JP6445632B1 - Extraction apparatus, extraction method, and extraction program - Google Patents

Abstract

Information regarding needs is appropriately extracted from information input by a user. An extraction apparatus according to the present application includes an acquisition unit and an extraction unit. The acquisition unit acquires input information input by the user. The extraction unit is a first keyword included in the input information, which is a first keyword corresponding to an object provided by a predetermined business operator, and a second keyword included in the input information, and is a second keyword related to the property of the object. Based on the keywords, information on the needs for the target is extracted. [Selection] Figure 3

Description

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

  In recent years, with the rapid spread of the Internet, for example, techniques relating to analysis using various information on the Internet are provided. For example, a technique for analyzing a customer in consideration of a trend of time using purchase history data or the like is known.

JP2015-146145A

  However, in the above-described conventional technology, it is not always possible to appropriately extract information about needs from information input by the user. For example, there may be a case where information relating to the needs for the target cannot be extracted simply by making a comparison using a 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 extraction device, an extraction method, and an extraction program that appropriately extract information about needs from information input by a user.

  The extraction device according to the present application includes an acquisition unit that acquires input information input by a user, a first keyword included in the input information, the first keyword corresponding to an object provided by a predetermined operator, An extraction unit configured to extract information related to needs for the target based on a second keyword included in the input information and related to the second keyword related to the property of the target.

  According to one aspect of the embodiment, there is an effect that information related to needs can be appropriately extracted from information input by the user.

FIG. 1 is a diagram illustrating an example of an extraction process according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the extraction system according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the extraction device according to the embodiment. FIG. 4 is a diagram illustrating an example of a company information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of a user information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of the behavior information storage unit according to the embodiment. FIG. 7 is a diagram illustrating an example of the need information storage unit according to the embodiment. FIG. 8 is a flowchart illustrating an example of the extraction process according to the embodiment. FIG. 9 is a diagram illustrating an example of the extraction process according to the embodiment. FIG. 10 is a diagram illustrating an example of the extraction process according to the embodiment. FIG. 11 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the extraction device.

  Hereinafter, an embodiment (hereinafter referred to as “embodiment”) for carrying out an extraction apparatus, an extraction method, and an extraction program according to the present application will be described in detail with reference to the drawings. Note that the extraction device, the extraction method, and the extraction program according to the present application are not limited to the embodiment. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description is omitted.

(Embodiment)
[1. (Extraction process)
An example of the extraction process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of an extraction process according to the embodiment.

  In FIG. 1, the extraction apparatus 100 extracts information related to user needs for a predetermined target based on keywords included in input information input by the user. Based on the first keyword corresponding to the target provided by the predetermined operator included in the input information and the second keyword related to the nature of the target, the extraction device 100 obtains information regarding the needs for the target corresponding to the first keyword. Extract. Here, the property is a property (feature) of the object, and the property is a concept including a function of the object, a specification of the object, a value evaluation for the object, and the like. In the example of FIG. 1, information related to needs for a target is extracted as user input information based on a keyword (hereinafter also referred to as “search query” or “query”) used by the user for search. In the example illustrated in FIG. 1, the search information used by the user for the search is described as an example of the input information input by the user. However, the input information is not limited to the search query, and the user can use the social networking service (SNS: SNS: Various information such as information posted in (Social Networking Service) (posted information) may be used.

  FIG. 1 shows a case where the extraction device 100 provides information to a business operator. As long as a company here carries out a business, various companies, such as an individual (natural person) and a corporation, may be included. For example, the business operator is a business operator that designates a product or a product category for which provision of information is requested. For example, the business operator may be a company that provides (sells) goods or services. In the example of FIG. 1, a case where the business operator who designates the product or the category of the product is the automobile manufacturer MA is shown. In addition, the goods here may include services (services) provided by the business operator. Hereinafter, the product or service may be collectively referred to as “product”. In the example of FIG. 1, the extraction apparatus 100 obtains target demand information that is information related to needs for a target corresponding to information (hereinafter also referred to as “target information”) indicating a product or a category of a product specified by the business. To provide. In FIG. 1, the extraction apparatus 100 acquires target information from the automobile manufacturer MA, and provides the automobile manufacturer MA with information related to target demand information corresponding to the acquired target information.

[Configuration of extraction system]
First, the extraction system 1 shown in FIGS. 1 and 2 will be described. As illustrated in FIG. 2, the extraction system 1 includes a terminal device 10, an operator device 20, and an extraction device 100. The terminal device 10, the provider device 20, and the extraction device 100 are connected via a predetermined network N so as to be communicable by wire or wirelessly. FIG. 2 is a diagram illustrating a configuration example of the extraction system according to the embodiment. Note that the extraction system 1 illustrated in FIG. 2 may include a plurality of terminal devices 10, a plurality of business entity devices 20, and a plurality of extraction 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 shown in FIG. 1, the case where the terminal device 10 is a smartphone used by the user is shown. Hereinafter, the terminal device 10 may be referred to as a user. That is, hereinafter, 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 the user ID “U1” (hereinafter, may be referred to as “user U1”).

  Moreover, the terminal device 10 may detect various sensor information not only with a GPS sensor etc. but with various sensors. Moreover, the terminal device 10 has a function of an acceleration sensor, and detects and acquires acceleration information (sensor information) in the movement of the user. 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 where the user is placed such as temperature and atmospheric pressure. Moreover, the terminal device 10 may have various functions such as a heart rate sensor, and may be able to detect and acquire a user's biological information. For example, a user using the terminal device 10 may acquire a user's own context information 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, and the terminal device 10 acquires information on 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 terminal devices 10-1 to 10-5 in accordance with a 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”. Hereinafter, the terminal devices 10-1 to 10-5 are referred to as the terminal device 10 when they are not particularly distinguished.

  The extraction device 100 is an information processing device that extracts information related to needs for a target based on a first keyword included in input information input by a user and a second keyword included in input information. For example, the extraction device 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.

  Further, the extraction device 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 extraction device 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.

  FIG. 1 shows the case where the extraction device 100 provides a search service. However, when an external information processing device provides a search service, the extraction device 100 may not provide the search service. In this case, the extraction apparatus 100 may acquire various types of information from an external information processing apparatus or the like that provides a search service, and may only provide 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 operator device 20 is an information processing device used by an administrator M1 of an automobile manufacturer MA that is an operator. For example, the manager M <b> 1 of the automobile manufacturer MA uses the operator device 20 to specify the keyword regarding the extraction device 100. 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 extraction device 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 extraction device 100 acquires the query “car X width” from the terminal device 10-1 at the date and time dt11-1. Then, the extraction 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 extraction apparatus 100 stores, in the behavior information storage unit 123, behavior information indicating that the user U1 has performed a search using the query “car X width” at the date dt11-1.

  Further, the extraction 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 extraction device 100 acquires the query “car Y fuel consumption” from the terminal device 10-2 at the date dt11-2. Then, the extraction device 100 provides the search result corresponding to the query “car Y fuel consumption” to the terminal device 10-2 (step S12-2). In addition, the extraction 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 consumption” at the date and time dt11-2.

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

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

  First, the extraction 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 extraction device 100 acquires the query “car X cargo bed size” from the terminal device 10-5 at the date and time dt11-5. Then, the extraction device 100 provides the search result corresponding to the query “car X cargo bed size” to the terminal device 10-5 (step S12-5). Further, the extraction apparatus 100 stores, in the behavior information storage unit 123, behavior information indicating that the user U5 has performed a search using the query “car X cargo bed size” at the date dt11-5.

  Hereinafter, when it demonstrates without distinguishing step S11-1-S11-5, it will generically call step S11. Further, the search for each user may be performed a plurality of times without being limited to steps S11-1 to S11-5. In the following description, steps S12-1 to S12-5 will be collectively referred to as step S12 when not described. Although FIG. 1 illustrates five users U1 to U5, the extraction device 100 is not limited to the users U1 to U5, and a large number of users (for example, 1 million users, 10 million users, etc.) are used for the search. Get the query that was.

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

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

  For example, the extraction 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 extraction 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 extraction device 100 may include list information on properties related to various vehicles such as functions, specifications, and value evaluations related to vehicles. For example, the extraction device 100 may have list information including various keywords related to price, size, evaluation, and the like as properties related to a car. For example, the extraction apparatus 100 may have list information including keywords such as “width” and “fuel consumption” as properties related to a car. For example, the extraction device 100 may extract the second keyword using the list information regarding the property of the target “car”.

  In the example of FIG. 1, the extraction device 100 extracts information indicating that the user U1 has used the second keyword “width” related to the specification of the car in combination with the first keyword “car X”. For example, the extraction apparatus 100 extracts information indicating that the user U1 has used the query “width” in combination with the query “car X” from the behavior information storage unit 123. Thus, the extraction 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”. Further, for example, the extraction device 100 extracts user information related to the user U1 indicating that the user U1 is a male in his twenties from the user information storage unit 122 (see FIG. 5).

  Further, in the example of FIG. 1, the extraction device 100 uses that the user U5 uses the second keyword “loading platform” and the second keyword “area” related to the vehicle specification in combination with the first keyword “car X”. Extract the information shown. For example, the extraction device 100 extracts information indicating that the user U5 has used the query “loading platform” and the query “width” in combination with the query “car X” from the behavior information storage unit 123. In this way, the extraction device 100 extracts the user's needs for the target “car X” by extracting the second keyword “carriage” and “width” used together with the first keyword “car X”. Can do. Further, for example, the extraction apparatus 100 extracts user information related to the user U5 indicating that the user U5 is a female in his 30s from the user information storage unit 122 (see FIG. 5). In the above example, the second keyword related to the specification of “car X” corresponding to the first keyword is extracted. However, if the second keyword is used together with the first keyword, various information is extracted. May be. For example, the extraction apparatus 100 may extract the second keyword related to the function of “car X” corresponding to the first keyword. For example, the extraction device 100 may extract the second keyword related to the function of the vehicle such as “energy saving” and “collision prevention”. For example, the extraction apparatus 100 may extract the second keyword related to the value evaluation of “car X” corresponding to the first keyword. For example, the extraction device 100 may extract the second keyword related to the value evaluation of the car such as “popular among young people”, “bargain”, and “hard chair”. Note that the above is an example, and the extraction apparatus 100 may extract the second keyword from various keywords as long as the business operator who manufactures the target product can use the keyword for product development.

  And the extraction apparatus 100 produces | generates target demand information based on the information regarding the needs with respect to a target (step S15). In the example of FIG. 1, the extraction device 100 generates target demand information as shown in the needs information storage unit 124. For example, in the extraction device 100, of the keywords used as a query together with the product “car X”, 65% are “width”, 20% are “loading area”, and 10% are “off-road”. Target demand information indicating that 5% is “riding comfort” is generated. For example, the extraction device 100 generates target demand information indicating that, among users searching for the product “car X”, male is “75%” and female is “25%”. Further, for example, the extraction apparatus 100 generates target demand information indicating that the 20s among the users who search for the product “car X” is “65%” or the like.

  And the extraction apparatus 100 provides object demand information to a provider (step S16). In the example of FIG. 1, the extraction device 100 provides the target demand information generated to the automobile manufacturer MA that is the transmission source of the target information. For example, in the extraction device 100, of the keywords used as a query together with the product “car X”, 65% are “width”, 20% are “loading area”, and 10% are “off-road”. Target demand information indicating that 5% is “riding comfort” is provided to the automobile manufacturer MA. In addition, for example, the extraction device 100 provides the automobile manufacturer MA with target demand information indicating that “male is“ 75% ”and females is“ 25% ”among users searching for the product“ car X ”. To do. In the example of FIG. 1, the extraction device 100 provides the target demand information indicating that the 20s among the users who search for the product “car X” are “65%” or the like to the automobile manufacturer MA.

[Use of information (product development, etc.)]
In this way, the extraction apparatus 100 provides the business with the target demand information indicating the needs for the target corresponding to the target information. Thus, the business entity that has received the target demand information can develop or market a new product or the like based on the provided target demand information for the product or the category of the product specified by itself. 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 from the extraction device 100 together with the second keyword “width” related to the specification of the car X is high. The provided automaker MA can develop the product of the car X with an emphasis on the “width” specification (property). 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 “loading area size” related to the specification of the car X is high. The automaker MA that has received the provision from the extraction device 100 can develop a product of the car X that places importance on the size of the specification (property) of the “loading platform”. The extraction apparatus 100 may generate content related to the target based on information related to the needs for the extracted target. This point will be described later. Further, for example, in the example of FIG. 1, the automobile manufacturer MA that has received a search for the target “car X” from the extraction apparatus 100 provided target demand information indicating that there are many users in their twenties among users. Will be able to develop car X products targeting young users in their 20s. In addition, for example, in the example of FIG. 1, the automobile manufacturer MA that has received the target demand information indicating that there are many male users among the users after performing a search for the target “car X”. Development of car X products targeting men is possible. Further, for example, in the example of FIG. 1, the automobile manufacturer MA that has received the target demand information from the extraction device 100 is a product of the car X that takes into account both the tendency of the second keyword and the user attribute using the second keyword. Development is possible. For example, in the example of FIG. 1, an automobile that has received information from the extraction device 100 that indicates that a female user has a high rate of searching using the second keyword “ride” together with the first keyword “car X”. The maker 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 “car X”.

[1-1. Input information)
In the example of FIG. 1, the search query used by the user for the search is shown as an example of the input information. However, the extraction apparatus 100 can use various information to meet the needs related to the target as long as the input information is input by the user. It may be extracted. For example, the extraction apparatus 100 may extract needs related to objects from character information communicated over a predetermined network.

  For example, the extraction apparatus 100 may extract the needs related to the target for post information posted by the user in the social networking service. For example, the extraction apparatus 100 may extract needs related to a target for posting information posted by a user on Twitter (registered trademark), Facebook (registered trademark), or the like. For example, the extraction apparatus 100 may extract a need related to a target for text (character information) posted by a user on Twitter. In this case, for example, the extraction device 100 uses the first keyword based on the result of the semantic analysis of the input information (posted information) of the user by appropriately using conventional techniques of various natural language processing techniques such as morphological analysis. Or the second keyword may be extracted.

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

  In addition, for example, the extraction apparatus 100 may extract the needs related to the target with respect to the input information regarding the question and the answer input by the user at the question site or the like. Note that the above is an example, and the extraction apparatus 100 may extract needs related to various types of input information. For example, the extraction apparatus 100 may extract the needs related to the target based on the second keyword whose co-occurrence frequency with the first keyword is greater than or equal to a predetermined threshold in the input information input by the user. For example, the extraction apparatus 100 may extract the needs related to the target based on the second keyword in which the number of times the first keyword co-occurs in the input information input by the user is equal to or greater than a predetermined threshold (for example, 1000 times). Good.

[1-2. Content generation)
Note that the extraction apparatus 100 may generate content related to the target based on the information related to the needs for the extracted target. For example, when the input information including the target “car X” includes the second keyword corresponding to the specification “width” which is the property of the target “car X” at a predetermined ratio or more, the extraction device 100 determines that the car X The content related to the car X that makes it easy for the user to visually recognize the specification “width” may be generated. In this case, for example, the extraction apparatus 100 may generate a Web page of the car X that displays the specification “width” information of the car X in a font larger than the other information. Further, for example, the extraction apparatus 100 may generate a Web page of the car X that displays the specification “width” information of the car X in a color different from other information. Further, the extraction device 100 may provide the user with content related to the car X that makes the information of the specification “width” of the car X easier to see than other information.

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

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

  In this case, the extraction 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 extraction apparatus 100 extracts needs for the target “car” based on the second keyword used together with the first keyword such as “car X” and “car Y” related to the target “car”. May be.

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

  In this case, the extraction 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 extraction device 100 may satisfy the needs for the target “minivan” based on the second keyword used together with the first keyword corresponding to the product name (specific car name) related to the target “minivan”. It may be extracted. For example, the extraction apparatus 100 extracts 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”. Also good.

[1-3-2. (Target setting)
In the example of FIG. 1, the extraction device 100 uses the designation information that designates the target related to the business of the business operator, but the extraction device 100 may acquire the target information in various modes.

  For example, the extraction apparatus 100 may extract information related to a target provided by a predetermined operator from information related to the business of the predetermined operator. For example, the extraction apparatus 100 may extract information related to a target provided by a predetermined business from information related to a business of a predetermined business stored in the company information storage unit 121. For example, the extraction apparatus 100 uses information related to the business of the automobile manufacturer MA stored in the company information storage unit 121 as information related to the object provided by the automobile manufacturer MA, such as “car”, “car X”, “car B”, Various information such as “SUV” may be extracted.

  Further, the extraction apparatus 100 is not limited to the information stored in the company information storage unit 121, and may extract information related to a target provided by the business from content on the Internet regarding the business. For example, the extraction apparatus 100 may extract information related to a target provided by a predetermined operator from a site such as a homepage of the automobile manufacturer MA. In this case, for example, the extraction apparatus 100 uses a conventional technique of various natural language processing techniques such as morphological analysis as appropriate, and a predetermined operator operates based on the result of semantic analysis of the homepage of the automobile manufacturer MA. You may extract the information regarding the object to provide. Further, the extraction apparatus 100 may generate list information related to objects corresponding to each business operator based on the above information. In this case, the extraction apparatus 100 may extract information related to a target provided by a predetermined operator using the generated list information.

  And the extraction apparatus 100 may extract the information regarding the needs with respect to the target based on the first keyword corresponding to the target extracted from the information regarding the business of the predetermined operator and the second keyword regarding the property of the target. .

  In addition, for example, the extraction apparatus 100 may acquire target information for designating a target provided by a predetermined provider from another provider different from the predetermined provider. For example, the extraction apparatus 100 may accept designation of target information corresponding to a target related to a product provided by another business from one business. This point will be described with reference to FIG.

[1-4. (Billing)
Further, the extraction device 100 may charge the information providing destination according to the provision of the target demand information. That is, the extraction device 100 may provide the target demand information to a business operator who is charged for providing information. For example, the extraction device 100 may increase the amount and quality of the target demand information to be provided in accordance with an increase in the billing amount. For example, the extraction device 100 uses 50,000 yen as the information provision of the highest-ranking keyword among the keywords used as a query together with the keyword corresponding to the target information, and uses it as a query together with the keyword corresponding to the target information. Information provision on the entire keyword may be 100,000 yen. For example, the extraction apparatus 100 sets the information provision of the first keyword “width” having the highest ratio among the keywords used as a query together with the product “car X” as 50,000 yen, and as a query together with the product “car X”. It is good also as information provision of the whole keyword used for 100,000 yen.

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

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

[1-5. Target demand information)
The above-described target demand information is an example, and the extraction device 100 may provide various types of information as target demand information. For example, the extraction apparatus 100 may provide information indicating the distribution of the area of the user who performed the search as target demand information. In addition, for example, the extraction apparatus 100 acquires target information indicating a product of a business that competes with the business (hereinafter also referred to as “competitive business”) or a category of the product, and obtains target demand information related to the business. It may be provided to the operator. Details of this point will be described later.

[1-6. Provision Mode]
In addition, for example, the extraction apparatus 100 may change the provision mode of the target demand information according to the business scale (sales etc.) of the business operator that is the information provision destination. For example, when the business scale (sales etc.) is less than a predetermined threshold, the extraction apparatus 100 may charge each time information is provided. Further, for example, when the business scale (sales etc.) is equal to or greater than a predetermined threshold, the extraction apparatus 100 may provide information by a fixed amount system. For example, when the business scale (sales, etc.) is greater than or equal to a predetermined threshold value, the extraction apparatus 100 charges the charge amount set for each predetermined period and provides information within the predetermined period. Also good. Further, for example, the extraction apparatus 100 may change the charge amount according to the business scale (sales etc.) of the business operator that is the information providing destination. For example, when the business scale (sales, etc.) is less than a predetermined threshold value for the business operator, the extraction apparatus 100 is similar to the information provision task in comparison with the case where information is provided to a business enterprise whose business scale is a predetermined threshold value or more. The amount may be lowered.

[2. (Extractor configuration)
Next, the configuration of the extraction apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a configuration example of the extraction device according to the embodiment. As illustrated in FIG. 3, the extraction device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The extraction device 100 includes an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator of the extraction device 100, and a display unit (for example, a liquid crystal display) for displaying various types of information. May be.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). The communication unit 110 is connected to the network by wire or wirelessly, and transmits and receives information to and from the terminal device 10 and the provider device 20 included in the extraction 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, or a storage device such as a hard disk or an optical disk. As illustrated in FIG. 3, 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 types of information related to products. FIG. 4 is a diagram illustrating an example of a company information storage unit according to the embodiment. The company information storage unit 121 illustrated in FIG. 4 includes items such as “company ID”, “company name”, “business type”, “competitor”, “product”, “category”, and “competitive product”.

  “Company ID” indicates identification information for identifying a company. “Company name” indicates the name of the company identified by the corresponding company ID. “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” may be a company in the same industry as the company identified by the corresponding company ID, or may be a company providing a product similar to the company identified by the corresponding company ID. Good. Further, for example, “competitor company” may be designated by a company identified by a 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. The “competitive product” indicates the competition of 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 the same type of product or service as the corresponding product. Further, for example, the “competitive product” may be specified by a company identified by the corresponding company ID.

  For example, in the example shown in FIG. 4, the company (company EP1) identified by the company ID “EP1” indicates that the company name is “automobile manufacturer MA” and the business type is “automobile manufacturing / sales”. Further, the competitor of the automobile manufacturer MA is a company (maker MR) identified by the company ID “EP11”. In addition, the product provided by the automobile manufacturer MA indicates “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 car”. The competing product of “car X” is car Y.

  The company information storage unit 121 is not limited to the above, and may store various types of information according to the purpose. For example, the company information storage unit 121 may store information on the business scale 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 types of information regarding user attributes. For example, the user information storage unit 122 stores user attribute information. FIG. 5 is a diagram illustrating an example of a user information storage unit according to the embodiment. The user information storage unit 122 illustrated in FIG. 5 includes items such as “user ID”, “age”, “sex”, “home”, “work location”, 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 illustrated in the example of FIG. “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. “Gender” indicates the gender of the user identified by the user ID.

  “Home” indicates location information of the user's home identified by the user ID. In the example illustrated in FIG. 5, “home” indicates an abstract code such as “LC11”, but may be information indicating latitude and longitude. For example, “home” may be a region name or an address.

  “Work location” indicates position information of the user's work location identified by the user ID. In the example illustrated in FIG. 5, “work location” illustrates an abstract code such as “LC12”, but may be information indicating latitude and longitude. Further, for example, the “work location” may be an area name or an address.

  “Interest” indicates the interest of the user identified by the user ID. That is, “interest” indicates an object that is highly interested by the user identified by the user ID. In the example shown in FIG. 5, “interest” is illustrated for each user one by one.

  For example, in the example illustrated in FIG. 5, the age of the user identified by the user ID “U1” is “20s”, and the gender is “male”. For example, the user identified by the user ID “U1” indicates that the home is “LC11”. For example, the user identified by the user ID “U1” indicates that the work location is “LC12”. For example, the user identified by the user ID “U1” indicates that he / she is interested in “sports”.

  Note that the user information storage unit 122 is not limited to the above, and may store various types of information according to the purpose. For example, the user information storage unit 122 may store information on the demographic attribute of the user and information on 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 types of information regarding the user's behavior. FIG. 6 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. 6 includes items such as “action ID”, “user ID”, “date / time”, and “query information”. The “query information” includes items such as “query 1”, “query 2”, and “query 3”. The “query information” is not limited to “query 1” to “query 3”, but may include items such as “query 4”, “query 5”, and the like as many as the number of combinations.

  The “behavior ID” indicates information for identifying the user's behavior. “User ID” indicates identification information for identifying a user. For example, the user identified by the user ID “U1” corresponds to the user U1 illustrated in the example of FIG. “Date and time” indicates the date and time when the corresponding user action was performed. The “date and time” is abstractly illustrated as “dt11-1” or the like, but a specific date and time such as “April 11, 2017 23:31:52” may be stored. “Query information” indicates information related to the query used in the corresponding search. “Query 1” and “Query 2” indicate 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. 6, the user (user U1) identified by the user ID “U1” indicates that the action AC11 has been performed. Specifically, in the example illustrated in FIG. 6, the user U1 indicates that a search (action AC11) using the first query “car X” and the second query “width” is performed at the date dt11-1. Further, for example, in the example illustrated in FIG. 6, the user (user U2) identified by the user ID “U2” indicates that the action AC12 has been performed. Specifically, in the example illustrated in FIG. 6, the user U2 indicates that a search (action AC12) using the first query “car Y” and the second query “fuel consumption” is performed at the date dt11-2.

  The behavior information storage unit 123 is not limited to the above, and may store various information according to the purpose. Moreover, although the case where action information was memorize | stored in the action information storage part 123 for every user ID was shown in FIG. 6, action information may be memorize | stored for every user ID, for example not only in order of a date. In FIG. 6, information related to the query used by the user for the search is illustrated in the behavior information storage unit 123, but the input information input by the user such as post information posted by the user is stored in the behavior information storage unit 123. May be.

(Needs information storage unit 124)
The needs information storage unit 124 according to the embodiment stores various types of information related to the index. FIG. 7 is a diagram illustrating an example of the need information storage unit according to the embodiment. The needs information storage unit 124 illustrated in FIG. 7 includes items such as “target”, “keyword information”, and “user attribute information”.

  “Target” indicates a target for generating target demand information. 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.).

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

  “User attribute information” indicates target demand information of an attribute of a user who has input input information regarding a corresponding target. For example, “user attribute information” indicates target demand information of an attribute of a user who performed a search or posting using a query related to a corresponding target. The “user attribute information” includes items such as “category”, “attribute”, and “ratio”. “Category” indicates a category for classifying the user. “Attribute” indicates the type (attribute) in the corresponding category. The “ratio” indicates a ratio at which users with corresponding attributes perform a search using a keyword corresponding to a corresponding target.

  In the example of FIG. 7, among keywords used as a query together with the product “car X”, 65% is “width”, 20% is “loading area”, and 10% is “off-road”. 5% indicates "riding comfort". In the example of FIG. 7, among the users who search for the product “car X”, the male is “75%” and the female is “25%”. In the example of FIG. 7, among the users who search for the product “car X”, the 20s 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. 3, the control unit 130 is a controller and is stored in a storage device inside the extraction device 100 by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. Various programs (corresponding to an example of an extraction program) are implemented by using the RAM as a work area. The control unit 130 is a controller, and is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As illustrated in FIG. 3, the control unit 130 includes an acquisition unit 131, a generation unit 133, an extraction unit 132, and a provision unit 134, and realizes or executes functions and operations of information processing described below. .

(Acquisition part 131)
The acquisition unit 131 acquires various types 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 or the provider device 20.

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

  For example, the acquisition unit 131 acquires a query used for the search specified by the operator. For example, the acquisition unit 131 acquires a keyword designated by the business operator as target information. For example, the acquisition unit 131 acquires a category based on a keyword specified by the business operator as target information. For example, when the keyword specified by the operator matches one category, the acquisition unit 131 acquires the specified keyword as the category specification. For example, the acquisition unit 131 acquires target information related to a 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 extraction device 100 acquires target information for designating the keyword “car X” from the company device 20 of the automobile manufacturer MA.

  The acquisition unit 131 acquires various types of information from an external information processing apparatus. 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 a query that the user uses for a 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. In the example of FIG. 1, the acquisition unit 131 acquires the query “car Y fuel consumption” from the terminal device 10-2. In the example of FIG. 1, the acquisition unit 131 acquires a query “smartphone battery” from the terminal device 10-3. In the example of FIG. 1, the acquisition unit 131 acquires the query “weather” from the terminal device 10-4. In the example of FIG. 1, the acquisition unit 131 acquires the query “car X cargo bed 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 information acquired from the terminal device 10.

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

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

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

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

  In the example of FIG. 1, the extraction unit 132 extracts information indicating that the user U1 has used the query “width” in combination with the query “car X” from the behavior information storage unit 123. In the example of FIG. 1, the extraction unit 132 extracts user information related to the user U1 indicating that the user U1 is a male in his twenties from the user information storage unit 122 (see FIG. 5).

  In the example of FIG. 1, the extraction unit 132 extracts information indicating that the user U5 has used the query “loading platform” and the query “width” in combination with the query “car X” from the behavior information storage unit 123. In the example of FIG. 1, the extraction unit 132 extracts user information related to the user U5 indicating that the user U5 is a woman in their 30s from the user information storage unit 122 (see FIG. 5).

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

  In the example of FIG. 1, the generation unit 133 includes 65% of the keywords used as a query together with the product “car X”, “width”, 20% “loading area”, and 10% “off”. Target demand information indicating that the road is “road” and 5% is “ride” is generated. In the example of FIG. 1, the generation unit 133 generates target demand information indicating that males are “75%” and females are “25%” among users searching for the product “car X”. To do. Further, in the example of FIG. 1, the generation unit 133 indicates the target demand indicating that among the users searching for the product “car X”, the 20s are “65%”, the 30s are “20%”, and the like. Generate information.

(Providing unit 134)
The providing unit 134 provides various types of information to an external information processing apparatus. For example, the providing unit 134 provides various types of information to the business entity apparatus 20. The providing unit 134 provides a service using information related to the needs for the object extracted by the extracting unit 132. For example, the providing unit 134 provides information related to the needs for the object extracted by the extracting unit 132 to the information request source.

  For example, the providing unit 134 provides target demand information to the business entity apparatus 20. For example, the providing unit 134 provides target demand information indicating a need for a target corresponding to the target information to the business operator. For example, the providing unit 134 provides the business with target demand information including attribute information of a user who has performed a search using a keyword corresponding to the target information. For example, the providing unit 134 provides target demand information indicating a need for a target corresponding to the target information to the business operator. For example, the providing unit 134 provides target business information including attribute information of a user who has performed an action related to a keyword corresponding to the target information to the business operator. For example, the providing unit 134 provides the business with target demand information including position information of a user who has performed an action related to a keyword corresponding to the target information.

  For example, the providing unit 134 provides target demand information including information on the age of the user who performed a search using a keyword corresponding to the target information to the business operator. For example, the providing unit 134 provides the business with target demand information including information related to the gender of the user who performed a search using a keyword corresponding to the target information. For example, the providing unit 134 provides the business with the target demand information including the position information of the user who performed a search using a keyword corresponding to the target information. For example, the providing unit 134 provides the business with target demand information including other keywords used in the search together with keywords corresponding to the target information. For example, the providing unit 134 provides target business information related to a competing business to the business.

  For example, the providing unit 134 provides target demand information to a business operator charged for providing information. For example, the providing unit 134 provides the target demand information to a business determined based on an amount bid for information provision. Details of this point will be described later.

  In the example of FIG. 1, of the keywords used as a query together with the product “car X”, the providing unit 134 has 65% “width”, 20% “loading area”, and 10% “off”. The target demand information indicating that the vehicle is “road” and 5% is “ride” is provided to the automobile manufacturer MA. In the example of FIG. 1, the providing unit 134 displays target demand information indicating that “male is“ 75% ”and females is“ 25% ”among users searching for the product“ car X ”. Provide to manufacturer MA. In the example of FIG. 1, the providing unit 134 indicates that among users searching for the product “car X”, the 20s are “65%”, the 30s are “20%” (not shown), and the like. Is provided to the automobile manufacturer MA.

[3. (Extraction process flow)
Here, the procedure of the extraction process by the extraction apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 8 is a flowchart illustrating an example of the extraction process according to the embodiment.

  As illustrated in FIG. 8, the extraction apparatus 100 acquires user input information (step S101). For example, the extraction device 100 acquires a query used for a user search as user input information. In the example of FIG. 1, the extraction device 100 acquires the query “car X width” from the terminal device 10-1. In the example of FIG. 1, the extraction device 100 acquires the query “car Y fuel consumption” from the terminal device 10-2. In the example of FIG. 1, the extraction device 100 acquires a query “smartphone battery” from the terminal device 10-3. In the example of FIG. 1, the extraction device 100 acquires the query “weather” from the terminal device 10-4. Further, in the example of FIG. 1, the extraction device 100 acquires the query “car X cargo bed size” from the terminal device 10-5. The extraction device 100 acquires a query used by many users such as the user U1 to the user U5 for the search. In addition, the extraction device 100 acquires target information from the business operator. In the example of FIG. 1, the extraction apparatus 100 acquires target information for designating the product “car X” from the business entity apparatus 20 used by the automobile manufacturer MA.

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

  And the extraction apparatus 100 produces | generates object demand information based on the information regarding the needs with respect to object (step S103). In the example of FIG. 1, the extraction device 100 generates target demand information as shown in the needs information storage unit 124.

  Then, the extraction device 100 provides the target demand information to the business operator (step S104). In the example of FIG. 1, the extraction apparatus 100 has 65% of the keywords used as a query together with the product “car X” as “width”, 20% as “loading area”, and 10% as “off”. The target demand information indicating that the vehicle is “road” and 5% is “ride” is provided to the automobile manufacturer MA. Further, in the example of FIG. 1, the extraction apparatus 100 uses the target demand information indicating that the male is “75%” and the female is “25%” among the users who search for the product “car X”. Provide to manufacturer MA. In the example of FIG. 1, the extraction device 100 indicates that among users searching for the product “car X”, the 20s are “65%”, the 30s are “20%” (not shown), and the like. Is provided to the automobile manufacturer MA.

[4. (Providing information from other companies)
In the example of FIG. 1, the case where the target demand information related to the product “car X” sold by itself is provided to the automobile manufacturer MA is shown, but the extraction device 100 provides the target demand information related to the competition of the business to the business. May be. This point will be described with reference to FIG. FIG. 9 is a diagram illustrating an example of the extraction process according to the embodiment. The example of FIG. 9 shows a case where the extraction apparatus 100 provides target demand information related to the product “car Y”, which is a competing product of the product “car X” that the extraction device 100 provides to the car manufacturer MA. The description of the same points as in FIG. 1 will be omitted as appropriate.

  In the example of FIG. 9, the extraction device 100 acquires target information from the business operator (step S21). For example, the extraction apparatus 100 acquires target information for 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 inputs the target information specifying the competitive product “car Y” provided by the competitor of the automobile manufacturer MA, thereby specifying the product “car Y” to the extraction device 100. Send information.

  And the extraction apparatus 100 extracts the needs with respect to the object corresponding to object information. In the example of FIG. 9, the extraction apparatus 100 extracts a query including a character string corresponding to the target information “car Y”. For example, the extraction 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. 6). In addition, for example, the extraction device 100 extracts user information related to the user U2 indicating that the user U2 is a female in his twenties from the user information storage unit 122 (see FIG. 5).

  And the extraction apparatus 100 produces | generates object demand information based on the information regarding the needs with respect to object. In the example of FIG. 9, the extraction device 100 generates target demand information as shown in the needs information storage unit 124. For example, in the extraction device 100, of the keywords used as a query together with the product “car Y”, 50% is “fuel economy”, 20% is “cheap”, 10% is “luxury”, 5 Target demand information indicating that% is “COSPA is good” is generated. For example, the extraction device 100 generates target demand information indicating that “90%” is male and “10%” is female among users who search for the product “car Y”. In the example of FIG. 9, among the users who search for the product “car Y”, the target demand information indicating that the 20s is “90%” and the 30s is “5%” (not shown). Is generated.

  And the extraction apparatus 100 provides object demand information to a provider (step S22). In the example of FIG. 9, the extraction device 100 provides the target demand information generated to the car manufacturer MA that is the transmission source of the target information. For example, in the extraction device 100, of the keywords used as a query together with the product “car Y”, 50% is “fuel economy”, 20% is “cheap”, 10% is “luxury”, 5 The target demand information indicating that “%” is “COSPA is good” is provided to the automobile manufacturer MA. In addition, for example, the extraction apparatus 100 provides the target demand information indicating that the male “90%” and the female “10%” among the users who search for the product “car Y” to the automobile manufacturer MA. To do. In the example of FIG. 9, among the users who search for the product “car Y”, the target demand information indicating that the 20s is “90%” and the 30s is “5%” (not shown). Is provided to automaker MA.

  As described above, the extraction apparatus 100 provides the target demand information related to the competition to the provider, so that the provider that has received the target demand information is provided for the product or the category of the product that competes with its own business. Development and marketing of new products and the like can be performed based on the target demand information.

[5. (Information provided by bid)
For example, the extraction device 100 may provide target demand information in a bid format. For example, the extraction device 100 may provide the target demand information to a business determined based on the amount bid for the information provision. This point will be described with reference to FIG. FIG. 10 is a diagram illustrating an example of the extraction process according to the embodiment. FIG. 10 shows a case where a plurality of companies designate the same product and bid. The description of the same points as in FIG. 1 will be omitted as appropriate.

  The extraction device 100 acquires target information from the automobile manufacturer MA (step S31-1). In the example of FIG. 10, the extraction apparatus 100 designates the product “car X” from the business entity apparatus 20 used by the automobile manufacturer MA, and acquires target information whose bid amount is “100,000 yen”. For example, the manager M1 of the automobile manufacturer MA designates the product “car X” in the business entity apparatus 20 and inputs target information with a bid amount of “100,000 yen”, whereby the product “car” is input to the extraction apparatus 100. Bid the target information specifying “X”.

  Further, the extraction device 100 acquires target information from the automobile manufacturer MB (step S31-2). In the example of FIG. 10, the extraction device 100 designates the product “car X” from the business entity device 20 used by the automobile manufacturer MB, and acquires target information whose bid amount is “200,000 yen”. For example, the manager M2 of the automobile manufacturer MB designates the product “car X” in the business entity apparatus 20 and inputs the target information with the bid amount “200,000 yen” to the product apparatus “car”. Bid the target information specifying “X”.

  Further, the extraction device 100 acquires target information from the automobile manufacturer MC (step S31-3). In the example of FIG. 10, the extraction apparatus 100 designates the product “car X” from the business entity apparatus 20 used by the automobile manufacturer MC, and acquires target information whose bid amount is “150,000 yen”. For example, the manager M3 of the automobile manufacturer MC designates the product “car X” in the business entity apparatus 20 and inputs the target information with a bid amount of “150,000 yen” to the product apparatus “car”. Bid the target information specifying “X”.

  In addition, as long as processing of step S31-1-S31-3 etc. is before the determination of the provider of step S32, any may be performed first.

  And the extraction apparatus 100 determines the provider who provides object demand information (step S32). For example, the extraction device 100 determines a business that provides the target demand information by extracting a business from the bid information as shown in the bid information list BL11 based on the bid price. In the example of FIG. 10, the extraction device 100 determines the automobile manufacturer MB that bids the highest amount “200,000 yen” among the bids for the product “car X” as the business provider that provides the target demand information. To do. The extraction device 100 may store bid information as shown in the bid information list BL11 in the storage unit 120.

  And the extraction apparatus 100 provides object demand information to a provider (step S33). In the example of FIG. 10, the extraction device 100 provides the target demand information generated to the automobile manufacturer MB. For example, in the extraction device 100, of the keywords used as a query together with the product “car X”, 65% are “width”, 20% are “loading area”, and 10% are “off-road”. Target demand information indicating that 5% is “riding comfort” is provided to the automobile manufacturer MB. Further, for example, the extraction apparatus 100 provides the target demand information indicating that “male is“ 20% ”and female is“ 25% ”among the users who search for the product“ car X ”to the automobile manufacturer MB. To do. In the example of FIG. 10, the extraction device 100 indicates that among users searching for the product “car X”, the 20s are “65%”, the 30s are “20%” (not shown), and the like. Is provided to the automobile manufacturer MB. In addition, the extraction apparatus 100 may determine the provider that provides the target demand information based on various criteria without being limited to the above. For example, the extraction apparatus 100 may determine an operator with a bid amount equal to or greater than a predetermined threshold (for example, 150,000 yen) as an operator that provides target demand information. In this case, the extraction apparatus 100 may determine the automobile manufacturer MB and the automobile manufacturer MC as the business provider that provides the target demand information.

[6. effect〕
As described above, the extraction device 100 according to the embodiment includes the acquisition unit 131 and the extraction unit 132. The acquisition unit 131 acquires input information input by the user. The extraction unit 132 is a first keyword included in the input information, which is a first keyword corresponding to a target provided by a predetermined business operator, and a second keyword included in the input information, and is a first keyword related to the property of the target. Based on the two keywords, information on the needs for the target is extracted.

  As described above, the extraction device 100 according to the embodiment is included in the input keyword and the first keyword included in the input information input by the user and corresponding to the target provided by the predetermined operator. By extracting information related to the needs of the target based on the second keyword and the second keyword related to the properties of the target, it is possible to appropriately extract information about the needs from the information input by the user.

  In the extraction device 100 according to the embodiment, the acquisition unit 131 acquires input information including a search query used by a user for a search.

  As described above, the extraction apparatus 100 according to the embodiment can appropriately extract information related to needs from information input by the user by acquiring input information including a search query used by the user for the search.

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

  As described above, the extraction apparatus 100 according to the embodiment can appropriately extract information on needs from information input by the user by acquiring input information including post information posted by the user in a predetermined service. .

  Further, in the extraction device 100 according to the embodiment, the extraction unit 132 relates to the needs for the target based on the first keyword corresponding to the target that is the product or the category of the product provided by the predetermined operator and the second keyword. Extract information.

  As described above, the extraction apparatus 100 according to the embodiment extracts information on the needs for the target based on the first keyword corresponding to the target that is the product or the category of the product provided by the predetermined operator and the second keyword. By doing so, information regarding needs can be appropriately extracted from information input by the user.

  In the extraction device 100 according to the embodiment, the extraction unit 132 extracts information related to the needs for the target function based on the second keyword regarding the target function.

  As described above, the extraction apparatus 100 according to the embodiment appropriately extracts information on needs from information input by the user by extracting information on needs of the target function based on the second keyword related to the target function. can do.

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

  As described above, the extraction apparatus 100 according to the embodiment appropriately extracts information about needs from information input by the user by extracting information about needs for the target specifications based on the second keyword related to the target specifications. can do.

  In the extraction device 100 according to the embodiment, the extraction unit 132 extracts information related to the needs for the target specification based on the second keyword related to the target value evaluation.

  As described above, the extraction apparatus 100 according to the embodiment appropriately extracts information related to needs from information input by the user by extracting information related to needs for the target specification based on the second keyword related to target value evaluation. Can be extracted.

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

  As described above, the extraction apparatus 100 according to the embodiment can appropriately extract information on needs from information input by the user by extracting information on needs for a target designated by a predetermined business operator.

  In the extraction device 100 according to the embodiment, the acquisition unit 131 acquires target information that designates a target from another business operator that is different from the predetermined business operator. The extraction unit 132 extracts information related to needs for a target specified by another business operator.

  As described above, the extraction apparatus 100 according to the embodiment can appropriately extract information on needs from information input by the user by extracting information on needs for a target designated by a predetermined business operator.

  In the extraction device 100 according to the embodiment, the acquisition unit 131 acquires information related to a business of a predetermined business operator. The extraction unit 132 extracts information related to the target from information related to the business of the predetermined operator, and obtains information related to the needs for the target based on the first keyword corresponding to the extracted target and the second keyword related to the property of the target. Extract.

  As described above, the extraction apparatus 100 according to the embodiment extracts information related to a target from information related to a business of a predetermined operator, and based on the first keyword corresponding to the extracted target and the second keyword related to the property of the target. Thus, by extracting information related to the needs for the target, it is possible to appropriately extract information related to the needs from information input by the user.

  In addition, the extraction device 100 according to the embodiment includes a providing unit 134. The providing unit 134 provides a service using information related to the needs for the object extracted by the extracting unit 132.

  Thus, the extraction apparatus 100 according to the embodiment can provide a service based on information related to needs appropriately from information input by the user by providing a service using information related to needs for the extracted target. .

  Further, in the extraction device 100 according to the embodiment, the providing unit 134 provides information regarding the needs for the target extracted by the extracting unit 132 to the information request source.

  As described above, the extraction apparatus 100 according to the embodiment provides a service based on information related to needs appropriately from information input by the user by providing information related to needs regarding the extracted target to the information request source. Can do.

  In addition, the extraction device 100 according to the embodiment includes a generation unit 133. The generation unit 133 generates content related to the target based on the information related to needs for the target extracted by the extraction unit 132.

  As described above, the extraction apparatus 100 according to the embodiment appropriately generates content based on information related to needs from information input by the user by generating content related to the target based on information regarding needs regarding the extracted target. be able to.

[7. Hardware configuration)
The extraction apparatus 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG. 11, for example. FIG. 11 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the extraction device. The computer 1000 includes a CPU 1100, RAM 1200, ROM 1300, HDD (Hard Disk Drive) 1400, communication interface (I / F) 1500, input / output interface (I / F) 1600, and 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 is started up, a program depending 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 other devices via the network N and sends the data to the CPU 1100, and provides the data generated by the CPU 1100 to other devices via the network N.

  The CPU 1100 controls an output device such as a display and a printer and an input device 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. In addition, 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 it to the CPU 1100 via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable disk), a magneto-optical recording medium such as 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 extraction device 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 130 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them. However, as another example, these programs may be acquired from other devices via the network N.

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

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

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  In addition, the processes described in the above-described embodiments can be appropriately combined within a range that does not contradict the processing contents.

  In addition, the “section (module, unit)” described above can be read as “means” or “circuit”. For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 Extraction system 100 Extraction apparatus 121 Company information storage part 122 User information storage part 123 Behavior information storage part 124 Needs information storage part 130 Control part 131 Acquisition part 132 Extraction part 133 Generation part 134 Providing part 10 Terminal apparatus 20 Provider apparatus N Network

Claims (15)

An acquisition unit that acquires input information input by a user and acquires target information that specifies a target provided by the predetermined provider from a predetermined provider ;
A first keyword included in the input information, a first keyword corresponding to the target specified by the predetermined carrier, a second keyword contained in the input information, about the nature of the object An extraction unit for extracting information on needs for the target by extracting a second keyword from the input information ;
An extraction device comprising: An acquisition unit that acquires input information input by a user and acquires target information that specifies a target provided by the predetermined provider from another provider different from the predetermined provider ;
A first keyword included in the input information, the first keyword corresponding to the target specified by the other business operator, and a second keyword included in the input information, which are related to the property of the target An extraction unit that extracts information on needs for the target by extracting a second keyword from the input information ;
Extraction device you comprising: a. The acquisition unit
Extraction device according to claim 1 or claim 2, characterized in that to obtain the input information including a search query by the user using the search. The acquisition unit
The extraction apparatus according to any one of claims 1 to 3, wherein the input information including post information posted by the user in a predetermined service is acquired. The extraction unit includes:
The information about the needs for the target is extracted based on the first keyword corresponding to the target that is a product or a category of products provided by the predetermined business operator and the second keyword. The extraction device according to any one of 1 to 4 . The extraction unit includes:
Based on the second keyword on the function of the object, extracting apparatus according to any one of claims 1 to 5, characterized in that to extract information about the need for the function of the object. The extraction unit includes:
The extraction device according to any one of claims 1 to 6 , wherein information related to needs for the target specification is extracted based on the second keyword related to the target specification. The extraction unit includes:
The extraction device according to any one of claims 1 to 7 , wherein information related to a need for the specification of the target is extracted based on the second keyword regarding the value evaluation of the target. A providing unit that provides a service using information about the needs of the object extracted by the extracting unit;
The extraction device according to any one of claims 1 to 8 , further comprising: The providing unit includes:
The extraction apparatus according to claim 9 , wherein information relating to the needs for the target extracted by the extraction unit is provided to a business operator who has specified the target . A generating unit that generates content related to the target based on information related to the needs of the target extracted by the extracting unit;
Extraction device according to any one of claims 1 to 10, further comprising a. An extraction method performed by a computer,
An acquisition step of acquiring input information input by a user and acquiring target information specifying a target provided by the predetermined operator from a predetermined operator ;
A first keyword included in the input information, a first keyword corresponding to the target specified by the predetermined carrier, a second keyword contained in the input information, about the nature of the object Extracting a second keyword from the input information to extract information related to the needs of the target;
The extraction method characterized by including. An acquisition procedure for acquiring input information input by a user and acquiring target information for specifying a target provided by the predetermined operator from a predetermined operator ;
A first keyword included in the input information, a first keyword corresponding to the target specified by the predetermined carrier, a second keyword contained in the input information, about the nature of the object An extraction procedure for extracting information on needs for the target by extracting a second keyword from the input information ;
An extraction program characterized by causing a computer to execute. An extraction method performed by a computer,
An acquisition step of acquiring input information input by a user and acquiring target information for specifying a target provided by the predetermined operator from another operator different from the predetermined operator;
A first keyword included in the input information, the first keyword corresponding to the target specified by the other business operator, and a second keyword included in the input information, which are related to the property of the target Extracting a second keyword from the input information to extract information related to the needs of the target;
The extraction method characterized by including. An acquisition procedure for acquiring input information input by a user and acquiring target information for specifying a target provided by the predetermined provider from another provider different from the predetermined provider;
A first keyword included in the input information, the first keyword corresponding to the target specified by the other business operator, and a second keyword included in the input information, which are related to the property of the target An extraction procedure for extracting information on needs for the target by extracting a second keyword from the input information;
An extraction program characterized by causing a computer to execute.

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