step S11-2). In the example of FIG. 1, the information processing apparatus 100 acquires the query “car Y fuel efficiency” from the terminal device 10-2 at the date and time dt11-2. Then, the information processing device 100 provides the search result corresponding to the query “car Y fuel efficiency” to the terminal device 10-2 (step S12-2). Further, the information processing apparatus 100 stores, in the behavior information storage unit 123, behavior information indicating that the user U2 has performed a search using the query “car Y fuel efficiency” at the date and time dt11-2.

The information processing apparatus 100 also acquires a query from the terminal device 10-3 used by the user U3 (step S11-3). In the example of FIG. 1, the information processing apparatus 100 acquires the query “smartphone battery” from the terminal device 10-3 at the date and time dt11-3. Then, the information processing device 100 provides the search result corresponding to the query "smartphone battery" to the terminal device 10-3 (step S12-3). In addition, the information processing apparatus 100 stores, in the behavior information storage unit 123, behavior information indicating that the user U3 performed the search using the query “smartphone battery” at the date and time dt11-3.

The information processing apparatus 100 also acquires a query from the terminal device 10-4 used by the user U4 (step S11-4). In the example of FIG. 1, the information processing device 100 acquires the query “weather” from the terminal device 10-4 at the date and time dt11-4. Then, the information processing apparatus 100 provides the search result corresponding to the query "weather" to the terminal device 10-4 (step S12-4). Further, the information processing apparatus 100 stores, in the activity information storage unit 123, activity information indicating that the user U4 has performed a search using the query “weather” at the date and time dt11-4.

First, the information processing device 100 acquires a query from the terminal device 10-5 used by the user U5 (step S11-5). In the example of FIG. 1, the information processing apparatus 100 acquires the query “vehicle X loading platform size” from the terminal device 10-5 at date and time dt11-5. Then, the information processing device 100 provides the terminal device 10-5 with the search result corresponding to the query “vehicle X loading space” (step S12-5). In addition, the information processing apparatus 100 stores, in the activity information storage unit 123, activity information indicating that the user U5 has performed a search using the query “vehicle X loading space” at date and time dt11-5.

Hereinafter, when the steps S11-1 to S11-5 will be described without making a distinction, they are collectively referred to as step S11. The search for each user is not limited to steps S11-1 to S11-5, and may be performed multiple times. Further, hereinafter, when the steps S12-1 to S12-5 are described without making a distinction, they are collectively referred to as step S12. Note that although FIG. 1 illustrates five users U1 to U5, the information processing apparatus 100 is not limited to the users U1 to U5, and a large number of users (for example, 1 million users or 10 million users) can search. Get the used query.

Further, the information processing device 100 acquires the target information from the business operator (step S13). In the example of FIG. 1, the information processing apparatus 100 acquires target information (designation information) designating the product “car X” from the business entity apparatus 20 used by the automobile manufacturer MA. For example, the manager M1 of the automobile maker MA transmits the target information designating the product “car X” to the information processing apparatus 100 by inputting the target information designating the product “car X” to the business entity apparatus 20. ..

Then, the information processing apparatus 100 extracts the needs for the target corresponding to the target information (step S14). For example, the information processing apparatus 100 extracts the needs for the target corresponding to the target information from the query used for the search. In the example of FIG. 1, the information processing device 100 extracts a query including a character string corresponding to the target information “car X”. For example, the information processing apparatus 100 extracts information based on the information regarding the query acquired in step S11. In the example of FIG. 1, the information processing apparatus 100 extracts the information about the query corresponding to the target information from the information about the query stored in the behavior information storage unit 123.

For example, the information processing apparatus 100 extracts the second keyword related to the property of the target “car X” used together with the first keyword “car X” corresponding to the target “car X”. For example, the information processing apparatus 100 may extract the second keyword used together with the first keyword “car X” based on the list information regarding the property of the target “car”. For example, the information processing apparatus 100 may have list information of various vehicle-related properties such as vehicle-related functions, specifications, and value evaluations. For example, the information processing apparatus 100 may have list information and the like including various keywords regarding price, size, evaluation, and the like as properties related to the vehicle. For example, the information processing apparatus 100 may have list information including keywords such as “width” and “fuel consumption” as properties related to the vehicle. For example, the information processing apparatus 100 may extract the second keyword by using the list information regarding the property of the target “car”.

In the example of FIG. 1, the information processing apparatus 100 extracts information indicating that the user U1 combined with the first keyword “car X” and used the second keyword “width” regarding the specification of the car. For example, the information processing apparatus 100 extracts, from the behavior information storage unit 123, information indicating that the user U1 has used the query “width” in combination with the query “car X”. In this way, the information processing apparatus 100 can extract the user's needs for the target “car X” by extracting the second keyword “width” used together with the first keyword “car X”. In addition, for example, the information processing apparatus 100 extracts the user information regarding the user U1 indicating that the user U1 is a male in his 20s from the user information storage unit 122 (see FIG. 6).

Further, in the example of FIG. 1, in the information processing apparatus 100, the user U5 combined the first keyword “car X” with the second keyword “cargo” and the second keyword “width” regarding the specifications of the car. Is extracted. For example, the information processing apparatus 100 extracts, from the behavior information storage unit 123, information indicating that the user U5 combined the query “car X” with the query “packing platform” and the query “area”. In this way, the information processing apparatus 100 extracts the user's needs for the target “car X” by extracting the second keyword “packing platform” and “width” used together with the first keyword “car X”. be able to. Further, for example, the information processing apparatus 100 extracts the user information regarding the user U5 indicating that the user U5 is a female in the thirties, from the user information storage unit 122 (see FIG. 6). In the above example, the example of extracting the second keyword relating to the specification of “car X” corresponding to the first keyword has been shown, but various information is extracted if it is the second keyword used together with the first keyword. May be. For example, the information processing apparatus 100 may extract the second keyword related to the function of “car X” corresponding to the first keyword. For example, the information processing apparatus 100 may extract the second keyword related to vehicle functions such as “energy saving” and “collision prevention”. Further, for example, the information processing device 100 may extract the second keyword related to the value evaluation of “car X” corresponding to the first keyword. For example, the information processing apparatus 100 may extract the second keyword related to the value evaluation of the car, such as “popular among young people”, “bargain”, or “stiff chair”. Note that the above is an example, and the information processing apparatus 100 may extract various keywords as the second keywords as long as they are keywords that can be used by the business operator who manufactures the target product for product development.

Then, the information processing apparatus 100 generates the target demand information based on the information regarding the needs of the target (step S15). In the example of FIG. 1, the information processing device 100 generates target demand information as shown in the needs information storage unit 124. For example, in the information processing apparatus 100, 65% of the keywords used as a query together with the product “car X” are “width”, 20% are “cargo width”, and 10% are “off-road”. Yes, the target demand information indicating that 5% is "comfort" is generated. Further, for example, the information processing apparatus 100 generates target demand information indicating that among the users who search for the product “car X”, the men are “75%” and the women are “25%”. Further, for example, the information processing apparatus 100 generates target demand information indicating that 20's among users who search for the product “car X” are “65%” or the like.

Then, the information processing apparatus 100 provides the business with the target demand information (step S16). In the example of FIG. 1, the information processing apparatus 100 provides the generated target demand information to the automobile manufacturer MA that is the transmission source of the target information. For example, in the information processing apparatus 100, 65% of the keywords used as a query together with the product “car X” are “width”, 20% are “cargo width”, and 10% are “off-road”. Yes, the target demand information indicating that 5% is "comfort" is provided to the automobile manufacturer MA. In addition, for example, the information processing apparatus 100 provides the automobile manufacturer MA with the target demand information indicating that among the users who search for the product “car X”, the men are “75%” and the women are “25%”. provide. In addition, in the example of FIG. 1, the information processing apparatus 100 provides the automobile manufacturer MA with the target demand information indicating that among the users who search for the product “car X”, those in their twenties are “65%” or the like.

[Use of information (product development, etc.)]
In this way, the information processing apparatus 100 provides the business with the target demand information indicating the needs for the target corresponding to the target information. Thus, the business operator who has been provided with the target demand information can develop or market a new product or the like for the product or the category of the product designated by the business operator based on the provided target demand information. For example, in the example of FIG. 1, the target demand information indicating that the first keyword corresponding to the target “car X” is input together with the second keyword “width” regarding the specification of the car X from the information processing apparatus 100 is high. The car manufacturer MA, which receives the provision of the above, can develop the product of the car X that attaches importance to the specification (property) of the "width". Further, for example, in the example of FIG. 1, the target demand information indicating that the first keyword corresponding to the target “car X” is input together with the second keyword “cargo size” related to the specification of the car X is high. The automobile manufacturer MA that receives the provision from the information processing apparatus 100 can develop the product of the vehicle X that emphasizes the breadth of the specification (property) of the "packing platform". The information processing apparatus 100 may generate the content regarding the target based on the information regarding the needs regarding the extracted target, which will be described later. In addition, for example, in the example of FIG. 1, the automobile manufacturer MA that receives the target demand information indicating that there are many users in their twenties among the users who searched for the target “car X” from the information processing apparatus 100. Makes it possible to develop a product for the car X targeting young users in their twenties. Further, for example, in the example of FIG. 1, the automobile manufacturer MA that receives the target demand information indicating that there are many male users among the users who searched for the target “car X” from the information processing apparatus 100 is , It becomes possible to develop the car X product targeting men. In addition, for example, in the example of FIG. 1, the automobile manufacturer MA that has been provided with the target demand information from the information processing apparatus 100 determines that the vehicle X that has both the tendency of the second keyword and the user attribute using the second keyword. It becomes possible to develop products. For example, in the example of FIG. 1, a female user receives information from the information processing apparatus 100 that indicates that the search rate using the first keyword “car X” and the second keyword “ride comfort” is high. The automobile manufacturer MA may provide information to the female user so as to appeal the ride comfort to the female user among the properties of the target “vehicle X”.

[1-1. Input information)
In the example of FIG. 1, the search query used for the search by the user is shown as an example of the input information, but the information processing apparatus 100 uses various information as long as it is the input information input by the user, and May be extracted. For example, the information processing apparatus 100 may extract needs regarding a target from character information communicated on a predetermined network.

For example, the information processing apparatus 100 may extract the needs regarding the target from the posted information posted by the user in the social networking service. For example, the information processing apparatus 100 may extract the needs related to the target from the posted information posted by the user in Twitter (registered trademark), Facebook (registered trademark), or the like. For example, the information processing apparatus 100 may target a sentence (character information) posted in Twitter by the user and extract needs regarding the target. In this case, for example, the information processing apparatus 100 uses the conventional techniques of various natural language processing techniques such as morphological analysis as appropriate to perform the first analysis based on the result of the semantic analysis of the input information (posted information) of the user. You may extract a keyword and a 2nd keyword.

For example, the information processing apparatus 100 may extract the needs relating to the target by using the input information input by the user in the message service as the target. For example, the information processing apparatus 100 may extract the needs regarding the target from the input information input by the user in a message service such as LINE (registered trademark). For example, the information processing apparatus 100 may extract the needs related to the target by using the input information input in the e-mail as the target. For example, the information processing apparatus 100 may target the information (search query) in the search service regarding the content (information) on the web and extract the needs regarding the target.

Further, for example, the information processing apparatus 100 may extract the needs regarding the target by using the input information regarding the question and the answer input by the user on the question site or the like. Note that the above is an example, and the information processing apparatus 100 may extract needs regarding the target from various input information. For example, the information processing apparatus 100 may extract the needs regarding the target based on the second keyword in which the co-occurrence frequency with the first keyword in the input information input by the user is equal to or higher than a predetermined threshold. For example, the information processing apparatus 100 extracts the needs regarding the target based on the second keyword in which the number of times that the first keyword co-occurs in the input information input by the user is equal to or greater than a predetermined threshold value (for example, 1000 times). Good.

[1-2. Content generation]
Note that the information processing apparatus 100 may generate the content regarding the target based on the extracted information regarding the needs regarding the target. For example, when the input information including the target “car X” includes the second keyword corresponding to the specification “width” that is the property of the target “car X” in a predetermined ratio or more, the information processing apparatus 100 determines that the vehicle The content about the car X may be generated such that the information of the specification “width” of X is easily visible to the user. In this case, for example, the information processing apparatus 100 may generate a Web page of the car X that displays the information of the specification “width” of the car X in a font larger than other information. Further, for example, the information processing apparatus 100 may generate a Web page of the car X that displays the information of the specification “width” of the car X in a color different from other information. Further, the information processing apparatus 100 may provide the user with the content regarding the vehicle X in which the information on the specification “width” of the vehicle X is more visible than other information.

[1-3. Target]
[1-3-1. First keyword]
In the example of FIG. 1, a case where needs are extracted for a specific product “Car X” provided by the automobile manufacturer MA is shown, but the target is not limited to the car but various products such as beverages and foods. It may be. For example, the information processing apparatus 100 may extract needs for a target according to various levels (hierarchies). For example, the information processing apparatus 100 may extract needs for categories of products provided by a predetermined business.

For example, the information processing apparatus 100 may extract the needs by setting the target as a “car”. In this case, the information processing apparatus 100 may set the first keyword to “car” and extract the needs for the target “car” based on the second keyword used together with the first keyword “car”.

Further, in this case, the information processing apparatus 100 may extract the needs for the target “car” based on the second keyword used together with the first keyword related to the target “car”. For example, the information processing apparatus 100 extracts the needs for the target “car” based on the second keyword used together with the first keyword such as “car X” or “car Y” related to the target “car”. You may.

For example, the information processing apparatus 100 may extract needs for a vehicle type (type) of a vehicle such as “SUV (Sport Utility Vehicle)” or “minivan”. For example, when a “minivan” is targeted, the information processing apparatus 100 sets the first keyword to “minivan”, and determines the needs for the target “minivan” based on the second keyword used together with the first keyword “minivan”. You may extract.

Further, in this case, the information processing apparatus 100 may extract the needs for the target “minivan” based on the second keyword used together with the first keyword related to the target “minivan”. For example, the information processing apparatus 100 needs the target “minivan” based on the second keyword used together with the first keyword corresponding to the product name (specific vehicle name) related to the target “minivan”. May be extracted. For example, the information processing apparatus 100 extracts the needs for the target “minivan” based on the second keyword used together with the first keyword such as “car B” or “car M” that is the target “minivan”. May be.

[1-3-2. Target setting]
Moreover, in the example of FIG. 1, the case where the information processing apparatus 100 uses the designation information for designating the target related to the business of the business operator is shown, but the information processing apparatus 100 may acquire the target information in various modes. Good. In this case, the information processing apparatus 100 may acquire the information on the business of the predetermined business by any means as long as the information on the business of the predetermined business can be acquired. For example, the information processing apparatus 100 may acquire information about a business of a predetermined business operator from a predetermined user of the predetermined business operator or the like. Further, the information processing apparatus 100 receives a designation from a predetermined user or the like of a predetermined business operator, and based on the designation from a predetermined user or the like of the predetermined business operator, stores information about the business of the predetermined business operator in the storage unit 120 ( (See FIG. 4).

For example, the information processing apparatus 100 may extract the information about the target provided by the predetermined business operator from the information about the business of the predetermined business operator. For example, the information processing apparatus 100 may extract the information about the target provided by the predetermined company from the information about the business of the predetermined company stored in the company information storage unit 121. For example, the information processing apparatus 100 uses the information about the business of the automobile maker MA stored in the company information storage unit 121 as “vehicle”, “vehicle X”, and “vehicle B” as the information about the target provided by the automobile maker MA. Various information such as “SUV” and “SUV” may be extracted.

Further, the information processing apparatus 100 may extract not only the information stored in the company information storage unit 121 but also the information regarding the target provided by the business operator from the content on the Internet regarding the business operator. For example, the information processing apparatus 100 may extract information about a target provided by a predetermined business operator from a site such as the homepage of the automobile manufacturer MA. In this case, for example, the information processing apparatus 100 uses a conventional technique such as various natural language processing techniques such as morphological analysis as appropriate, and based on the result of the semantic analysis of the homepage of the automobile manufacturer MA, the predetermined business operator. The information about the target provided by may be extracted. Further, the information processing apparatus 100 may generate list information regarding targets corresponding to each business operator based on the above information. In this case, the information processing apparatus 100 may use the generated list information to extract information regarding the target provided by the predetermined business operator.

Then, the information processing apparatus 100 may extract the information about the needs of the target based on the first keyword corresponding to the target extracted from the information about the business of the predetermined business operator and the second keyword related to the property of the target. Good.

In addition, for example, the information processing apparatus 100 may acquire target information for designating a target provided by a predetermined business operator from another business operator different from the predetermined business operator. For example, the information processing apparatus 100 may accept designation of target information corresponding to a target regarding a product provided by another business operator from one business operator. Note that this point will be described with reference to FIG.

[1-4. Billing)
Further, the information processing apparatus 100 may charge the information providing destination according to the provision of the target demand information. That is, the information processing apparatus 100 may provide the target demand information to the business operator who is charged for providing the information. For example, the information processing apparatus 100 may increase the amount and quality of the target demand information to be provided according to the increase in the amount of charge. For example, the information processing apparatus 100 sets the information provision of the first keyword having the highest ratio among the keywords used as the query together with the keyword corresponding to the target information to 50,000 yen, and the keyword corresponding to the target information as the query. The information provision of all the keywords used may be 100,000 yen. For example, the information processing apparatus 100 sets the information provision of the first keyword “width” having the highest proportion among the keywords used as a query together with the product “car X” to 50,000 yen, and queries with the product “car X”. The information provision of the entire keyword used as may be 100,000 yen.

For example, the information processing apparatus 100 provides the keyword information (second keyword) in the needs information storage unit 124 to the business operator who has charged the predetermined amount (first amount), and the predetermined amount (second amount). The user attribute information in the needs information storage unit 124 may be provided to the business operator who has only charged. In addition, for example, the information processing apparatus 100 may discount the charge amount (discount), that is, volume discount, to the business operator who desires to provide the target demand information of a predetermined amount or more. For example, the information processing apparatus 100 charges an amount of money (third amount of money) lower than the sum of the first amount of money and the second amount of money to a business operator who desires to provide target demand information of both keyword information and user attribute information. You may. Note that the above is an example, and the information processing apparatus 100 may determine the target demand information to be provided and the charge amount based on various information.

Further, for example, the information processing device 100 may provide the target demand information in a bid format. For example, the information processing apparatus 100 may provide the target demand information to the business operator determined based on the amount of money bid for the information provision. Details of this point will be described later.

[1-5. Target demand information]
The target demand information described above is an example, and the information processing apparatus 100 may provide various information as the target demand information. For example, the information processing apparatus 100 may provide, as the target demand information, information indicating the regional distribution of the users who have searched. In addition, for example, the information processing apparatus 100 acquires target information indicating a product of a business operator that competes with the business operator (hereinafter, also referred to as “competitive business operator”) or a category of the product, and target demand information regarding the competitive business operator. May be provided to the business operator. Details of this point will be described later.

[1-6. Provision mode]
In addition, for example, the information processing apparatus 100 may change the provision mode of the target demand information according to the business scale (sales or the like) of the business operator serving as the information provision destination. For example, the information processing apparatus 100 may charge the business operator each time information is provided when the business scale (sales or the like) is less than a predetermined threshold. In addition, for example, when the business scale (sales etc.) is equal to or larger than a predetermined threshold, the information processing apparatus 100 may provide information to the business operator on a flat rate basis. For example, when the business scale (sales, etc.) is equal to or greater than a predetermined threshold, the information processing apparatus 100 charges a charge amount set for each predetermined period and provides information within the predetermined period. May be. Further, for example, the information processing apparatus 100 may change the charge amount according to the business scale (sales etc.) of the business operator serving as the information provision destination. For example, when the business scale (sales, etc.) is less than a predetermined threshold value to the business operator, the information processing apparatus 100 provides the same information as in the case of providing information to the business operator whose business scale is equal to or higher than the predetermined threshold value. The billing amount may be lowered.

[1-7. Information processing]
Here, an example of information processing according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating an example of information processing according to the embodiment. FIG. 2 is a diagram showing information processing relating to extraction of transition information indicating temporal transition of the second keyword. In addition, FIG. 2 illustrates a case where a second keyword (also referred to as a “second rising keyword”) whose input tends to increase with time is extracted based on the temporal transition of the second keyword. In the example of FIG. 2, the information processing apparatus 100 extracts the second keyword whose co-occurrence with the first keyword satisfies a predetermined condition as the ascending second keyword. The co-occurrence here may take various forms as long as it is included in the same input information of the user, and it is used in combination as a search query in one search, or included in a sentence in one posting. It may be done. In addition, in the example of FIG. 2, a query is described as an example of the input information, but the input information is not limited to the query and may be various information as long as the information is input by the user, such as posted information.

The example of FIG. 2 illustrates a case where the information processing apparatus 100 targets the microwave oven MW and extracts the transition information and the rising second keyword. The information processing apparatus 100 may acquire information (designation information) designating the target “microwave MW” from a predetermined business operator. For example, the information processing device 100 may acquire the designation information from a business operator who provides the target “microwave MW” or another business operator different from the business operator. Further, the information processing device 100 may acquire the designation information from the administrator of the information processing device 100. Then, the information processing apparatus 100 may perform the extraction process according to the acquisition of the designation information. Note that the information processing apparatus 100 may determine the extraction target by various modes other than the above. For example, the information processing apparatus 100 may randomly determine the extraction target, or may use the designation information stored in the storage unit 120 (see FIG. 4) to determine the extraction target.

In the example of FIG. 2, the information processing apparatus 100 extracts the transition information NINF51 and the transition information NINF52 from the input information (action information) of the user. May be obtained. For example, the information processing apparatus 100 may acquire the transition information NINF51 and the transition information NINF52 from an external information processing apparatus, or may acquire the transition information NINF51 and the transition information NINF52 from the needs information storage unit 124 (see FIG. 8). May be.

First, the information processing apparatus 100 extracts the first input information group that is the input information group corresponding to the first time point (step S51). The information processing apparatus 100 extracts the first input information group from the behavior information storage unit 123. The information processing apparatus 100 extracts the input information corresponding to the first time point as the first input information. In the example of FIG. 2, the information processing apparatus 100 extracts the first input information group ININF1 including a plurality of first input information corresponding to the first time point.

For example, the information processing apparatus 100 extracts the first input information group corresponding to the first time point before the second time point described below. For example, when the second time point is the current time point (the start time point of the extraction process), the information processing apparatus 100 may set the time point (two months ago, two years ago, etc.) that is a predetermined period back from the second time point as the first time point. Good. For example, the information processing apparatus 100 may determine the first time point based on a preset period (also referred to as “elapsed period”) between the first time point and the second time point.

The information processing apparatus 100 may determine the elapsed period using the information indicating the elapsed period stored in the storage unit 120 (see FIG. 4) in association with the target product or service category. In the example of FIG. 2, the information processing apparatus 100 uses the information indicating the elapsed period (for example, 6 months or a year and a half) associated with the category “home appliances” corresponding to the microwave oven MW, and uses the elapsed period. To decide. The elapsed period is not limited to the category, and may be set for each target such as a product or service, or may be common to all targets.

For example, the information processing apparatus 100 extracts the first input information group that is the input information in a predetermined period (also referred to as “collection period”) before the first time point as the end point. For example, the collection period may be any period such as one month or one year. For example, the information processing apparatus 100 extracts the first input information group of the collection period with the first time point as the end point based on the preset collection period. For example, the information processing apparatus 100 extracts the first input information group based on the preset collection period.

The information processing apparatus 100 may determine the collection period using the information indicating the collection period stored in the storage unit 120 (see FIG. 4) in association with the target product or service category. In the example of FIG. 2, the information processing apparatus 100 uses the information indicating the collection period (for example, one month or three months) associated with the category “home appliances” corresponding to the microwave oven MW to determine the collection period. decide. The collection period is not limited to the category, and may be set for each target such as goods and services, or may be common to all targets.

The information processing apparatus 100 extracts, as the first input information group, the input information input from the behavior information storage unit 123 within the collection period (hereinafter, also referred to as “first period”) whose end point is the first time point. For example, the information processing apparatus 100 compares the time point when the action corresponding to the input information (action information) stored in the action information storage unit 123 is performed with the first period, and thus the time point when the action is performed. The input information included in the first period is extracted as the first input information. As a result, the information processing device 100 extracts the first input information group ININF1.

Then, the information processing apparatus 100 extracts the transition information from the first input information group ININF1 (step S52). For example, the information processing apparatus 100 extracts the input information including the first keyword indicating the target “microwave MW”. In the example of FIG. 2, the information processing apparatus 100 extracts a query including a character string corresponding to the target “microwave MW”. For example, the information processing apparatus 100 extracts information based on the first input information group ININF1. In the example of FIG. 2, the information processing apparatus 100 extracts the first input information corresponding to the target “microwave oven MW” from the first input information in the first input information group ININF1.

For example, the information processing apparatus 100 extracts the second keyword related to the property of the target “microwave MW” used together with the first keyword “microwave MW” corresponding to the target “microwave MW”. For example, the information processing apparatus 100 may extract the second keyword used together with the first keyword “microwave MW” based on the list information regarding the property of the target “microwave oven”. For example, the information processing apparatus 100 may have list information of various microwave-related properties such as functions and specifications related to the microwave oven, value evaluation, and the like. For example, the information processing apparatus 100 may have list information including various keywords related to price, size, evaluation, and the like as properties related to the microwave oven. For example, the information processing apparatus 100 may have list information including keywords such as “compact” and “high output” as a property related to the microwave oven. For example, the information processing apparatus 100 may extract the second keyword using the list information regarding the property of the target “microwave oven”.

In the example of FIG. 2, the information processing apparatus 100 displays information indicating that the user U11 or the user U12 combined the first keyword “microwave MW” and used the second keyword “compact” regarding the value evaluation of the microwave. Extract. For example, the information processing apparatus 100 extracts, from the first input information group ININF1, information indicating that the user U11 or the user U12 has used the query “compact” in combination with the query “microwave MW”. Further, for example, the information processing apparatus 100 may extract the user information regarding the user U11 and the user U12 from the user information storage unit 122 (see FIG. 6).

In the example of FIG. 2, the information processing apparatus 100 uses the second keyword “low price” related to the value evaluation of the microwave oven by combining the user U13 and the user U14 with the first keyword “microwave oven MW”. Extract the information shown. For example, the information processing apparatus 100 extracts, from the first input information group ININF1, information indicating that the user U13 or the user U14 combined the query “microwave MW” and used the query “low price”. Further, for example, the information processing apparatus 100 may extract the user information regarding the user U13 and the user U14 from the user information storage unit 122 (see FIG. 6).

In the above example, an example in which the second keyword relating to the value evaluation of the “microwave oven MW” corresponding to the first keyword is extracted has been described. However, if the second keyword is used together with the first keyword, various information can be obtained. You may extract. For example, the information processing apparatus 100 may extract the second keyword related to the function of the “microwave MW” corresponding to the first keyword. For example, the information processing apparatus 100 may extract the second keyword related to the function of the microwave oven such as “energy saving” or “steam”. Further, for example, the information processing apparatus 100 may extract the second keyword related to the specifications of the “microwave MW” corresponding to the first keyword. For example, the information processing apparatus 100 may extract the second keyword related to the specifications of the microwave oven, such as “high output” or “XXW”. Note that the above is an example, and the information processing apparatus 100 may extract various keywords as the second keywords.

As a result, the information processing apparatus 100 extracts the transition information from the first input information group ININF1. In the example of FIG. 2, the information processing device 100 extracts the transition information NINF51. For example, in the information processing apparatus 100, 15% of the keywords used as a query together with the target “microwave MW” are “compact”, 12% are “low price”, and 10% are “steam”. , 0.8% is the transition information NINF51 indicating that it is “sound”. Although not shown, the information processing apparatus 100 extracts the transition information NINF51 including information indicating that the total number of inputs using the first keyword “microwave oven MW” in the first period is 100,000. For example, the information processing apparatus 100 counts the number of times the first keyword “microwave oven MW” has been used to extract transition information NINF51 including information indicating that the total number of input times is 100,000.

That is, the information processing apparatus 100 is a transition indicating that the second keyword having the first highest proportion among the second keywords co-occurring with the first keyword “microwave MW” is “compact” having the proportion “15%”. The information NINF51 is extracted. The information processing apparatus 100 is the transition information indicating that the second keyword having the second highest ratio among the second keywords co-occurring with the first keyword “microwave MW” is “low price” having the ratio “12%”. Extract NINF51. In addition, the information processing apparatus 100 determines that, of the second keywords that co-occur with the first keyword “microwave MW”, the second keyword having the 100th position is “sound” having the ratio “0.8%”. The transition information NINF51 shown is extracted. Further, the information processing apparatus 100 extracts the transition information NINF51 indicating that the user who uses "compact" as the second keyword together with the first keyword "microwave MW" is the user U11 or the user U12. The information processing apparatus 100 may generate information as shown in the transition information NINF51 based on the extracted information.

First, the information processing apparatus 100 extracts the second input information group which is the input information group corresponding to the second time point (step S53). The information processing apparatus 100 extracts the second input information group from the behavior information storage unit 123. The information processing apparatus 100 extracts the input information corresponding to the second time point as the second input information. In the example of FIG. 2, the information processing apparatus 100 extracts the second input information group ININF2 including the plurality of second input information corresponding to the second time point. In the example of FIG. 2, the information processing apparatus 100 performs the extraction process with the current point (the start point of the extraction process) as the second point.

For example, the information processing apparatus 100 extracts the second input information group that is the input information in a predetermined period (collection period) before the second time point as the end point. For example, the information processing apparatus 100 extracts the second input information group in the collection period with the second time point as the end point based on the preset collection period.

The information processing apparatus 100 extracts, as the second input information group, the input information input from the behavior information storage unit 123 within the collection period (hereinafter, also referred to as “second period”) whose end point is the second time point. The length of the second period may be the same as that of the first period. For example, the information processing apparatus 100 compares the time point when the action corresponding to the input information (action information) stored in the action information storage unit 123 is performed with the second period, and the time point when the action is performed. The input information included in the second period is extracted as the second input information. As a result, the information processing apparatus 100 extracts the second input information group ININF2.

Then, the information processing apparatus 100 extracts the transition information from the second input information group ININF2 (step S54). For example, the information processing apparatus 100 extracts the input information including the first keyword indicating the target “microwave MW”. In the example of FIG. 2, the information processing apparatus 100 extracts a query including a character string corresponding to the target “microwave MW”. For example, the information processing apparatus 100 extracts information based on the second input information group ININF2. In the example of FIG. 2, the information processing apparatus 100 extracts the second input information corresponding to the target “microwave oven MW” from the second input information in the second input information group ININF2.

In the example of FIG. 2, the information processing apparatus 100 displays information indicating that the user U21 or the user U22 has used the second keyword “compact” regarding the value evaluation of the microwave oven in combination with the first keyword “microwave oven MW”. Extract. For example, the information processing apparatus 100 extracts, from the second input information group ININF2, information indicating that the user U21 or the user U22 has used the query “compact” in combination with the query “microwave MW”. Further, for example, the information processing apparatus 100 may extract the user information regarding the user U21 and the user U22 from the user information storage unit 122 (see FIG. 6).

Further, in the example of FIG. 2, the information processing apparatus 100 indicates that the user U23 or the user U24 has used the second keyword “sound” related to the function of the microwave oven in combination with the first keyword “microwave oven MW”. To extract. For example, the information processing apparatus 100 extracts, from the second input information group ININF2, information indicating that the user U23 or the user U24 used the query “sound” in combination with the query “microwave MW”. Further, for example, the information processing apparatus 100 may extract the user information regarding the user U23 and the user U24 from the user information storage unit 122 (see FIG. 6).

As a result, the information processing apparatus 100 extracts the transition information from the second input information group ININF2. In the example of FIG. 2, the information processing device 100 extracts the transition information NINF52. For example, in the information processing apparatus 100, 20% of the keywords used as a query together with the target “microwave MW” are “compact”, 15% are “sound”, and 11% are “low price”. , 6% is extracted as the transition information NINF52 indicating that it is "lightweight". Although not shown, the information processing apparatus 100 extracts the transition information NINF 52 including the information indicating that the total number of inputs using the first keyword “microwave oven MW” in the second period is 100,000.

That is, the information processing apparatus 100 is a transition indicating that the second keyword having the first highest proportion among the second keywords co-occurring with the first keyword “microwave MW” is “compact” having the proportion “20%”. The information NINF 52 is extracted. The information processing apparatus 100 is the transition information NINF52 indicating that the second keyword having the second highest ratio among the second keywords co-occurring with the first keyword “microwave MW” is “sound” having the ratio “15%”. To extract. Further, the information processing apparatus 100 extracts the transition information NINF52 indicating that the user who uses “compact” as the second keyword together with the first keyword “microwave MW” is the user U21 or the user U22. The information processing apparatus 100 may generate information such as the transition information NINF52 based on the extracted information. The information processing apparatus 100 may store the transition information NINF51 and the transition information NINF52 in the storage unit 120 (see FIG. 4).

Then, the information processing apparatus 100 extracts the rising second keyword (step S55). The information processing apparatus 100 extracts the second keyword whose input tends to increase with the passage of time, as the rising second keyword. For example, the information processing apparatus 100 extracts the second keyword having the tendency of increasing the number of inputs as time passes, as the rising second keyword. The information processing apparatus 100 extracts, as the ascending second keyword, the second keyword of the plurality of second keywords related to the property of the target, the second keyword satisfying a predetermined ratio of co-occurrence with the first keyword. The information processing apparatus 100 raises the second keyword in which the ratio corresponding to the first time point does not satisfy the predetermined condition and the ratio corresponding to the second time point after the first time point satisfies the predetermined condition. To extract.

For example, the information processing apparatus 100 extracts the predetermined condition as the ascending second keyword when the ratio rank is 10th or higher. In this case, the information processing apparatus 100 extracts, as the ascending second keyword, a second keyword whose ratio corresponding to the first time point is not 10th or higher but which is 10th or higher. ..

In the example of FIG. 2, the information processing apparatus 100, as shown in the rising second keyword information SINF51, has a rank corresponding to the first time point that is 100th below the tenth rank, and corresponds to the second time point. The second keyword “sound”, which is the second place of the tenth place or more, is extracted as the ascending second keyword. The information processing apparatus 100 may store the rising second keyword information SINF51 in the storage unit 120 (see FIG. 4).

Note that the information processing apparatus 100 may extract the rising second keyword by appropriately using various information such as the share, not limited to the ranking. For example, the information processing apparatus 100 may extract a predetermined condition as a rising second keyword when the ratio (share) is 10% or more. In this case, the information processing apparatus 100 extracts a second keyword having a ratio (share) corresponding to the first time point of less than 10% and a ratio corresponding to the second time point of 10% or more, as an ascending second keyword. To do. In the example of FIG. 2, in the information processing apparatus 100, the ratio (share) corresponding to the first time point is 0.8%, which is less than 10%, and the ratio (share) corresponding to the second time point is 15%, which is 10% or more. The second keyword “sound”, which is %, is extracted as the rising second keyword.

Then, the information processing apparatus 100 selects, as an innovator, the user who has input the input information including the ascending second keyword (step S56). The information processing apparatus 100 selects, as the innovator, the user who has input the input information including the ascending second keyword when the score of the ascending second keyword related to the co-occurrence with the first keyword is equal to or less than the predetermined threshold. For example, the information processing apparatus 100 selects the user who has used the ascending second keyword as an innovator when the ascending second keyword is rarely used.

In the example of FIG. 2, the information processing apparatus 100 sets the rank of the ratio as a score, and when the rank of the ratio is below the threshold “50th place”, the user who has input the input information including the rising second keyword is set as the innovator. Select. In this case, the information processing apparatus 100 determines, as the innovator, the input user who has input the input information including the rising second keyword “sound” at the first time point when the rank of the ratio is 100th below the threshold “50th”. Select. Specifically, as shown in the innovator information IVINF51, the information processing apparatus 100 selects the users U100 and U101 who have input the input information including the rising second keyword “sound” at the first time point as the innovator. The information processing apparatus 100 may store the innovator information IVINF51 in the storage unit 120 (see FIG. 4).

The information processing apparatus 100 may provide the rising second keyword information SINF51 to a business entity that requests information regarding the rising second keyword information SINF51. In addition, the information processing device 100 may provide the innovator information IVINF51 to a business that requests information regarding the innovator information IVINF51. Moreover, the information processing apparatus 100 may provide the rising second keyword information SINF51 and the innovator information IVINF51 to a business operator who provides a microwave oven.

Further, the information processing device 100 may generate the graph information SG11 regarding the rising second keyword. The information processing apparatus 100 may generate the graph information SG11 indicating a transition indicating a temporal transition of the rising second keyword “sound” among the second keywords of the first keyword “microwave MW”. Then, the information processing apparatus 100 may provide the graph information SG11 to a predetermined business operator. For example, the information processing apparatus 100 may provide the graph information SG11 to a business operator who provides a microwave oven.

In the example of FIG. 2, the information processing apparatus 100 extracts transition information indicating a temporal transition of the second keyword corresponding to the property of the target “microwave MW”. As a result, the information processing device 100 can appropriately extract information. In addition, the information processing apparatus 100 extracts the rising second keyword from the second keywords corresponding to the property of the target “microwave MW”. As a result, the information processing apparatus 100 can extract the information indicating the nature that the needs (demand) are increasing due to the nature of the target. Therefore, the information processing device 100 can appropriately extract the information.

In addition, the information processing apparatus 100 selects a user who has input the input information including the rising second keyword as an innovator, so that the user (innovator) who has noticed in advance the property of which the need (demand) is high in the target property (innovator). ) Can be specified and extracted (selected). Therefore, the information processing device 100 can appropriately extract the information. As a result, the information processing apparatus 100 identifies a person (user) who has been demanding properties such as functions of well-sold products and services from an early stage, and uses the user as an innovator for trendsetters or those who anticipate needs. Can be selected.

[1-7-1. Information extraction]
In the example of FIG. 2, the case where the information processing apparatus 100 extracts the input information corresponding to each of the first time point and the second time point and extracts the transition information and the rising second keyword based on the information is shown. The information processing device 100 may extract information in various modes. For example, the information processing apparatus 100 may extract the input information corresponding to the target from the behavior information storage unit 123, and extract the transition information and the rising second keyword based on the extracted information. For example, the information processing apparatus 100 may extract input information including the target “microwave MW” from the behavior information storage unit 123, and extract transition information or a rising second keyword based on the extracted information.

Further, in the example of FIG. 2, the example in which the rising second keyword “sound” is extracted based on the relative relationship with the second keyword regarding other properties of the target “microwave MW” has been shown. The device 100 may extract the ascending second keyword based on the temporal transition of the number of times of inputting one second keyword. For example, the information processing apparatus 100 may extract each second keyword as a rising second keyword based on the transition information indicating the temporal transition of each second keyword. For example, the information processing apparatus 100 may extract the ascending second keyword based on the comparison between the number of inputs of the one second keyword at the first time point and the number of inputs of the one second keyword at the second time point. Good. In the information processing apparatus 100, the rate of increase in the number of times the second keyword is input at the second time point with respect to the number of times the second keyword is input at the first time point is equal to or greater than a predetermined threshold value (for example, 50% increase). , The second keyword may be extracted as the ascending second keyword. For example, in the information processing apparatus 100, the number of inputs of the one second keyword at the first time point is the first threshold value (for example, 1000 times), and the number of inputs of the one second keyword at the second time point is equal to or more than the first threshold value. If it is equal to or more than the second threshold value of (for example, 5000 times), one second keyword may be extracted as a rising second keyword. Note that the above is an example, and the information processing apparatus 100 may extract the rising second keyword by appropriately using various information.

[1-7-2. Innovator]
The information processing apparatus 100 may provide various services regarding the selected innovator. For example, the information processing apparatus 100 may predict the next hit from an action such as searching for an innovator. For example, the information processing apparatus 100 may collect behavior information such as a search for an innovator and predict the next hit from the behavior of the innovator. For example, the information processing apparatus 100 may acquire action information such as search for an innovator by giving a predetermined reward to the innovator, and predict the next hit from the action of the innovator.

[1-7-3. Other]
The information processing apparatus 100 may extract the transition information of various targets and the rising second keyword. The information processing apparatus 100 may extract the transition information and the rising second keyword according to various modes. The information processing device 100 may extract the transition information and the rising second keyword according to the designation of the administrator of the information processing device 100. The information processing apparatus 100 may extract the transition information and the rising second keyword for the automatically extracted target. The information processing apparatus 100 may extract the transition information and the rising second keyword for the target randomly extracted from the storage unit 120 (see FIG. 4). For example, the information processing apparatus 100 may extract the transition information and the rising second keyword in response to a request from a predetermined business operator. For example, the information processing apparatus 100 may extract the transition information of the microwave oven MW and the rising second keyword in response to a request for the transition information and the rising second keyword of the enterprise that provides the microwave oven MW. Then, the information processing apparatus 100 may provide the service regarding the transition information and the rising second keyword to a predetermined business operator. For example, the information processing apparatus 100 may transmit the transition information and the rising second keyword to the business operator who provides the microwave oven MW. Note that the information processing apparatus 100 extracts the transition information of the target “microwave MW” and the rising second keyword in response to a request from a business operator (electrical device maker MX) other than the business operator providing the microwave MW. You may. The information processing apparatus 100 may extract the transition information and the rising second keyword of the target “microwave MW” in response to a request from an electric appliance manufacturer or the like, which is a competitor of a business operator who provides the microwave MW. For example, the information processing apparatus 100 may provide the electric machine maker MX with the transition information of the target “microwave oven MW” and the second keyword for increase.

[1-8. Information processing flow]
Here, the procedure of information processing by the information processing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 12 is a flowchart showing an example of information processing according to the embodiment.

As illustrated in FIG. 12, the information processing apparatus 100 acquires the input information input by the user (step S501). Further, the information processing apparatus 100 extracts transition information indicating a temporal transition of the second keyword by extracting the first keyword corresponding to the target and the second keyword related to the property of the target from the input information. (Step S502). Then, the information processing apparatus 100 extracts the second keyword having the tendency of increasing the number of times of input as the time increases, as the rising second keyword (step S503).

[2. Configuration of information processing device]
Next, the configuration of the information processing device 100 according to the embodiment will be described with reference to FIG. FIG. 4 is a diagram illustrating a configuration example of the information processing apparatus according to the embodiment. As shown in FIG. 4, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The information processing apparatus 100 includes an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator of the information processing apparatus 100, and a display unit (for example, a liquid crystal display) for displaying various information. You may have.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 110 is connected to a network by wire or wirelessly, and transmits/receives information to/from the terminal device 10 or the business entity device 20 included in the information processing system 1, for example.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. As illustrated in FIG. 4, the storage unit 120 according to the embodiment includes a company information storage unit 121, a user information storage unit 122, a behavior information storage unit 123, and a needs information storage unit 124.

(Company information storage unit 121)
The company information storage unit 121 according to the embodiment stores various kinds of information regarding products. FIG. 5 is a diagram illustrating an example of the company information storage unit according to the embodiment. The company information storage unit 121 shown in FIG. 5 includes items such as “company ID”, “company name”, “business type”, “competitor company”, “product”, “category”, and “competitive product”.

The “company ID” indicates identification information for identifying the company. The “company name” indicates the name of the company identified by the corresponding company ID. The “business type” indicates the business type of the company identified by the corresponding company ID. The “competitor” indicates a competitor of the company identified by the corresponding company ID. For example, the “competitor company” may be a company in the same industry as the company identified by the corresponding company ID, or may be a company that provides products similar to the company identified by the corresponding company ID. Good. Further, for example, the “competitor company” may be designated by the company identified by the corresponding company ID.

"Product" indicates a product provided by the company identified by the corresponding company ID. “Category” indicates the category of the corresponding product. In addition, “competition product” indicates a competition for the corresponding product. For example, the “competitive product” may be a product in a category similar to the corresponding product, or may be a company that provides products and services of the same type as the corresponding product. Further, for example, the “competitive product” may be designated by the company identified by the corresponding company ID.

For example, in the example shown in FIG. 5, the company (company EP1) identified by the company ID “EP1” has a company name of “automobile manufacturer MA” and a business type of “automobile manufacturing/sales”. Further, it indicates that the competitor of the automobile manufacturer MA is the company (maker MR) identified by the company ID “EP11”. In addition, the products provided by the automobile manufacturer MA are “car X”, “car B”, and “car C”. Further, the category of “car X” is “SUV”, the category of “car B” is “minivan”, and the category of “car C” is “light vehicle”. Also, the competing product of “car X” is car Y.

Note that the company information storage unit 121 is not limited to the above, and may store various information according to the purpose. For example, the company information storage unit 121 may store information about the business location such as the location of the company, the number of employees of the company, and sales.

(User information storage unit 122)
The user information storage unit 122 according to the embodiment stores various information regarding user attributes. For example, the user information storage unit 122 stores user attribute information. FIG. 6 is a diagram illustrating an example of the user information storage unit according to the embodiment. The user information storage unit 122 illustrated in FIG. 6 includes items such as “user ID”, “age”, “gender”, “home”, “work place”, and “interest”.

“User ID” indicates identification information for identifying a user. For example, the user identified by the user ID “U1” corresponds to the user U1 shown in the example of FIG. The "age" indicates the age of the user identified by the user ID. The “age” may be a specific age of the user identified by the user ID, such as 35 years old. Further, “sex” indicates the sex of the user identified by the user ID.

Further, "home" indicates the position information of the home of the user identified by the user ID. In the example shown in FIG. 6, “home” is an abstract code such as “LC11”, but it may be information indicating latitude and longitude. Further, for example, “home” may be a region name or an address.

Further, "work location" indicates position information of the work location of the user identified by the user ID. Note that, in the example shown in FIG. 6, the “work place” shows an abstract code such as “LC12”, but it may be information indicating latitude and longitude. Further, for example, the “work place” may be a region name or an address.

The "interest" indicates the interest of the user identified by the user ID. That is, “interest” indicates a target of high interest to the user identified by the user ID. In the example shown in FIG. 6, the “interest” is shown one for each user, but it may be plural.

For example, in the example illustrated in FIG. 6, the age of the user identified by the user ID “U1” is “20s”, and the gender is “male”. Further, for example, the user identified by the user ID “U1” indicates that his home is “LC11”. Further, for example, the user identified by the user ID “U1” indicates that the work place is “LC12”. Further, for example, the user identified by the user ID “U1” indicates that he is interested in “sports”.

The user information storage unit 122 is not limited to the above, and may store various information according to the purpose. For example, the user information storage unit 122 may store information regarding the demographic attribute of the user and information regarding the psychographic attribute. For example, the user information storage unit 122 may store information such as name, family structure, income, interest, and lifestyle.

(Behavior information storage unit 123)
The behavior information storage unit 123 according to the embodiment stores various information regarding the behavior of the user. FIG. 7 is a diagram illustrating an example of the behavior information storage unit according to the embodiment. For example, the behavior information storage unit 123 stores various behavior information including a search performed using the terminal device 10 of each user. The action information storage unit 123 illustrated in FIG. 7 includes items such as “action ID”, “user ID”, “date and time”, and “query information”. The "query information" includes items such as "query 1", "query 2", "query 3", and the like. The "query information" is not limited to "query 1" to "query 3", and may include items such as "query 4" and "query 5" as many as the number of combinations.

The "action ID" indicates information that identifies the action of the user. “User ID” indicates identification information for identifying a user. For example, the user identified by the user ID “U1” corresponds to the user U1 shown in the example of FIG. “Date and time” indicates the date and time when the action of the corresponding user was performed. The “date and time” is illustrated in an abstract manner such as “dt11-1”, but a specific date and time such as “23:31:52 on April 11, 2017” may be stored. In addition, “query information” indicates information regarding the query used in the corresponding search. “Query 1” and “query 2” indicate the queries used in the corresponding search. For example, "query 1" corresponds to the first query, "query 2" corresponds to the second query, and "query 3" corresponds to the third query.

For example, in the example illustrated in FIG. 7, the user (user U1) identified by the user ID “U1” indicates that the action AC11 is performed. Specifically, in the example illustrated in FIG. 7, the user U1 indicates that the search (action AC11) using the first query “car X” and the second query “width” is performed at the date and time dt11-1. Further, for example, in the example illustrated in FIG. 7, the user (user U2) identified by the user ID “U2” indicates that the behavior AC12 is performed. Specifically, in the example illustrated in FIG. 7, the user U2 indicates that the search (action AC12) using the first query “car Y” and the second query “fuel consumption” is performed at the date and time dt11-2.

The behavior information storage unit 123 is not limited to the above, and may store various information according to the purpose. Further, FIG. 7 shows the case where the behavior information is stored in the behavior information storage unit 123 for each user ID, but the behavior information is not limited to the order of date and time, and may be stored for each user ID, for example. Further, in FIG. 7, the behavior information storage unit 123 illustrates the information regarding the query used by the user, but the behavior information storage unit 123 stores the input information input by the user, such as the posted information posted by the user. May be done.

In addition, the action information storage unit 123 may store various action information performed by the user. For example, the behavior information storage unit 123 stores behavior information of various types such as browsing of user contents and purchase of products or services (products etc.). For example, when the user's action is browsing of content, the action information storage unit 123 stores information indicating the content browsed by the user in association with the action ID. For example, when the user's action is the purchase of a product or the like, the action information storage unit 123 stores information indicating the product or the like purchased by the user in association with the action ID. For example, the behavior information storage unit 123 stores information indicating the type of behavior of the user in association with each behavior. For example, in the behavior information storage unit 123, type information indicating which type the user's behavior is among various types such as “search”, “post”, “browsing”, and “purchase” is stored. It is stored in association with the ID.

(Needs information storage unit 124)
The needs information storage unit 124 according to the embodiment stores various kinds of information regarding the index. FIG. 8 is a diagram illustrating an example of a needs information storage unit according to the embodiment. The needs information storage unit 124 shown in FIG. 8 has items such as “target”, “keyword information”, and “user attribute information”.

"Target" indicates a target for which the target demand information is generated. The “target” is not limited to a specific product name or service name, but may be a product or service category (beverage, fashion, travel, etc.).

The “keyword information” indicates information about a keyword (query) used in a search for a corresponding target. For example, “keyword information” indicates information about the second keyword used together with the first keyword corresponding to the target. The “keyword information” includes items such as “keyword” and “ratio”. The “keyword” indicates a query used with the target. Further, the “ratio” indicates the ratio of the corresponding keyword used together with the keyword corresponding to the target.

The “user attribute information” indicates the target demand information of the attribute of the user who inputs the input information regarding the corresponding target. For example, “user attribute information” indicates the target demand information of the attribute of the user who performed the search or the posting using the query regarding the corresponding target. The “user attribute information” includes items such as “category”, “attribute”, and “ratio”. “Category” indicates a category for classifying users. The “attribute” indicates the type (attribute) in the corresponding category. Further, the “ratio” indicates the ratio of the user having the corresponding attribute performing the search using the keyword corresponding to the corresponding target.

In the example of FIG. 8, 65% of the keywords used as a query together with the product “car X” are “width”, 20% are “cargo width”, and 10% are “off-road”, 5% indicates that it is "riding comfort". Further, in the example of FIG. 8, among the users who search for the product “car X”, men are “75%” and women are “25%”. Further, the example of FIG. 8 indicates that among the users who search for the product “car X”, those in their twenties are “65%” or the like.

Further, the need information storage unit 124 is not limited to the above, and may store various information according to the purpose. For example, the needs information storage unit 124 may store information regarding the date and time when the target demand information was generated and the period during which the information used for generation was collected.

(Control unit 130)
Returning to the description of FIG. 4, the control unit 130 is a controller, and is stored in a storage device inside the information processing device 100 by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). It is realized by executing various programs (corresponding to an example of an information processing program) that are stored in the RAM as a work area. The control unit 130 is a controller, and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As illustrated in FIG. 4, the control unit 130 includes an acquisition unit 131, an extraction unit 132, a generation unit 133, a selection unit 134, and a provision unit 135, and has the information processing function and operation described below. Realize or execute.

(Acquisition unit 131)
The acquisition unit 131 acquires various kinds of information. For example, the acquisition unit 131 acquires various types of information from the company information storage unit 121, the user information storage unit 122, the behavior information storage unit 123, and the needs information storage unit 124. For example, the acquisition unit 131 acquires various types of information from the terminal device 10 and the business entity device 20. The acquisition unit 131 acquires the information extracted by the extraction unit 132. The acquisition unit 131 acquires information regarding the needs of the target extracted by the extraction unit 132. The acquisition unit 131 acquires the information generated by the generation unit 133.

The acquisition unit 131 acquires input information input by the user. For example, the acquisition unit 131 acquires input information including the search query used by the user for the search. For example, the acquisition unit 131 acquires input information including posted information posted by a user in a predetermined service. For example, the acquisition unit 131 acquires target information specifying a target from a predetermined business operator. For example, the acquisition unit 131 acquires target information specifying a target from another business operator different from the predetermined business operator. For example, the acquisition unit 131 acquires information about the business of a predetermined business operator.

For example, the acquisition unit 131 acquires the query used for the search specified by the business operator. Further, for example, the acquisition unit 131 acquires the keyword specified by the business operator as the target information. Further, for example, the acquisition unit 131 acquires, as the target information, a category based on the keyword specified by the business operator. For example, when the keyword specified by the business operator matches one category, the acquisition unit 131 acquires the specified keyword as the category specification. Further, for example, the acquisition unit 131 acquires target information regarding the query specified by the business operator.

In the example of FIG. 1, the acquisition unit 131 acquires target information indicating a product or a product category from the business entity apparatus 20. In the example of FIG. 1, the information processing apparatus 100 acquires target information specifying the keyword “car X” from the business entity apparatus 20 of the automobile manufacturer MA.

Further, the acquisition unit 131 acquires various kinds of information from an external information processing device. For example, the acquisition unit 131 acquires the query used by the user for the search from the behavior information storage unit 123. For example, the acquisition unit 131 acquires the query used by the user for the search from the terminal device 10.

In the example of FIG. 1, the acquisition unit 131 acquires the query “car X width” from the terminal device 10-1. Further, in the example of FIG. 1, the acquisition unit 131 acquires the query “car Y fuel efficiency” from the terminal device 10-2. Further, in the example of FIG. 1, the acquisition unit 131 acquires the query “smartphone battery” from the terminal device 10-3. Further, in the example of FIG. 1, the acquisition unit 131 acquires the query “weather” from the terminal device 10-4. In addition, in the example of FIG. 1, the acquisition unit 131 acquires the query “vehicle X loading platform size” from the terminal device 10-5.

(Extractor 132)
The extraction unit 132 extracts various information. For example, the extraction unit 132 extracts various information based on the information stored in the storage unit 120. For example, the extraction unit 132 extracts various information based on the information acquired from the terminal device 10. The extraction unit 132 determines various information. For example, the extraction unit 132 determines various information based on the information stored in the storage unit 120. For example, the extraction unit 132 determines various information based on the information acquired from the terminal device 10.

The extraction unit 132 extracts, from the input information, the first keyword corresponding to the target and the second keyword related to the property of the target to extract transition information indicating the temporal transition of the second keyword. The extraction unit 132 extracts a second keyword whose input tends to increase with the passage of time, as an upward second keyword. The extraction unit 132 extracts a second keyword in which the number of times of input tends to increase with the passage of time, as a rising second keyword.

The extraction unit 132 extracts the second keyword whose co-occurrence with the first keyword satisfies a predetermined condition as the ascending second keyword. The extraction unit 132 extracts, as the ascending second keyword, a second keyword of the plurality of second keywords related to the property of the target, in which the ratio of co-occurrence with the first keyword satisfies a predetermined condition.

The extraction unit 132 sets, as the second keyword to be increased, the second keyword in which the ratio corresponding to the first time point does not satisfy the predetermined condition and the ratio corresponding to the second time point after the first time point satisfies the predetermined condition. Extract. The extraction unit 132 extracts the information regarding the needs of the target by extracting the first keyword and the second keyword from the input information.

The extraction unit 132 is the first keyword included in the input information, which is the first keyword corresponding to the target provided by the predetermined business operator, and the second keyword included in the input information, which is the first keyword related to the property of the target. Based on the two keywords, information regarding the needs for the target is extracted. For example, the extraction unit 132 extracts information about needs for the target based on the first keyword and the second keyword corresponding to the target, which is the product or the category of the product provided by the predetermined business operator.

For example, the extraction unit 132 extracts information regarding needs for the target function based on the second keyword regarding the target function. For example, the extraction unit 132 extracts information regarding needs for the target specifications based on the second keyword regarding the target specifications. For example, the extraction unit 132 extracts information regarding the needs for the target specifications based on the second keyword regarding the value evaluation of the target.

For example, the extraction unit 132 extracts information regarding needs for a target designated by a predetermined business operator. For example, the extraction unit 132 extracts information regarding needs for a target designated by another business operator. For example, the extraction unit 132 extracts the information about the target from the information about the business of the predetermined business operator, and based on the first keyword corresponding to the extracted target and the second keyword related to the property of the target, the need for the target. Extract information.

For example, the extraction unit 132 extracts information based on the information regarding the query acquired by the acquisition unit 131. In the example of FIG. 1, the extraction unit 132 extracts information about the query corresponding to the target information from among the information about the query stored in the behavior information storage unit 123.

In the example of FIG. 1, the extraction unit 132 extracts, from the behavior information storage unit 123, information indicating that the user U1 combined the query “car X” with the query “width”. Further, in the example of FIG. 1, the extraction unit 132 extracts, from the user information storage unit 122 (see FIG. 6), user information regarding the user U1 indicating that the user U1 is a male in his 20s.

In the example of FIG. 1, the extraction unit 132 extracts, from the behavior information storage unit 123, information indicating that the user U5 has used the query “cargo” and the query “size” in combination with the query “car X”. Further, in the example of FIG. 1, the extraction unit 132 extracts, from the user information storage unit 122 (see FIG. 6), user information regarding the user U5 indicating that the user U5 is a woman in her thirties.

In the example of FIG. 2, the extraction unit 132 extracts, from the behavior information storage unit 123, the first input information group from the input information input within the collection period (first period) having the first time point as the end point. The extraction unit 132 compares the time when the action corresponding to the input information (action information) stored in the action information storage unit 123 is performed with the first period, and thus the time when the action is performed is the first time. The input information included in the period is extracted as the first input information. The extraction unit 132 extracts the first input information group ININF1.

The extraction unit 132 extracts transition information from the first input information group ININF1. For example, the extraction unit 132 extracts the input information including the first keyword indicating the target “microwave MW”. The extraction unit 132 extracts a query including a character string corresponding to the target “microwave MW”. The extraction unit 132 extracts information based on the first input information group ININF1. The extraction unit 132 extracts the first input information corresponding to the target “microwave oven MW” from the first input information in the first input information group ININF1.

The extraction unit 132 extracts transition information from the first input information group ININF1. The extraction unit 132 extracts the transition information NINF51. Of the keywords used as a query together with the target “microwave MW”, the extraction unit 132 determines that 15% is “compact”, 12% is “low price”, 10% is “steam”, and 0. The transition information NINF51 indicating that 8% is "sound" is extracted.

The extraction unit 132 extracts, from the behavior information storage unit 123, the second input information group, from the input information input within the collection period (second period) having the second time point as the end point. The length of the second period may be the same as that of the first period. The extraction unit 132 compares the time point at which the action corresponding to the input information (action information) stored in the action information storage unit 123 is performed with the second period, so that the time point at which the action is performed is the second time point. The input information included in the period is extracted as the second input information. The extraction unit 132 extracts the second input information group ININF2.

The extraction unit 132 extracts transition information from the second input information group ININF2. The extraction unit 132 extracts the input information including the first keyword indicating the target “microwave MW”. The extraction unit 132 extracts a query including a character string corresponding to the target “microwave MW”. The extraction unit 132 extracts information based on the second input information group ININF2. The extraction unit 132 extracts the second input information corresponding to the target “microwave oven MW” from the second input information in the second input information group ININF2.

The extraction unit 132 extracts transition information from the second input information group ININF2. The extraction unit 132 extracts the transition information NINF52. Of the keywords used as a query together with the target “microwave MW”, the extraction unit 132 has 20% “compact”, 15% “sound”, 11% “low price”, and 6%. The transition information NINF52 indicating that is "lightweight" is extracted.

The extraction unit 132 extracts the rising second keyword. The extraction unit 132 extracts, as the ascending second keyword, a second keyword of the plurality of second keywords related to the property of the target, in which the ratio of co-occurrence with the first keyword satisfies a predetermined condition. The extraction unit 132 sets, as the second keyword to be increased, the second keyword in which the ratio corresponding to the first time point does not satisfy the predetermined condition and the ratio corresponding to the second time point after the first time point satisfies the predetermined condition. Extract.

The extraction unit 132 extracts the predetermined condition as the ascending second keyword assuming that the rank of the ratio is 10th or higher. The extraction unit 132 extracts, as the ascending second keyword, a second keyword whose ratio corresponding to the first time point is not 10th or higher, but whose ratio corresponding to the second timepoint is 10th or higher. The extraction unit 132, as shown in the rising second keyword information SINF51, has a rank corresponding to the first time point of 100th, which is lower than the 10th rank, and a proportion corresponding to the second time point is the 10th rank or higher, and is ranked second. The second keyword “sound” that is “A” is extracted as the ascending second keyword.

(Generator 133)
The generation unit 133 generates various information. For example, the generation unit 133 generates the target demand information based on the information regarding the query extracted by the extraction unit 132. The generation unit 133 generates the content regarding the target based on the information regarding the needs for the target extracted by the extraction unit 132.

In the example of FIG. 1, the generation unit 133 determines that 65% of the keywords used as a query together with the product “car X” are “width”, 20% are “cargo width”, and 10% are “off”. The target demand information indicating that “road” and 5% is “comfort” is generated. Further, in the example of FIG. 1, the generation unit 133 generates target demand information indicating that among the users who search for the product “car X”, the men are “75%” and the women are “25%”. To do. In addition, in the example of FIG. 1, the generation unit 133 is a target demand indicating that among the users who search for the product “car X”, the twenties are “65%” and the thirties are “20%”. Generate information.

In the example of FIG. 2, the generation unit 133 generates the graph information SG11 regarding the rising second keyword. The generation unit 133 generates graph information SG11 indicating a transition indicating a temporal transition of the rising second keyword “sound” among the second keywords of the first keyword “microwave MW”.

(Selection unit 134)
The selection unit 134 selects various information. The selection unit 134 selects various information. The selection unit 134 selects various information based on the various information stored in the storage unit 120. The selection unit 134 selects various information based on the various information stored in the storage unit 120. The selection unit 134 selects various types of information based on the various types of information acquired by the acquisition unit 131. The selection unit 134 selects various information based on the various information extracted by the extraction unit 132. The selection unit 134 selects various information based on the various information generated by the generation unit 133. The selection unit 134 selects various information based on the various information acquired by the acquisition unit 131. The selection unit 134 selects various information based on the various information extracted by the extraction unit 132. The selection unit 134 selects various information based on the various information generated by the generation unit 133. The selection unit 134 may predict various kinds of information.

The selection unit 134 selects the user who has input the input information including the second keyword of rise as an innovator. The selecting unit 134 selects, as an innovator, the user who has input the input information including the second keyword of rise when the score of the second keyword of rise related to the co-occurrence with the first keyword is equal to or less than a predetermined threshold.

In the example of FIG. 2, the selection unit 134 selects the user who has input the input information including the second keyword of ascent as the innovator. The selecting unit 134 selects, as an innovator, the user who has input the input information including the second keyword of rise when the score of the second keyword of rise related to the co-occurrence with the first keyword is equal to or less than a predetermined threshold. The selection unit 134 selects the user who has used the ascending second keyword as an innovator when the ascending second keyword is not used so much.

The selecting unit 134 uses the rank of the ratio as a score and selects the user who has input the input information including the rising second keyword when the rank of the ratio is below the threshold “50th place” as an innovator. The selecting unit 134 selects, as the innovator, the input user who has input the input information including the rising second keyword “sound” at the first time point when the rank of the ratio is 100th below the threshold “50th”. As shown in the innovator information IVINF51, the selecting unit 134 selects the users U100 and U101 who have input the input information including the rising second keyword “sound” at the first time point as the innovator.

(Providing section 135)
The providing unit 135 provides various information to an external information processing device. For example, the providing unit 135 provides various information to the business entity apparatus 20. The providing unit 135 provides a service using the information regarding the needs for the target extracted by the extracting unit 132. For example, the providing unit 135 provides the information requesting source with information regarding the needs of the target extracted by the extracting unit 132.

For example, the providing unit 135 provides the target demand information to the business entity apparatus 20. For example, the providing unit 135 provides the business with the target demand information indicating the needs for the target corresponding to the target information. For example, the providing unit 135 provides the business with the target demand information including the attribute information of the user who searched using the keyword corresponding to the target information. For example, the providing unit 135 provides the business with the target demand information indicating the needs for the target corresponding to the target information. For example, the providing unit 135 provides the business with the target demand information including the attribute information of the user who performed the action related to the keyword corresponding to the target information. For example, the providing unit 135 provides the business with the target demand information including the position information of the user who has performed the action related to the keyword corresponding to the target information.

For example, the providing unit 135 provides the business with the target demand information including the information about the age of the user who searched using the keyword corresponding to the target information. For example, the providing unit 135 provides the business with the target demand information including the information about the sex of the user who searched using the keyword corresponding to the target information. For example, the providing unit 135 provides the business with the target demand information including the position information of the user who has searched using the keyword corresponding to the target information. For example, the providing unit 135 provides the business with the target demand information including the keyword corresponding to the target information and other keywords used in the search. For example, the providing unit 135 provides the business operator with the target demand information regarding the competitive business operator.

For example, the providing unit 135 provides the target demand information to the business operator who is charged for providing the information. For example, the providing unit 135 provides the target demand information to the business operator determined based on the amount of money bid for the information provision. Details of this point will be described later.

In the example of FIG. 1, the provision unit 135 determines that 65% of the keywords used as a query together with the product “car X” are “width”, 20% are “width of cargo bed”, and 10% are “off”. The target demand information indicating “road” and 5% “comfort” is provided to the automobile manufacturer MA. Further, in the example of FIG. 1, the providing unit 135 sets the target demand information indicating that among the users who search for the product “car X”, the male is “75%” and the female is “25%”. Provide to manufacturer MA. Further, in the example of FIG. 1, the providing unit 135 determines that among the users who search for the product “car X”, the twenties are “65%” and the thirties are “20%” (not shown). Is provided to the automobile manufacturer MA.

The providing unit 135 provides a service regarding the second keyword. The providing unit 135 provides a service related to the second keyword of ascent. The providing unit 135 provides the service regarding the second keyword to a predetermined business operator. For example, the providing unit 135 transmits the transition information and the information indicating the rising second keyword to the business entity apparatus 20 (see FIG. 1) of a predetermined business entity. In the example of FIG. 2, the providing unit 135 provides a business that sells a microwave oven with information indicating that the rising second keyword is “sound”.

The providing unit 135 provides services related to innovators. The providing unit 135 transmits information indicating the innovator to the business entity apparatus 20 (see FIG. 1) of a predetermined business entity. In the example of FIG. 2, the providing unit 135 provides a business that sells a microwave oven with information indicating that the innovator is the user U100 or the user U101.

[3. Information processing flow]
Here, the procedure of information processing by the information processing apparatus 100 according to the embodiment will be described with reference to FIG. 9. FIG. 9 is a flowchart showing an example of information processing according to the embodiment.

As shown in FIG. 9, the information processing apparatus 100 acquires user input information (step S101). For example, the information processing apparatus 100 acquires the query used for the user search as the user input information. In the example of FIG. 1, the information processing device 100 acquires the query “car X width” from the terminal device 10-1. Further, in the example of FIG. 1, the information processing device 100 acquires the query “car Y fuel efficiency” from the terminal device 10-2. Further, in the example of FIG. 1, the information processing device 100 acquires the query “smartphone battery” from the terminal device 10-3. Further, in the example of FIG. 1, the information processing device 100 acquires the query “weather” from the terminal device 10-4. Moreover, in the example of FIG. 1, the information processing apparatus 100 acquires the query “vehicle X bed width” from the terminal device 10-5. The information processing apparatus 100 acquires a query used by a large number of users such as the users U1 to U5 for searching. Moreover, the information processing apparatus 100 acquires target information from the business operator. In the example of FIG. 1, the information processing apparatus 100 acquires target information designating the product “car X” from the business entity apparatus 20 used by the automobile manufacturer MA.

The information processing apparatus 100 also extracts the needs for the target corresponding to the target information (step S102). For example, the information processing apparatus 100 extracts the needs for the target corresponding to the target information from the query used for the search. In the example of FIG. 1, the information processing device 100 extracts a query including a character string corresponding to the target information “car X”.

Then, the information processing apparatus 100 generates the target demand information based on the information regarding the needs for the target (step S103). In the example of FIG. 1, the information processing device 100 generates target demand information as shown in the needs information storage unit 124.

Then, the information processing apparatus 100 provides the target demand information to the business operator (step S104). In the example of FIG. 1, the information processing apparatus 100, of the keywords used as a query together with the product “car X”, has 65% “width”, 20% “cargo width”, and 10% “width”. The target demand information indicating "off-road" and 5% "ride comfort" is provided to the automobile manufacturer MA. Further, in the example of FIG. 1, the information processing apparatus 100 displays target demand information indicating that among the users who search for the product “car X”, the men are “75%” and the women are “25%”. Providing to automaker MA. In the example of FIG. 1, among the users who search for the product “Car X”, the information processing apparatus 100 has “65%” in their 20s and “20%” (not shown) in their 30s. The target demand information indicating that is provided to the automobile manufacturer MA.

[4. Providing information from other businesses
In the example of FIG. 1, the case where the target demand information regarding the product “Car X” that the seller sells is provided to the automobile manufacturer MA is shown, but the information processing apparatus 100 provides the target demand information regarding the competition of the business to the business. May be provided. This point will be described with reference to FIG. FIG. 10 is a diagram illustrating an example of information processing according to the embodiment. In the example of FIG. 10, the information processing apparatus 100 provides the automobile manufacturer MA with the target demand information regarding the product “car Y” that is a competitive product of the product “car X” provided by itself. Note that the description of the same points as in FIG. 1 will be omitted as appropriate.

In the example of FIG. 10, the information processing device 100 acquires the target information from the business operator (step S21). For example, the information processing apparatus 100 acquires target information designating the product “car Y” from the business entity apparatus 20 used by the automobile manufacturer MA. For example, the manager M1 of the automobile manufacturer MA specifies the product “car Y” in the information processing apparatus 100 by inputting the target information designating the competitive product “car Y” provided by the competitor of the automobile manufacturer MA. Send the target information.

Then, the information processing apparatus 100 extracts the needs for the target corresponding to the target information. In the example of FIG. 10, the information processing device 100 extracts a query including a character string corresponding to the target information “car Y”. For example, the information processing apparatus 100 extracts information indicating that the user U2 has used the query “fuel consumption” in combination with the query “car Y” from the behavior information storage unit 123 (see FIG. 7). Further, for example, the information processing apparatus 100 extracts the user information regarding the user U2 indicating that the user U2 is a female in their 20s from the user information storage unit 122 (see FIG. 6).

Then, the information processing apparatus 100 generates the target demand information based on the information regarding the needs for the target. In the example of FIG. 10, the information processing device 100 generates target demand information as shown in the needs information storage unit 124. For example, in the information processing apparatus 100, 50% of the keywords used as a query together with the product “car Y” are “fuel consumption”, 20% are “cheap”, and 10% are “luxury”, The target demand information indicating that 5% is “good quality” is generated. In addition, for example, the information processing apparatus 100 generates target demand information indicating that among the users who search for the product “car Y”, the men are “90%” and the women are “10%”. Further, in the example of FIG. 10, among the users who search for the product “car Y”, the target demand information indicating that the twenties are “90%” and the thirties are “5%” (not shown). To generate.

Then, the information processing apparatus 100 provides the business with the target demand information (step S22). In the example of FIG. 10, the information processing apparatus 100 provides the generated target demand information to the automobile manufacturer MA that is the transmission source of the target information. For example, in the information processing apparatus 100, 50% of the keywords used as a query together with the product “car Y” are “fuel consumption”, 20% are “cheap”, and 10% are “luxury”, The target demand information indicating that 5% is “cospa good” is provided to the automobile manufacturer MA. Further, for example, the information processing apparatus 100 provides the automobile manufacturer MA with the target demand information indicating that among the users who search for the product “car Y”, the men are “90%” and the women are “10%”. provide. Further, in the example of FIG. 10, among the users who search for the product “car Y”, the target demand information indicating that the twenties are “90%” and the thirties are “5%” (not shown). To the automobile manufacturer MA.

In this way, the information processing apparatus 100 provides the target demand information regarding the competition to the business, so that the business receiving the target demand information provides the business or the product category that competes with its own business. It is possible to develop or market a new product or the like based on the target demand information thus obtained.

[5. Providing information by bidding)
Further, for example, the information processing device 100 may provide the target demand information in a bid format. For example, the information processing apparatus 100 may provide the target demand information to the business operator determined based on the amount of money bid for the information provision. This point will be described with reference to FIG. FIG. 11 is a diagram illustrating an example of information processing according to the embodiment. FIG. 11 shows a case where a plurality of businesses specify the same product and bid. Note that the description of the same points as in FIG. 1 will be omitted as appropriate.

The information processing apparatus 100 acquires target information from the automobile manufacturer MA (step S31-1). In the example of FIG. 11, the information processing apparatus 100 specifies the product “car X” from the business entity apparatus 20 used by the automobile maker MA and acquires the target information for which the bid amount is “100,000 yen”. For example, the manager M1 of the automobile maker MA designates the product “car X” in the business entity device 20 and inputs the target information for which the bid amount is “100,000 yen”, and the product “car X” is input to the information processing device 100. Bid the target information designating "Car X".

The information processing apparatus 100 also acquires the target information from the automobile manufacturer MB (step S31-2). In the example of FIG. 11, the information processing apparatus 100 specifies the product “car X” from the business entity apparatus 20 used by the automobile manufacturer MB, and acquires the target information for which the bid amount is “200,000 yen”. For example, the manager M2 of the automobile maker MB specifies the product “car X” in the business entity device 20 and inputs the target information for which the bid amount is “200,000 yen”, and the product “car X” is input to the information processing device 100. Bid the target information designating "Car X".

In addition, the information processing device 100 acquires target information from the automobile manufacturer MC (step S31-3). In the example of FIG. 11, the information processing apparatus 100 specifies the product “car X” from the business entity apparatus 20 used by the automobile manufacturer MC and acquires the target information for which the bid amount is “150,000 yen”. For example, the manager M3 of the automobile manufacturer MC specifies the product "car X" in the business entity device 20 and inputs the target information for which the bid amount is "150,000 yen", and thus the product "car X" is input to the information processing device 100. Bid the target information designating "Car X".

Any of the processes of steps S31-1 to S31-3 may be performed before the determination of the business operator of step S32.

Then, the information processing apparatus 100 determines the business operator who provides the target demand information (step S32). For example, the information processing apparatus 100 determines the business operator who provides the target demand information by extracting the business operator based on the bid price from the bid information as shown in the bid information list BL11. In the example of FIG. 11, the information processing apparatus 100 sets the car maker MB that bids the highest amount of “200,000 yen” among the bids for the product “car X” as the operator who provides the target demand information. decide. The information processing apparatus 100 may store the bid information as shown in the bid information list BL11 in the storage unit 120.

Then, the information processing apparatus 100 provides the business with the target demand information (step S33). In the example of FIG. 11, the information processing device 100 provides the generated target demand information to the automobile manufacturer MB. For example, in the information processing apparatus 100, 65% of the keywords used as a query together with the product “car X” are “width”, 20% are “cargo width”, and 10% are “off-road”. Yes, the target demand information indicating that 5% is "comfort" is provided to the automobile manufacturer MB. Further, for example, the information processing apparatus 100 provides the automobile manufacturer MB with the target demand information indicating that among the users who search for the product “car X”, the men are “20%” and the women are “25%”. provide. In the example of FIG. 11, the information processing apparatus 100 has “65%” in the 20s and “20%” (not shown) in the 30s among the users who search for the product “car X”. The target demand information indicating that is provided to the automobile manufacturer MB. Note that the information processing apparatus 100 may determine the business operator who provides the target demand information based on various criteria, not limited to the above. For example, the information processing apparatus 100 may determine a business operator with a bid amount equal to or greater than a predetermined threshold value (for example, 150,000 yen) as a business operator who provides the target demand information. In this case, the information processing apparatus 100 may determine the automobile maker MB and the automobile maker MC as the business entity that provides the target demand information.

[6. effect〕
As described above, the information processing apparatus 100 according to the embodiment has the acquisition unit 131 and the extraction unit 132. The acquisition unit 131 acquires input information input by the user. The extraction unit 132 extracts, from the input information, the first keyword corresponding to the target and the second keyword related to the property of the target to extract transition information indicating the temporal transition of the second keyword.

As described above, the information processing apparatus 100 according to the embodiment extracts the time of the second keyword by extracting the first keyword corresponding to the target and the second keyword related to the property of the target from the input information input by the user. By extracting the transition information indicating the transition, it is possible to extract the information indicating the nature that the needs (demands) are increasing due to the nature of the target. Therefore, the information processing device 100 can appropriately extract the information.

In addition, in the information processing apparatus 100 according to the embodiment, the extraction unit 132 extracts the second keyword whose input tends to increase with the passage of time, as the rising second keyword.

As described above, the information processing apparatus 100 according to the embodiment extracts the second keyword whose input tends to increase with the lapse of time as the rising second keyword, so that the needs (demand) increase due to the nature of the target. It is possible to extract the information indicating the property that is present. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing device 100 according to the embodiment, the extraction unit 132 extracts, as the ascending second keyword, the second keyword whose co-occurrence with the first keyword satisfies a predetermined condition.

As described above, the information processing apparatus 100 according to the embodiment extracts the second keyword whose co-occurrence with the first keyword satisfies a predetermined condition as the ascending second keyword, and thereby needs (demand) according to the target property. It is possible to extract the information indicating the property of increasing. Therefore, the information processing device 100 can appropriately extract the information.

In addition, in the information processing apparatus 100 according to the embodiment, the extraction unit 132 increases the second keyword of the plurality of second keywords related to the property of the target, in which the ratio of co-occurrence with the first keyword satisfies a predetermined condition. 2 Extract as keywords.

As described above, in the information processing apparatus 100 according to the embodiment, among the plurality of second keywords related to the property of the target, the second keyword in which the ratio of co-occurrence with the first keyword satisfies a predetermined condition is set as the rising second keyword. By extracting the information, it is possible to extract information indicating the nature that the needs (demands) are increasing in the nature of the target. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing apparatus 100 according to the embodiment, the extraction unit 132 determines that the ratio corresponding to the first time point does not satisfy the predetermined condition, and the ratio corresponding to the second time point after the first time point is the predetermined condition. The second keyword that satisfies the condition is extracted as the ascending second keyword.

As described above, in the information processing apparatus 100 according to the embodiment, the ratio corresponding to the first time point does not satisfy the predetermined condition, and the ratio corresponding to the second time point after the first time point satisfies the predetermined condition. By extracting the two keywords as the rising second keyword, it is possible to extract the information indicating the property that the needs (demands) are increasing due to the target property. Therefore, the information processing device 100 can appropriately extract the information.

Further, the information processing device 100 according to the embodiment includes a selection unit 134. The selection unit 134 selects the user who has input the input information including the upward second keyword as an innovator.

As described above, the information processing apparatus 100 according to the embodiment selects the user who has input the input information including the rising second keyword as the innovator, and anticipates that the nature of the target has a high need (demand). It is possible to identify and extract (select) the user (innovator) who was doing. Therefore, the information processing device 100 can appropriately extract the information.

In addition, in the information processing apparatus 100 according to the embodiment, the selection unit 134 sets the input information including the ascending second keyword when the score of the ascending second keyword related to the co-occurrence with the first keyword is equal to or less than a predetermined threshold. The entered user is selected as an innovator.

As described above, the information processing apparatus 100 according to the embodiment allows the user who inputs the input information including the ascending second keyword when the score of the ascending second keyword related to the co-occurrence with the first keyword is equal to or less than the predetermined threshold value. By selecting as an innovator, it is possible to identify and extract (select) a user (innovator) who has been paying attention in advance of a property having a high need (demand) in the target property. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing device 100 according to the embodiment, the acquisition unit 131 acquires input information including the search query used by the user for the search.

As described above, the information processing apparatus 100 according to the embodiment acquires the input information including the search query used by the user to use the search query input by the user to meet the needs (demand) in the nature of the target. It is possible to make it possible to extract the information indicating the property in which is increased. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing device 100 according to the embodiment, the acquisition unit 131 acquires input information including posted information posted by a user in a predetermined service.

As described above, the information processing apparatus 100 according to the embodiment uses the posted information posted by the user by acquiring the input information including the posted information posted by the user in the predetermined service, and the needs ( It is possible to make it possible to extract information indicating the nature of increasing (demand). Therefore, the information processing device 100 can appropriately extract the information.

In the information processing apparatus 100 according to the embodiment, the extraction unit 132 extracts the information about the needs of the target by extracting the first keyword and the second keyword from the input information.

As described above, the information processing apparatus 100 according to the embodiment extracts the information about the needs of the target by extracting the first keyword and the second keyword from the input information, and thus the information input by the user. Information about needs can be extracted appropriately. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing apparatus 100 according to the embodiment, the extraction unit 132 extracts information regarding needs for the target based on the first keyword corresponding to the target that is the product or the category of the product and the second keyword.

As described above, the information processing apparatus 100 according to the embodiment allows the user to extract the information about the needs for the target based on the first keyword corresponding to the target that is the product or the category of the product and the second keyword. Information about needs can be appropriately extracted from the input information. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing apparatus 100 according to the embodiment, the extraction unit 132 extracts information regarding needs for the target function based on the second keyword regarding the target function.

As described above, the information processing apparatus 100 according to the embodiment extracts the information regarding the needs for the target function based on the second keyword regarding the target function, thereby appropriately obtaining the information regarding the needs from the information input by the user. Can be extracted. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing device 100 according to the embodiment, the extraction unit 132 extracts information regarding the needs for the target specifications based on the second keyword regarding the target specifications.

As described above, the information processing apparatus 100 according to the embodiment appropriately extracts information about needs from the information input by the user by extracting the information about needs for the target specifications based on the second keyword regarding the target specifications. Can be extracted. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing apparatus 100 according to the embodiment, the extraction unit 132 extracts information regarding the needs for the target specifications based on the second keyword regarding the target value evaluation.

As described above, the information processing apparatus 100 according to the embodiment appropriately extracts the information about the needs from the information input by the user by extracting the information about the needs for the specifications of the target based on the second keyword regarding the value evaluation of the target. Can be extracted. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing device 100 according to the embodiment, the acquisition unit 131 acquires target information specifying a target from a predetermined business operator. The extraction unit 132 extracts information regarding needs for a target designated by a predetermined business operator.

As described above, the information processing apparatus 100 according to the embodiment can appropriately extract the information regarding the needs from the information input by the user by extracting the information regarding the needs for the target designated by the predetermined business operator. .. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires target information that specifies a target from another business operator different from the predetermined business operator. The extraction unit 132 extracts information regarding needs for a target designated by another business operator.

As described above, the information processing apparatus 100 according to the embodiment can appropriately extract the information regarding the needs from the information input by the user by extracting the information regarding the needs for the target designated by the predetermined business operator. .. Therefore, the information processing device 100 can appropriately extract the information.

Further, in the information processing device 100 according to the embodiment, the acquisition unit 131 acquires information regarding the business of a predetermined business operator. The extraction unit 132 extracts the information about the target from the information about the business of the predetermined business operator, and based on the first keyword corresponding to the extracted target and the second keyword about the property of the target, the information about the need for the target is obtained. Extract.

As described above, the information processing apparatus 100 according to the embodiment extracts the information about the target from the information about the business of the predetermined business operator, and uses the first keyword corresponding to the extracted target and the second keyword regarding the property of the target. Based on this, by extracting the information regarding the needs for the target, the information regarding the needs can be appropriately extracted from the information input by the user. Therefore, the information processing device 100 can appropriately extract the information.

Further, the information processing device 100 according to the embodiment has a providing unit 135. The providing unit 135 provides a service using the information regarding the needs for the target extracted by the extracting unit 132.

As described above, the information processing apparatus 100 according to the embodiment can provide a service based on the information about the needs appropriately from the information input by the user by providing the service using the information about the needs for the extracted target. it can.

Further, in the information processing apparatus 100 according to the embodiment, the providing unit 135 provides the information request source with the information regarding the needs of the target extracted by the extracting unit 132.

As described above, the information processing apparatus 100 according to the embodiment provides the information requesting source with the information about the needs of the extracted target, thereby appropriately providing the service based on the information about the needs from the information input by the user. be able to.

Further, the information processing device 100 according to the embodiment has a generation unit 133. The generation unit 133 generates the content regarding the target based on the information regarding the needs for the target extracted by the extraction unit 132.

As described above, the information processing apparatus 100 according to the embodiment appropriately generates the content based on the information regarding the needs from the information input by the user by generating the content regarding the target based on the information regarding the needs regarding the extracted target. can do.

[7. Hardware configuration]
The information processing apparatus 100 according to the above-described embodiment is realized by, for example, a computer 1000 configured as shown in FIG. FIG. 13 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, a HDD (Hard Disk Drive) 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 unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, a program dependent on the hardware of the computer 1000, and the like.

The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. The communication interface 1500 receives data from another device via the network N, sends the data to the CPU 1100, and provides the data generated by the CPU 1100 to the other device via the network N.

The CPU 1100 controls output devices such as a display and a printer and input devices such as a keyboard and a mouse via the input/output interface 1600. 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) and a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Etc.

For example, when the computer 1000 functions as the information processing device 100 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 these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from another device via the network N.

The embodiments of the present application have been described above in detail with reference to the drawings. However, these are examples, and various modifications and improvements are made based on the knowledge of those skilled in the art, including the modes described in the line of the disclosure of the invention. The present invention can be carried out in other forms described above.

[8. Other]
Further, of the processes described in the above embodiment, all or part of the processes described as being automatically performed may be manually performed, or the processes described as being manually performed may be performed. All or part of the process can be automatically performed by a known method. In addition, the processing procedures, specific names, information including various data and parameters shown in the above-mentioned documents and drawings can be arbitrarily generated unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Further, each component of each device shown in the drawings is functionally conceptual and does not necessarily have to be physically configured as shown. 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 the device may be functionally or physically distributed/arranged in arbitrary units according to various loads and usage conditions. It can be integrated and configured.

Further, the respective processes described in the above-described embodiments can be appropriately combined within a range in which the processing contents do not contradict each other.

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

1 Information Processing System 100 Information Processing Device 121 Company Information Storage Unit 122 User Information Storage Unit 123 Behavior Information Storage Unit 124 Needs Information Storage Unit 130 Control Unit 131 Acquisition Unit 132 Extraction Unit 133 Generation Unit 134 Selection Unit 135 Providing Unit 10 Terminal Device 20 Business unit N network

Claims (16)

An acquisition unit that acquires input information input by the user,
An extraction unit that extracts transition information indicating a temporal transition of the second keyword by extracting a first keyword corresponding to a target and a second keyword related to the property of the target from the input information.
An information processing apparatus comprising: The extraction unit is
The information processing apparatus according to claim 1, wherein the second keyword whose input shows an upward trend with the passage of time is extracted as an upward second keyword. The extraction unit is
The information processing apparatus according to claim 1 or 2, wherein the second keyword whose co-occurrence with the first keyword satisfies a predetermined condition is extracted as a rising second keyword. The extraction unit is
The second keyword is extracted as an ascending second keyword from among the plurality of second keywords related to the property of the target, the second keyword whose ratio of co-occurrence with the first keyword satisfies a predetermined condition. The information processing device described. The extraction unit is
The second keyword is increased when the ratio corresponding to the first time point does not satisfy the predetermined condition, and the ratio corresponding to the second time point after the first time point satisfies the predetermined condition. The information processing device according to claim 4, wherein the information processing device is extracted as A selection unit for selecting, as an innovator, a user who has input the input information including the ascending second keyword;
The information processing apparatus according to any one of claims 2 to 5, further comprising: The selection unit is
The user who has input the input information including the ascending second keyword is selected as the innovator when the score of the ascending second keyword related to co-occurrence with the first keyword is equal to or less than a predetermined threshold. The information processing device according to claim 6. The acquisition unit is
The information processing apparatus according to claim 1, wherein the input information including a search query used by the user for searching is acquired. The acquisition unit is
The information processing apparatus according to claim 1, wherein the input information including posted information posted by the user in a predetermined service is acquired. The extraction unit is
The information about the needs of the target is extracted by extracting the first keyword and the second keyword from the input information. 10. The information according to claim 1, wherein Processing equipment. The extraction unit is
The information processing apparatus according to claim 10, wherein information regarding needs for the target is extracted based on the first keyword corresponding to the target that is a product or a category of the product and the second keyword. The extraction unit is
The information processing apparatus according to claim 10 or 11, wherein information regarding needs for the target function is extracted based on the second keyword related to the target function. The extraction unit is
The information processing apparatus according to any one of claims 10 to 12, wherein information regarding needs for the specification of the target is extracted based on the second keyword related to the specification of the target. The extraction unit is
The information processing apparatus according to any one of claims 10 to 13, wherein information regarding needs for specifications of the target is extracted based on the second keyword related to the evaluation of the value of the target. An information processing method executed by a computer,
An acquisition step of acquiring input information input by the user,
An extraction step of extracting transition information indicating a temporal transition of the second keyword by extracting a first keyword corresponding to a target and a second keyword related to the property of the target from the input information;
An information processing method comprising: Acquisition procedure to acquire the input information entered by the user,
An extraction procedure for extracting transition information indicating a temporal transition of the second keyword by extracting a first keyword corresponding to a target and a second keyword related to the property of the target from the input information,
An information processing program that causes a computer to execute.

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