Information processor, information processing method, and information processing program

Abstract

To appropriately classify a user for the purpose to use a specific keyword.SOLUTION: An information processor includes: a reception part for receiving input of a keyword and a purpose to use the keyword, from an output destination; a classification part for classifying a user having performed an action relating to the keyword (for example, a user having input the keyword as a retrieval query, a user having purchased a product relating to the keyword, a user having browsed a content relating to the keyword, and the like), in the tendency according to the keyword and the purpose received by the reception part; and an output part for outputting a result of classification by the classification part to the output destination.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] 2. Description of the Related Art Conventionally, there are known techniques for performing various types of information analysis on users. As an example of such a technique, a technique is known in which customer analysis is performed by taking into account trends over time using purchase history data or the like. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2015-146145 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the above-mentioned conventional techniques, it is not always possible to appropriately classify users according to the purpose for which they use a particular keyword.

[0005] For example, the above-mentioned conventional technology merely performs customer analysis taking into account seasonal trends, and does not necessarily allow appropriate classification of users according to the purpose of using specific keywords.

[0006] The present application has been made in consideration of the above, and has an object to appropriately classify users based on the purpose of using specific keywords. [Means for solving the problem]

[0007] The information processing device of the present application is characterized by having a reception unit that receives input of a keyword and a purpose for using the keyword from an output destination, a classification unit that classifies users who have performed an action related to the keyword based on a tendency according to the keyword and purpose received by the reception unit, and an output unit that outputs the result of the classification by the classification unit to the output destination. Effect of the Invention

[0008] According to one aspect of the embodiment, it is possible to provide an effect that users can be appropriately classified according to the purpose for which a particular keyword is used. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of the configuration of the information processing device 10 according to the embodiment. [Diagram 3] FIG. 3 is a diagram showing an example of the user information database 31. As shown in FIG. [Figure 4] FIG. 4 is a diagram showing an example of the destination information database 32. As shown in FIG. [Diagram 5] FIG. 5 is a flowchart illustrating an example of a procedure of information processing according to the embodiment. [Figure 6] FIG. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. As shown in FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the information processing device, the information processing method, and the information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to the embodiments. In addition, the same parts in the following embodiments are given the same reference numerals, and duplicated explanations will be omitted.

[0011] 1. Embodiment The information processing implemented by the information processing device etc. of the present embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the information processing according to the embodiment. Note that in Fig. 1, the information processing etc. according to the embodiment is implemented by an information processing device 10 which is an example of the information processing device according to the present application.

[0012] As shown in Fig. 1, an information processing system 1 according to an embodiment includes an information processing device 10, a user terminal 100, and a destination terminal 200. The information processing device 10, the user terminal 100, and the destination terminal 200 are connected to each other via a network N (see Fig. 2, for example) so as to be able to communicate with each other by wire or wirelessly. The network N is, for example, a Wide Area Network (WAN) such as the Internet. Note that the information processing system 1 shown in Fig. 1 may include a plurality of information processing devices 10, a plurality of user terminals 100, and a plurality of destination terminals 200.

[0013] The information processing device 10 shown in Fig. 1 is an information processing device that performs information processing, and is realized by, for example, a server device or a cloud system. In the example of Fig. 1, the information processing device 10 collects information on user behavior in services provided by the information processing device 10 itself or other server devices, and manages the information in a storage unit of the information processing device. The information processing device 10 then accepts input of a keyword and a purpose for using the keyword from a predetermined output destination, classifies (clusters) users who have performed behavior related to the keyword in some service according to a tendency according to the keyword and purpose, and outputs the classification result to the output destination.

[0014] The services provided by the information processing device 10 or other server devices may be, for example, a search service, a shopping service, a payment service, a route search service, a map provision service, a travel service, a restaurant introduction service, a weather forecast service, a schedule management service, a news provision service, an auction service, a video content distribution service, a financial transaction (stock trading, etc.) service, etc.

[0015] The user terminal 100 shown in Fig. 1 is an information processing device used by a user. The user terminal 100 is realized, for example, by a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. In the example shown in Fig. 1, the user terminal 100 is a smartphone used by a user.

[0016] The output destination terminal 200 shown in Fig. 1 is an information processing device used by an administrator of the output destination. The output destination terminal 200 is realized by, for example, a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, etc. In the example shown in Fig. 1, the output destination terminal 200 is a smartphone used by the administrator.

[0017] The information processing performed by the information processing device 10 will be described below with reference to FIG. 1. In the following description, the user terminal 100 will be referred to as user terminals 100-1 to 100-N (N is any natural number) according to the user who uses the user terminal 100. For example, the user terminal 100-1 is the user terminal 100 used by a user (user U1) identified by a user ID "UID#1". In the following description, the user terminals 100-1 to 100-N will be referred to as user terminal 100 when there is no particular distinction between them. In the following description, the user terminal 100 may be regarded as the same as the user. That is, in the following description, the user may be read as the user terminal 100.

[0018] In the following description, it is assumed that the output destination terminal 200 is used by an administrator (administrator M1) identified by an administrator ID "MID#1". In the following description, the output destination terminal 200 may be regarded as the same as the administrator M1. In other words, in the following description, the administrator M1 may be read as the output destination terminal 200.

[0019] First, the information processing device 10 collects user information about the user (step S1). For example, the information processing device 10 collects, as user information, the user's usage history in various services and information estimated based on the usage history from the user terminal 100, other server devices, etc. As a specific example, the information processing device 10 collects information such as gender and age, other attributes, search history, content browsing history, purchase history, and worry characteristics indicating the characteristics of the worries the user has.

[0020] Next, the information processing device 10 receives input of a keyword and a purpose for using the keyword from the destination terminal 200 (step S2). For example, the information processing device 10 receives information such as discovery of an idea for product development using the keyword, investigation of sales (sales impact, etc.) of the target indicated by the keyword, marketing related to the keyword, etc. In the example of FIG. 1, it is assumed that the information processing device 10 receives keyword #1 from the destination terminal 200.

[0021] Next, the information processing device 10 classifies the users who have performed an action related to the keyword #1 according to the tendency according to the keyword #1 and the purpose (step S3). For example, the information processing device 10 identifies a user group #1 who has performed an action related to the keyword #1 (for example, a user who inputs the keyword #1 as a search query, a user who has purchased a product related to the keyword #1, a user who has viewed a content related to the keyword #1, etc.) based on the user information, and classifies the user group #1 according to the tendency according to the keyword #1 and the purpose. As a specific example, the information processing device 10 classifies the user group #1 using the user information of each user belonging to the user group #1, the keyword #1, the purpose, and the model #1 that has been trained to generate an answer to an input question. As a more specific example, the user group #1 is classified by inputting to the model #1 the user information of each user belonging to the user group #1, the keyword #1, the purpose, and an instruction sentence that instructs the model #1 to output a segment of the user group #1 classified according to the tendency according to the keyword #1 and the purpose.

[0022] Model #1 is a model trained to output an answer corresponding to an input question, and is a language model that performs natural language processing, such as GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers). Model #1 is in the information processing device 10, and was created independently by the business entity that manages the information processing device 10. It is preferable that the input information is trained so as not to be used as a new answer, thereby concealing the input information, such as personal information.

[0023] Here, when "discovering ideas for product development using keywords" is accepted as the purpose of using keyword #1 (in other words, when the emphasis is on finding users who are highly related to keyword #1 and who are estimated to be the main target of the product to be developed), the information processing device 10 classifies, as shown in pattern #1, segments #11 and #12, which are user groups whose user information and the relatedness with keyword #1 are equal to or greater than a predetermined threshold, from user group #1. As an example, the information processing device 10 classifies segments #11 and #12 by inputting an instruction sentence indicating a rule that specifies that segments whose relatedness with keyword #1 is equal to or greater than a predetermined threshold and whose user information is similar should be classified into model #1.

[0024] Furthermore, when "investigating sales figures for the target indicated by the keyword" is received as the purpose of using keyword #1 (in other words, when the purpose cannot be achieved unless a certain number of users are ensured to be classified into the segment), the information processing device 10 classifies user group #1 into segments #21 to #23 so that the number of users classified into each segment is equal to or greater than a predetermined threshold, as shown in pattern #2. As an example, the information processing device 10 classifies segments #21 to #23 by inputting into model #1 an instruction sentence indicating a rule that specifies that the segments are classified into segments in which the user information of the classified users is similar and the number of users is equal to or greater than a predetermined threshold.

[0025] Furthermore, when "keyword-related marketing" is accepted as the purpose of using keyword #1 (in other words, when the purpose cannot be achieved without emphasizing comprehensiveness of users), the information processing device 10 classifies user group #1 into segments #31 to #37 so that users of user group #1 who are equal to or greater than a predetermined threshold are classified into one of the segments, as shown in pattern #3. As an example, the information processing device 10 classifies segments #31 to #37 by inputting an instruction sentence indicating a rule that specifies that users of user group #1 who are equal to or greater than a predetermined threshold are classified into one of the segments for segments with similar user information into model #1.

[0026] Next, the information processing device 10 outputs the classification result to the output destination terminal 200 (step S4). For example, the information processing device 10 outputs information such as information indicating each segment into which the user group #1 is classified according to the tendency according to the keyword #1 and the purpose, and user information of the users included in each segment.

[0027] As described above, the information processing device 10 according to the embodiment can classify a group of users who have performed actions related to a keyword based on a tendency according to the keyword and the purpose of using the keyword. This allows the information processing device 10 according to the embodiment to appropriately classify users according to the purpose of using a specific keyword.

[0028] [2. Other processing examples] The above-described process is merely an example, and the information processing device 10 may perform various processes using various information. In this regard, examples are given below.

[0029] [2-1. Classification of early adopters] In the example of FIG. 1, the information processing device 10 may accept "discovery of early adopters to trade with regarding keyword #1" as the purpose of using keyword #1. In such a case, the information processing device 10 inputs an instruction sentence indicating a rule that specifies classification of a segment of users who are early adopters into a segment with similar user information into model #1, and outputs a segment into which user group #1 is classified. For example, the information processing device 10 inputs the instruction sentence into model #1 together with information indicating the characteristics of the user's purchasing behavior estimated based on the purchase history (for example, whether or not the user tends to purchase a new product immediately after its release (within a specified period after its release)) as user information, thereby outputting the segment.

[0030] [2-2. About segments] 1, the information processing device 10 may classify the user group #1 so that the number of segments is equal to or less than a predetermined threshold (for example, equal to or less than 10). For example, the information processing device 10 inputs an instruction sentence indicating a rule that specifies that the number of segments is equal to or less than a predetermined threshold to the model #1, and causes the model #1 to output the segments into which the user group #1 has been classified.

[0031] Furthermore, the information processing device 10 may set names of segments into which the user group #1 is classified. For example, the information processing device 10 sets names of segments into which the user group #1 is classified based on user information of users classified into the segments. Then, the information processing device 10 outputs information indicating the names of the segments to the output destination terminal 200.

[0032] [2-3. Classification based on questionnaire] In the example of Fig. 1, the information processing device 10 may collect, as user information, response information indicating responses to questionnaires conducted in various services regarding keyword #1. Then, the information processing device 10 inputs the user information indicating the response information into model #1, and outputs a segment into which user group #1 is classified. For example, the information processing device 10 inputs user information indicating response information indicating the priority of a user's viewpoint when purchasing a transaction object (e.g., emphasis on low cost, emphasis on simplicity, etc.) into model #1, and outputs a segment into which user group #1 is classified.

[0033] If a user belonging to user group #1 has not responded to a questionnaire regarding keyword #1, the information processing device 10 may estimate the user's response to the questionnaire. For example, the information processing device 10 estimates the user's response to the questionnaire by inputting user information of the user who has not responded to the questionnaire, the questionnaire, and an instruction sentence instructing the model #1 to output the user's response to the questionnaire, and executes a process for classifying user group #1 using the estimated response.

[0034] In addition, when a user belonging to user group #1 answers only a part of the questionnaire related to keyword #1, the information processing device 10 may complement the answer of the user to the questionnaire. For example, the information processing device 10 inputs user information of the user who answers only a part of the questionnaire, the questionnaire, and an instruction sentence instructing to output the answer of the user to the questionnaire to the model #1, thereby complementing the answer of the user to the questionnaire, and executes the process related to classification of user group #1 using the complemented answer. As a specific example, when user U1 answers the questionnaire with "price emphasis, simplicity emphasis," and user U2, whose user information is similar to user U1, answers the questionnaire with only "price emphasis," the information processing device 10 complements the answer of user U2 with "price emphasis, simplicity emphasis," and executes the process related to classification.

[0035] 3. Configuration of Information Processing Device Next, the configuration of the information processing device 10 will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the information processing device 10 according to an embodiment. As shown in Fig. 2, the information processing device 10 has a communication unit 20, a storage unit 30, and a control unit 40.

[0036] (Regarding communication unit 20) The communication unit 20 is realized by, for example, a network interface card (NIC) etc. The communication unit 20 is connected to the network N by wire or wirelessly, and transmits and receives information between the user terminal 100, the output destination terminal 200, etc.

[0037] (Regarding the storage unit 30) The storage unit 30 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 2, the storage unit 30 has a user information database 31, an output destination information database 32, and a model database 33.

[0038] (Regarding User Information Database 31) The user information database 31 stores various types of information related to users. An example of information stored in the user information database 31 will now be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the user information database 31. In the example of Fig. 3, the user information database 31 has items such as "user ID", "gender / age", "attribute information", "search history", "browsing history", "purchase history", "concern characteristics", and "answer information".

[0039] "User ID" indicates identification information for identifying a user. "Gender / age" indicates the user's gender and age. "Attribute information" indicates the user's attributes (for example, user attributes other than gender / age). "Search history" indicates the user's search history. "Browsing history" indicates the user's browsing history of content, etc. "Purchase history" indicates the user's product purchasing history. "Concern characteristics" indicates the concerns the user is facing. "Response information" indicates the user's responses to a questionnaire.

[0040] That is, FIG. 3 shows an example in which the gender and age of a user identified by user ID "UID#1" is "Gender and Age #1", the attribute information is "Attribute Information #1", the search history is "Search History #1", the browsing history is "Browse History #1", the purchase history is "Purchase History #1", the concern characteristic is "Concern Characteristic #1", and the answer information is "Answer Information #1".

[0041] (About output destination information database 32) The output destination information database 32 stores various information related to output destinations. An example of information stored in the output destination information database 32 will now be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of the output destination information database 32. In the example of Fig. 4, the output destination information database 32 has items such as "output destination ID", "keyword", "target information", and "output information".

[0042] "Destination ID" indicates identification information for identifying the destination. "Keyword" indicates the keyword received from the destination. "Purpose information" indicates the purpose for which the destination uses the keyword. "Output information" indicates the information to be output to the destination.

[0043] That is, FIG. 4 shows an example in which the keyword received from the output destination identified by the output destination ID "DID#1" is "keyword #1", the purpose of using the keyword is "purpose information #1", and the information to be output to the output destination regarding the keyword is "output information #1".

[0044] (About model database 33) The model database 33 stores models that have been trained to generate answers to input questions.

[0045] (Regarding the control unit 40) The control unit 40 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs stored in a storage device inside the information processing device 10 using a RAM as a working area. The control unit 40 is also a controller, and is realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in FIG. 2, the control unit 40 according to the embodiment has a collection unit 41, a reception unit 42, a classification unit 43, and an output unit 44, and realizes or executes the functions and actions of information processing described below.

[0046] (About the collection unit 41) The collection unit 41 collects information on users. For example, in the example of FIG. 1, the collection unit 41 collects, as user information, the user's usage history in various services and information estimated based on the usage history from the user terminal 100, other server devices, etc., and stores the collected information in the user information database 31.

[0047] (Regarding reception unit 42) The receiving unit 42 receives input of a keyword and a purpose for using the keyword from the output destination. For example, in the example of FIG. 1, the receiving unit 42 receives a keyword and a purpose for using the keyword from the output destination terminal 200, and stores them in the output destination information database 32.

[0048] (Regarding classification unit 43) The classification unit 43 classifies users who have performed behavior related to the keyword, based on a tendency according to the keyword and purpose received by the reception unit 42. For example, in the example of Fig. 1, the reception unit 42 refers to the user information database 31 and the output destination information database 32, and classifies user group #1 who has performed behavior related to keyword #1, based on a tendency according to keyword #1 and purpose.

[0049] Furthermore, the classification unit 43 may classify users whose behavior has a correlation with a keyword that is equal to or greater than a predetermined threshold into a predetermined segment. For example, in the example of Fig. 1, the reception unit 42 classifies the user group #1 into segments #11 and #12, which are user groups whose user information has a correlation with the keyword #1 that is equal to or greater than a predetermined threshold, from the user group #1.

[0050] In addition, the classification unit 43 may classify the users so that the number of users classified into each segment is equal to or greater than a predetermined threshold. For example, in the example of Fig. 1, the reception unit 42 classifies the user group #1 into segments #21 to #23 so that the number of users classified into each segment is equal to or greater than a predetermined threshold.

[0051] Furthermore, the classification unit 43 may classify users such that users with a certain threshold or more are classified into one of the segments. For example, in the example of Fig. 1, the reception unit 42 classifies the user group #1 into segments #31 to #37 such that users with a certain threshold or more are classified into one of the segments.

[0052] Furthermore, the classification unit 43 may classify users who are estimated to be early adopters related to a keyword into a predetermined segment. For example, in the example of Fig. 1, when a characteristic of a user's purchasing behavior estimated based on the purchase history is a tendency to purchase a new product within a predetermined period after its release, the reception unit 42 estimates the user to be an early adopter and classifies the user into a predetermined segment.

[0053] In addition, the classification unit 43 may classify users so that the number of segments into which the users are classified is equal to or less than a predetermined number. For example, in the example of FIG. 1, the reception unit 42 classifies the user group #1 so that the number of segments is equal to or less than a predetermined threshold.

[0054] The classification unit 43 may further set a name for the segment into which the users are classified, based on information about the classified users. For example, in the example of Fig. 1, the reception unit 42 sets the name of the segment into which the user group #1 is classified, based on the user information of the users classified into the segment.

[0055] The classification unit 43 may classify users based on their responses to questionnaires about keywords. For example, in the example of Fig. 1, the reception unit 42 classifies user group #1 based on response information indicating responses to questionnaires conducted in various services.

[0056] Furthermore, when a user has not responded to a questionnaire, the classification unit 43 may estimate the user's response to the questionnaire by inputting information about the user and an instruction sentence instructing the model to output the user's response to the questionnaire, which has been trained to generate an answer to an input question, and classify the user using the estimated answer. For example, in the example of FIG. 1, the reception unit 42 refers to the model database 33, and inputs user information of a user who has not responded to a questionnaire, the questionnaire, and an instruction sentence instructing the model to output the user's response to the questionnaire, to the model #1, thereby estimating the user's response to the questionnaire, and performs processing related to classification of the user group #1 using the estimated answer.

[0057] The classification unit 43 may also input information about a user and an instruction sentence instructing the model to output the user's answer to the questionnaire to a model that has been trained to generate an answer to an input question, thereby complementing the user's answer to the questionnaire and classifying the user using the complemented answer. For example, in the example of Fig. 1, the reception unit 42 refers to the model database 33 and inputs user information of a user who has only answered a part of the questionnaire, the questionnaire, and an instruction sentence instructing the model to output the user's answer to the questionnaire to the model #1, thereby complementing the user's answer to the questionnaire, and performs processing related to classification of the user group #1 using the complemented answer.

[0058] The classification unit 43 may classify users by inputting keywords, purpose, information about users, and instruction sentences instructing a model trained to generate answers to input questions to output classification of users according to tendencies corresponding to the keywords and purpose. For example, in the example of FIG. 1, the reception unit 42 refers to the model database 33 and classifies the user group #1 using user information of each user belonging to the user group #1, keyword #1, purpose, and model #1 trained to generate answers to input questions. As a specific example, the user group #1 is classified by inputting user information of each user belonging to the user group #1, keyword #1, purpose, and instruction sentences instructing the model #1 to output segments of the user group #1 classified according to tendencies corresponding to the keywords #1 and purpose.

[0059] (Regarding output unit 44) The output unit 44 outputs to an output destination the result of the classification by the classification unit 43. For example, in the example of Fig. 1, the output unit 44 outputs information such as information indicating each segment into which the user group #1 is classified according to the tendency according to the keyword #1 and the purpose, and user information of the users included in each segment.

[0060] [4. Information processing flow] The procedure of information processing of the information processing device 10 according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a flowchart showing an example of the procedure of information processing according to the embodiment.

[0061] 5, the information processing device 10 judges whether or not an input of a keyword and a purpose for using the keyword has been received from an output destination (step S101). If the keyword and the purpose have not been received (step S101; No), the information processing device 10 waits until the keyword and the purpose are received.

[0062] On the other hand, when a keyword and a purpose are accepted (step S101; Yes), the information processing device 10 classifies users who have performed actions related to the keyword according to a tendency according to the keyword and the purpose (step S102). Then, the information processing device 10 outputs the result of the classification to an output destination (step S103), and ends the process.

[0063] 5. Modifications The above-described embodiment is merely an example, and various modifications and applications are possible.

[0064] [5-1. Processing mode] Among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, and conversely, all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above text and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0065] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0066] Furthermore, the above-described embodiments can be appropriately combined as long as the processing contents are not contradictory.

[0067] 6. Effects As described above, the information processing device 10 according to the embodiment includes a collection unit 41, a reception unit 42, a classification unit 43, and an output unit 44. The collection unit 41 collects information on users. The reception unit 42 receives input of a keyword and a purpose for using the keyword from an output destination. The classification unit 43 classifies users who have performed an action related to the keyword according to a tendency according to the keyword and purpose received by the reception unit 42. The classification unit 43 also classifies users by inputting, to a model trained to generate an answer to an input question, a keyword, a purpose, information about the user, and an instruction sentence instructing the model to output a classification of the user according to the tendency according to the keyword and purpose. The output unit 44 outputs the result of classification by the classification unit 43 to an output destination.

[0068] As a result, the information processing device 10 according to the embodiment can classify a group of users who have performed actions related to a keyword based on a tendency according to the keyword and the purpose of using the keyword, and can therefore appropriately classify users according to the purpose of using a particular keyword.

[0069] In addition, in the information processing device 10 according to the embodiment, for example, the classification unit 43 classifies users whose behavior has a relevance to a keyword equal to or greater than a predetermined threshold into a predetermined segment. The classification unit 43 classifies users such that the number of users classified into each segment is equal to or greater than a predetermined threshold. The classification unit 43 classifies users such that users whose relevance is equal to or greater than a predetermined threshold are classified into any of the segments. The classification unit 43 classifies users who are estimated to be early adopters related to a keyword into a predetermined segment.

[0070] As a result, the information processing device 10 according to the embodiment can classify users based on various criteria according to the keywords and the purpose for which the keywords are used, and can therefore appropriately classify users according to the purpose for which the keywords are used.

[0071] In the information processing device 10 according to the embodiment, for example, the classification unit 43 classifies users so that the number of segments into which the users are classified is a predetermined number or less. The classification unit 43 further sets names for the segments into which the users are classified based on information about the classified users.

[0072] As a result, the information processing device 10 according to the embodiment can output the results of classifying users in various ways, thereby improving convenience.

[0073] In addition, in the information processing device 10 according to the embodiment, for example, the classification unit 43 classifies users using their responses to a questionnaire regarding keywords. In addition, when a user has not responded to a questionnaire, the classification unit 43 estimates the user's response to the questionnaire by inputting information about the user and an instruction sentence instructing a model trained to generate an answer to an input question to output the user's response to the questionnaire, and classifies the user using the estimated answer. In addition, the classification unit 43 complements the user's response to the questionnaire by inputting information about the user and an instruction sentence instructing a model trained to generate an answer to an input question to output the user's response to the questionnaire, and classifies the user using the complemented answer.

[0074] As a result, the information processing device 10 according to the embodiment can classify users using the users' responses to a questionnaire regarding keywords, thereby improving the accuracy of user classification.

[0075] [7. Hardware Configuration] Moreover, the information processing device 10 according to each of the above-described embodiments is realized, for example, by a computer 1000 configured as shown in Fig. 6. The information processing device 10 will be described below as an example. Fig. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. The computer 1000 has a CPU 1100, a ROM 1200, a RAM 1300, a HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0076] The CPU 1100 operates and controls each unit based on a program stored in the ROM 1200 or the HDD 1400. The ROM 1200 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, programs that depend on the hardware of the computer 1000, and the like.

[0077] The HDD 1400 stores programs executed by the CPU 1100, data used by such programs, etc. The communication interface 1500 receives data from other devices via a communication network 500 (corresponding to the network N in the embodiment) and sends the data to the CPU 1100, and also transmits data generated by the CPU 1100 to other devices via the communication network 500.

[0078] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs data generated via the input / output interface 1600 to the output devices.

[0079] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1300. CPU 1100 loads the program from recording medium 1800 onto RAM 1300 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0080] For example, when the computer 1000 functions as the information processing device 10, the CPU 1100 of the computer 1000 executes a program loaded onto the RAM 1300 to realize the function of the control unit 40. In addition, the HDD 1400 stores each piece of data in the storage device of the information processing device 10. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, these programs may be obtained from another device via a predetermined communication network.

[0081] [8. Other] Although some of the embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section.

[0082] Further, the information processing device 10 described above can flexibly change its configuration, for example, by calling an external platform or the like using an API (Application Programming Interface) or network computing to realize some functions.

[0083] Furthermore, the term "unit" in the claims can be read as "means" or "circuit," etc. For example, a collection unit can be read as collection means or collection circuit. [Explanation of symbols]

[0084] 10. Information processing device 20 Communications Department 30 Storage section 31 User information database 32 Output destination information database 33 Model Database 40 Control section 41 Collection Department 42 Reception 43 Classification Department 44 Output section 100 User terminals 200 Output terminal

Claims

1. a reception unit that receives an input of a keyword and a purpose for using the keyword from an output destination; a classification unit that classifies users who have performed actions related to the keywords received by the reception unit according to a tendency according to the keywords and purpose; an output unit that outputs a result of the classification by the classification unit to the output destination; 13. An information processing device comprising:

2. The classification unit includes: Among the users, users whose behavior has a relevance to the keyword that is equal to or greater than a predetermined threshold are classified into a predetermined segment.

2. The information processing apparatus according to claim 1,

3. The classification unit includes: The users are classified into each segment such that the number of users classified into each segment is equal to or greater than a predetermined threshold.

2. The information processing apparatus according to claim 1,

4. The classification unit includes: The users are classified into one of the segments such that users who have a predetermined threshold value or more among the users are classified into one of the segments.

2. The information processing apparatus according to claim 1,

5. The classification unit includes: Among the users, users who are estimated to be early adopters of the keyword are classified into predetermined segments.

2. The information processing apparatus according to claim 1,

6. The classification unit includes: The user is classified into segments such that the number of segments into which the user is classified is equal to or less than a predetermined number.

2. The information processing apparatus according to claim 1,

7. The classification unit includes: Furthermore, a name is set for each segment into which the users are classified, based on information about the classified users.

2. The information processing apparatus according to claim 1,

8. The classification unit includes: The users are classified using their responses to a questionnaire regarding the keywords.

2. The information processing apparatus according to claim 1,

9. The classification unit includes: If the user has not responded to the questionnaire, information about the user and an instruction sentence instructing the model to output the user's response to the questionnaire are input to a model trained to generate responses to input questions, thereby estimating the user's response to the questionnaire, and classifying the user using the estimated response.

9. The information processing apparatus according to claim 8,

10. The classification unit includes: By inputting information about the user and an instruction sentence instructing the model to output the user's answer to the questionnaire to a model trained to generate an answer to an input question, the user's answer to the questionnaire is complemented, and the user is classified using the complemented answer.

9. The information processing apparatus according to claim 8,

11. The classification unit includes: The user is classified by inputting the keyword, the purpose, information about the user, and an instruction sentence instructing a model trained to generate an answer to an input question to output a classification of the user according to the keyword and the purpose.

2. The information processing apparatus according to claim 1,

12. 1. A computer-implemented information processing method, comprising: a receiving step of receiving an input of a keyword and a purpose for using the keyword from an output destination; a classification step of classifying users who have performed actions related to the keywords received in the receiving step, based on a tendency according to the keywords and purpose; an output step of outputting a result of the classification by the classification step to the output destination; 13. An information processing method comprising:

13. a receiving step of receiving an input of a keyword and a purpose for using the keyword from an output destination; a classification step of classifying users who have performed actions related to the keywords received in the reception step, based on a tendency according to the keywords and purpose; an output step of outputting a result of the classification by the classification step to the output destination; An information processing program for causing a computer to execute the above.

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