Information processing device, information processing method, and information processing program

Abstract

To appropriately provide a service according to a size of a target user based on evaluation information from a plurality of users.SOLUTION: An information processing device includes an acquisition part, a generation part and a provision part. The acquisition part acquires first evaluation information representing evaluation by a user for one or more sizes of a specific object having a plurality of sizes. The generation part generates first correlation information representing a first correlation between a plurality of different sizes of the specific object based on the first evaluation information acquired by the acquisition part. The provision part provides a service according to the size of the target user based on the first correlation information generated by the generation part.SELECTED DRAWING: Figure 5

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] Conventionally, there is known a technique for suggesting a specific object, such as footwear or clothing, that is suitable for a target user. For example, there is known a technique for suggesting a size of a specific object that is suitable for a target user, based on evaluations of other users of the size of the specific object. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5256362 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with conventional techniques, it has not been possible to provide services suited to target users based on the correlation between different sizes of specific targets.

[0005] The present application has been made in view of the above, and aims to appropriately provide a service according to the size of a target user based on evaluation information from a plurality of users. [Means for solving the problem]

[0006] The information processing device of the present application is characterized by having an acquisition unit that acquires first evaluation information indicating a user's evaluation of one or more sizes of a specific object having multiple sizes, a generation unit that generates first correlation information indicating a first correlation between different sizes of the specific objects based on the first evaluation information acquired by the acquisition unit, and a provision unit that provides a service according to the size of a target user based on the first correlation information generated by the generation unit. [Effects of the Invention]

[0007] According to one aspect of the embodiment, it is possible to provide an effect that a service appropriate for the size of a target user can be appropriately provided based on evaluation information from a plurality of users. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an information processing system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of information processing according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of second evaluation information according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of the configuration of a terminal device according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of the configuration of an information processing device according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a first evaluation information storage unit according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of a second evaluation information storage unit according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of a user information storage unit according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a specific target information storage unit according to the embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of the configuration of a management server according to the embodiment. [Figure 11] FIG. 11 is a flowchart illustrating an example of information processing according to the embodiment. [Figure 12] FIG. 12 is a diagram illustrating an example of information processing according to the modified example. [Figure 13] FIG. 13 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an information processing device, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to these embodiments. Furthermore, the same components in the following embodiments will be denoted by the same reference numerals, and duplicated descriptions will be omitted.

[0010] (Embodiment) [1. Information Processing System Configuration] An information processing system 1 shown in Fig. 1 will be described. As shown in Fig. 1, the information processing system 1 includes a terminal device 10, an information processing device 100, and a management server 200. The terminal device 10, the information processing device 100, and the management server 200 are connected to each other via a predetermined communication network (network N) so as to be able to communicate with each other via wired or wireless communication. Fig. 1 is a diagram showing an example of the configuration of the information processing system 1 according to an embodiment. Note that the information processing system 1 shown in Fig. 1 may include a plurality of terminal devices 10, a plurality of information processing devices 100, and a plurality of management servers 200.

[0011] The terminal device 10 is an information processing device used by a user. The terminal device 10 may be any device that can implement the processing in the embodiment. The terminal device 10 may also be a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or other device. In the example shown in FIG. 2, the terminal device 10 is a smartphone.

[0012] The terminal device 10 is, for example, a smart device such as a smartphone or a tablet, and is a mobile terminal device that can communicate with any server device via a wireless communication network such as 3G (Generation 3G), LTE (Long Term Evolution), etc. The terminal device 10 may have a screen such as a liquid crystal display with a touch panel function, and may accept various operations on display data such as content, such as tapping, sliding, scrolling, etc., performed by a user with a finger or a stylus.

[0013] In FIG. 2, terminal device 101 is used by user U11, terminal device 102 is used by user U12, terminal device 103 is used by user U13, and terminal device 104 is used by user U14. In the following, when there is no need to distinguish between terminal devices 101, 102, 103, and 104, they will be referred to as "terminal device 10." In addition, when there is no need to distinguish between users U11, U12, U13, and U14, they will be referred to simply as "user." In addition, in the following, terminal device 10 may be referred to as "user." In other words, in the following, user can also be read as terminal device 10.

[0014] Note that FIG. 2 illustrates a case where the user is a user (hereinafter referred to as "evaluating user" where appropriate) who has tried on a specific object to evaluate the size of the specific object. For example, the evaluating user is a user who has expertise in evaluating the size of a specific object. For example, the evaluating user is a seller (a salesperson, a store staff member, etc.) who sells the specific object. The evaluating user answers the question about the degree of fitting of the size of the specific object using, for example, a fitting tool (e.g., an app) that is predetermined for the evaluating user. Note that the method by which the evaluating user answers the question about the degree of fitting of the size of the specific object is not limited to the method using the fitting tool that is predetermined for the evaluating user. For example, the evaluating user may answer in the same way as a purchasing user, which will be described later.

[0015] The evaluating user tries on specific targets of multiple sizes in order and responds to the degree of fitting for each size of the specific target (for example, all sizes of the specific target). For this reason, in FIG. 2, the information processing device 100 acquires evaluation information indicating the evaluation by the evaluating user for each size of the specific target. In other words, the information processing device 100 acquires evaluation information indicating the degree of fitting for each size of the specific target (for example, for each size of the specific target) for each evaluating user.

[0016] In FIG. 12, the terminal device 10 11 is used by a user U21, and the terminal device 10 12 is used by a user U22, and the terminal device 10 13 is used by a user U23, and the terminal device 10 14 is used by a user U24. In the following, the terminal device 10 11 , 10 12 , 10 13 and 10 14 When it is not necessary to distinguish between the users U21, U22, U23, and U24, they will be referred to simply as "users."

[0017] Note that FIG. 12 illustrates a case where the user is a user who has purchased and used a specific object (hereinafter referred to as a "purchasing user" where appropriate). For example, the purchasing user is a general user who has purchased a specific object from a predetermined online shopping mall. The purchasing user answers questions about the degree of fit of the size of the specific object using, for example, a questionnaire notified by the predetermined online shopping mall. Note that the method by which the purchasing user answers questions about the degree of fit of the size of the specific object is not limited to the method using a questionnaire notified by the predetermined online shopping mall. For example, the purchasing user may answer questions on a dedicated page (e.g., a product page) for the specific object on the predetermined online shopping mall.

[0018] The purchasing user answers the question about the degree of fitting of one size of the specific object that the purchasing user purchased. Therefore, in FIG. 12 , the information processing device 100 acquires evaluation information indicating the purchasing user's evaluation of one size of the specific object. In other words, the information processing device 100 acquires evaluation information indicating the degree of fitting of one size of the specific object for each purchasing user. Of course, if the purchasing user has purchased multiple specific objects of different sizes and has answered the question about the degree of fitting for each purchased size, the information processing device 100 acquires evaluation information for each size.

[0019] In this way, the user is a user who has actually worn (or attached) the specific object at least once, such as an evaluator user who tried on the specific object or a purchaser user who purchased and used the specific object. Note that the user is not limited to an evaluator user or a purchaser user, and may be any user as long as they have actually worn (or attached) the specific object at least once.

[0020] The information processing device 100 is an information processing device for appropriately providing services according to the size of a target user based on evaluation information from multiple users, and is realized by, for example, a server device, a cloud system, or the like. For example, the information processing device 100 has a function for identifying a correlation between the sizes of multiple different specific targets based on evaluation information indicating user evaluations of the sizes of the specific targets. Hereinafter, the evaluation information indicating user evaluations of the sizes of the specific targets will be referred to as "first evaluation information" as appropriate. Hereinafter, the correlation between different sizes of specific targets identified based on the first evaluation information will be referred to as "first correlation," and information indicating the first correlation will be referred to as "first correlation information."

[0021] The management server 200 is an information processing device for managing a predetermined online shopping mall that offers specific objects, and is realized by, for example, a server device or a cloud system. For example, the management server 200 has a function of providing a questionnaire for users who have purchased the specific objects to evaluate the specific objects. Note that, hereinafter, the specific objects may be anything that can be worn (or attached) by a user, such as footwear or clothing, and are not particularly limited. For example, the specific objects may be sneakers, sandals, boots, pumps, dress shoes, running shoes, etc. Furthermore, the specific objects may be, for example, tops, dresses, dresses, T-shirts, bottoms, skirts, socks, etc. Furthermore, the specific objects may be rings, brooches, etc.

[0022] Although FIG. 1 shows a case where the information processing device 100 and the management server 200 are separate devices, the information processing device 100 and the management server 200 may be integrated.

[0023] [2. An example of information processing] Fig. 2 is a diagram showing an example of information processing in the information processing system 1 according to the embodiment. In Fig. 2, evaluations are accepted from evaluating users via the terminal device 10. Note that Fig. 2 illustrates an example in which evaluations are accepted from users U11 to U14 as evaluating users who evaluate the size of a specific target, but the number of evaluating users is not particularly limited. The number of evaluating users is not limited to four, i.e., users U11 to U14, and may be one, two, three, five or more.

[0024] Note that, since the first correlation is determined using the ratings from users U11 to U14 for each size, users U11 to U14 are assumed to be rating users with similar sizes, for example. Users U11 to U14 may be rating users identified based on size information of the rating users, for example. In this way, users U11 to U14 are rating users estimated to have similar ratings. Note that users U11 to U14 may be rating users identified based on the rating trends of the rating users, for example. Note that the size information of the rating users may be measured before the rating or at the time of the rating, and is not particularly limited.

[0025] In addition, in order to identify the first correlation between sizes, the evaluator user who evaluates each size is the same. Note that the target user to whom the service is provided according to the size may be any user who is involved in trying on or purchasing one of the sizes for which the first correlation has been identified.

[0026] The degree of fitting is a degree based on the feeling of size as perceived by the evaluator, such as loose, tight, painful, or a specific body part sticking out from the specific target, and is hereinafter assumed to be answered as "GOOD," "OK," or "BAD" as an example. For example, by selecting "GOOD" from "GOOD," "OK," or "BAD" for the size M11 of the specific target, the degree of fitting of the size M11 of the specific target is assumed to be answered as "GOOD." Then, first evaluation information indicating that the degree of fitting of the size M11 of the specific target has been answered as "GOOD" is transmitted to the information processing device 100.

[0027] For ease of explanation, the following description will be given taking an example where the specific target is footwear. That is, the description will be given assuming that the specific targets AA1 to AA3 are footwear. Note that in FIG. 2, the description will be given taking an example where the specific targets AA1 to AA3 are evaluated by the evaluation user, but the number of specific targets is not particularly limited. The number of specific targets is not limited to three, i.e., the specific targets AA1 to AA3, and may be one, two, four or more. For example, the number of specific targets may be all products available in a predetermined online shopping mall, or a portion of all products.

[0028] Each specific target has multiple sizes in 5 mm increments. While Figure 2 illustrates an example in which the multiple sizes of each specific target are 26 cm, 26.5 cm, 27 cm, and 27.5 cm, the multiple sizes of each specific target are not particularly limited. Furthermore, the number of multiple sizes of each specific target is not particularly limited.

[0029] The information processing device 100 acquires evaluation information DT11 indicating evaluations by users U11 to U14 for each size of specific objects AA1 to AA3 (step S101). In the evaluation information DT11, "◎" indicates "GOOD", "◯" indicates "OK", and "×" indicates "BAD".

[0030] The evaluation information DT11 indicates, for example, that user U11 evaluated each size of specific target AA1 to AA3 as follows: specific target AA1 26cm: "X", specific target AA1 26.5cm: "O", specific target AA1 27cm: "◎", specific target AA1 27.5cm: "X", specific target AA2 26cm: "X", specific target AA2 26.5cm: "◎", specific target AA2 27cm: "O", specific target AA2 27.5cm: "X", specific target AA3 26cm: "X", specific target AA3 26.5cm: "O", specific target AA3 27cm: "◎", specific target AA3 27.5cm: "X".

[0031] Furthermore, the evaluation information DT11 indicates that, for example, the size of the specific target AA1, 26 cm, is evaluated as "x" by user U11, "x" by user U12, "x" by user U13, and "x" by user U14.

[0032] For example, the user U11 tries on the sizes of the specific targets AA1 to AA3 in order and transmits the first evaluation information for each size of each specific target. In this case, the user U11 may transmit the first evaluation information for each size, for each of multiple sizes, for each specific target, or for each of multiple specific targets; the transmission of the first evaluation information is not particularly limited.

[0033] The information processing device 100 acquires and aggregates the first evaluation information transmitted from each rating user (step S102). The evaluation information DT11 is the first evaluation information transmitted from each rating user aggregated and stored by the information processing device 100.

[0034] The information processing device 100 identifies a first correlation between specific targets of different sizes among the sizes of the specific targets AA1 to AA3, based on the acquired first evaluation information (step S103).

[0035] The information processing apparatus 100 identifies, for example, a first correlation between each size of the specific target AA1, and each size of the specific target AA2 and each size of the specific target AA3.

[0036] Specifically, the information processing device 100 identifies the sizes of the specific target AA1 for which each evaluation user rated the degree of fitting highly, and identifies a first correlation between the identified highly rated size of the specific target AA1 and each size of the specific target AA2 and each size of the specific target AA3.

[0037] Here, among the sizes of the specific target AA1, all of the users U11 to U14 have rated the 27 cm of the specific target AA1 as "◎", so the information processing device 100 identifies the 27 cm of the specific target AA1 as the size of the specific target AA1 that has received the highest rating. Then, the information processing device 100 identifies a first correlation between the 27 cm of the specific target AA1 and each size of the specific target AA2 and each size of the specific target AA3.

[0038] Among the sizes of the specific target AA2, all of the users U11 to U14 evaluated the specific target AA2, 26 cm, as "x," which differs from the evaluation of the specific target AA1, 27 cm. Therefore, it is assumed that the first correlation between the specific target AA1, 27 cm, and the specific target AA2, 26 cm, is low. The information processing device 100 calculates a low score indicating the first correlation between the specific target AA1, 27 cm, and the specific target AA2, 26 cm.

[0039] On the other hand, among the sizes of the specific target AA3, all of the users U11 to U14 have rated the specific target AA3, 27 cm, as "◎", which is the same as the rating given to the specific target AA1, 27 cm. Therefore, it is assumed that the first correlation between the specific target AA1, 27 cm, and the specific target AA3, 27 cm, is high. The information processing device 100 calculates a high score indicating the first correlation between the specific target AA1, 27 cm, and the specific target AA3, 27 cm.

[0040] Furthermore, among the sizes of the specific target AA2, half of the users U11 to U14 rated the specific target AA2's 26.5 cm as "◎" and "◯," which is slightly different from the rating for the specific target AA1's 27 cm. Therefore, it is assumed that the first correlation between the specific target AA1's 27 cm and the specific target AA2's 26.5 cm is lower than the first correlation with the specific target AA3's 27 cm, but higher than the first correlation with the specific target AA2's 26 cm. The information processing device 100 calculates the score indicating the first correlation between the specific target AA1's 27 cm and the specific target AA2's 26.5 cm to be lower than the score indicating the first correlation with the specific target AA3's 27 cm, but higher than the score indicating the first correlation with the specific target AA2's 26 cm.

[0041] Furthermore, among the sizes of the specific target AA2, all of users U11 to U14 rated the specific target AA2, 27 cm, as "good," so the ratings for the specific target AA1, 27 cm, are slightly different from the ratings for the specific target AA2, 26.5 cm. Therefore, it is assumed that the first correlation between the specific target AA1, 27 cm, and the specific target AA2, 27 cm, is lower than the first correlation with the specific target AA2, 26.5 cm, but higher than the first correlation with the specific target AA2, 26 cm. The information processing device 100 calculates the score indicating the first correlation between the specific target AA1, 27 cm, and the specific target AA2, 27 cm, to be lower than the score indicating the first correlation with the specific target AA2, 26.5 cm, but higher than the score indicating the first correlation with the specific target AA2, 26 cm.

[0042] Then, the information processing device 100 determines the first correlation between 27 cm of the specific target AA1 and each size of the specific target AA2 and each size of the specific target AA3 by calculating a score indicating the first correlation between 27 cm of the specific target AA1 and each size of the specific target AA2 and each size of the specific target AA3.

[0043] In the above embodiment, the information processing device 100 identifies the first correlation between the size of the highly evaluated specific target AA1 and each size of the specific target AA2 and each size of the specific target AA3, but this is not limited to this example.

[0044] The information processing device 100 may, for example, identify sizes for which each rating user has rated the degree of fitting highly among the sizes of each specific target, and determine a first correlation between the identified sizes of the highly rated specific targets. For example, the information processing device 100 may identify sizes for which each rating user has rated the degree of fitting highly (e.g., 26.5 cm and 27 cm) among the sizes of the specific target AA2 in addition to 27 cm for the specific target AA1, and determine a first correlation between the identified size of the highly rated specific target AA2 and 27 cm for the specific target AA1. Furthermore, for example, the information processing device 100 may identify sizes for which each rating user has rated the degree of fitting highly (e.g., 27 cm) among the sizes of the specific target AA3 in addition to 27 cm for the specific target AA1, and determine a first correlation between the identified size of the highly rated specific target AA3 and 27 cm for the specific target AA1.

[0045] In addition, in the above embodiment, the information processing device 100 identifies 27 cm of the specific target AA1 as a criterion for identifying the first correlation, and then identifies the first correlation between 27 cm of the specific target AA1 and each size of each specific target, but this example is not limited to this.

[0046] For example, the information processing device 100 may calculate a score indicating the first correlation between the sizes of each identified target, and then identify the first correlation between sizes that have received high ratings from each rating user.

[0047] The information processing device 100 generates first correlation information based on the identified first correlation (step S104).

[0048] The information processing device 100 generates the first correlation information SDT11 based on, for example, the first correlation between sizes that have received high ratings from each rating user.

[0049] The first correlation information SDT11 indicates, for example, that the first correlation between the specific target AA1 at 27 cm and the specific target AA3 at 27 cm is high, the first correlation between the specific target AA2 at 26.5 cm is average, and the first correlation between the specific target AA2 at 27 cm and the specific target AA3 at 26.5 cm is not low but is somewhat low.

[0050] The information processing device 100 provides a service according to the size of the target user based on the generated first correlation information (step S105). The target user is a user to whom a service is provided according to the size. The target user may be any user who is involved in trying on or purchasing one of the sizes for which the first correlation has been identified. Of course, the target user may also be an evaluator user or a purchasing user.

[0051] For example, if the target user has tried on or purchased specific target AA1 of 27 cm, the information processing device 100 provides information suggesting that the target user try on or purchase specific target AA3 of 27 cm, because specific target AA3 of 27 cm has a high first correlation with specific target AA1 of 27 cm based on the first correlation information SDT11.

[0052] Furthermore, for example, if the specific target AA1 of 27 cm does not match the target user's preferences or is out of stock at the time of the target user's access, the information processing device 100 may provide information suggesting trying on or purchasing the specific target AA2 of 26.5 cm, since the specific target AA2 of 26.5 cm has the next highest first correlation with the specific target AA1 of 27 cm based on the first correlation information SDT11. Furthermore, for example, if the specific target AA3 of 26.5 cm, which has the second highest first correlation with the specific target AA1 of 27 cm after the specific target AA2 of 26.5 cm, matches the target user's preferences better than the specific target AA2 of 26.5 cm, the information processing device 100 may provide information suggesting trying on or purchasing the specific target AA3 of 26.5 cm. For example, the specific target AA3 belongs to a brand that matches the target user's preferences.

[0053] The process for providing a service taking into account the preferences of the target user will be described below.

[0054] Note that, although brand will be used as an example of an attribute of a specific object, the example is not limited to this. For example, the attribute of a specific object may be a category such as clothing or footwear, tops or bottoms, one-piece or dress, sneakers or sandals. Furthermore, for example, the attribute of a specific object may be the specific object itself. In this case, the service is provided taking into account the preference of the target user for the specific object itself.

[0055] Hereinafter, the evaluation information indicating the evaluation by a user (e.g., an evaluation user or a purchasing user) of an attribute of a specific target will be referred to as "second evaluation information" as appropriate. Also, the correlation between attributes of different specific targets identified based on the second evaluation information will be referred to as "second correlation" as appropriate, and information indicating the second correlation will be referred to as "second correlation information."

[0056] The information processing device 100 acquires evaluation information DT21 (see FIG. 3) indicating evaluations by users U11 to U14 of each brand of specific targets AA1 to AA3. FIG. 3 is a diagram showing an example of second evaluation information according to the embodiment. Note that in the evaluation information DT21, "GOOD," "OK," and "BAD" are responses about preference for each brand, and therefore indicate the degree of preference.

[0057] For example, when "GOOD" is selected from among "GOOD," "OK," and "BAD" for brand BB1, second evaluation information indicating that the degree of preference for brand BB1 is answered as "GOOD" is transmitted to the information processing device 100.

[0058] Furthermore, specific target AA1 belongs to brand BB1, specific target AA2 belongs to brand BB2, and specific target AA3 belongs to brand BB3. Note that if the attribute of a specific target is the specific target itself, then specific target AA1 can be read as belonging to specific target AA1, specific target AA2 to specific target AA2, and specific target AA3 to specific target AA3.

[0059] The evaluation information DT21 indicates that the user U11 has evaluated the brands BB1 as "◎", brand BB2 as "◯", and brand BB3 as "◎", for example.

[0060] Further, the evaluation information DT21 indicates that, for example, the user U11 has evaluated the brand BB1 as "◎", the user U12 as "◎", the user U13 as "◎", and the user U14 as "◯".

[0061] The information processing device 100 acquires and aggregates the second evaluation information transmitted from each of the rating users. The evaluation information DT21 is the second evaluation information transmitted by each of the rating users aggregated and stored by the information processing device 100.

[0062] The information processing device 100 identifies a second correlation between brands having different specific targets based on the acquired second evaluation information.

[0063] The information processing device 100 identifies, for example, a second correlation between the brand BB1 and the brand BB2 and the brand BB3.

[0064] The majority of users U11 to U14 rated brand BB1 as "◎". Half of users U11 to U14 rated brand BB2 as "×". The majority of users U11 to U14 rated brand BB3 as "◎".

[0065] Therefore, since the evaluations of brand BB1 and brand BB3 are more similar than the evaluations of brand BB2, it is assumed that the second correlation between brand BB1 and brand BB3 is higher than the second correlation with brand BB2. The information processing device 100 calculates the score indicating the second correlation between brand BB1 and brand BB3 to be higher than the score indicating the second correlation with brand BB2.

[0066] The information processing device 100 calculates a score indicating the second correlation between the brand BB1 and the brands BB2 and BB3, thereby identifying the second correlation between the brand BB1 and the brands BB2 and BB3.

[0067] The information processing device 100 generates second correlation information based on the identified second correlation.

[0068] The information processing device 100 provides a service according to the preference of the target user based on the generated second correlation information. The target user may be any user who is involved in trying on or purchasing one of the brands for which the second correlation has been identified.

[0069] For example, if the target user has tried on or purchased a specific item from brand BB1, the information processing device 100 provides information suggesting trying on or purchasing a specific item from brand BB3 based on the second correlation information, because brand BB3 is the brand that has a high second correlation with brand BB1.

[0070] The information processing device 100 provides a service according to the size and preference of the target user based on the first correlation information and the second correlation information. For example, the information processing device 100 adds the score indicating the second correlation to the score indicating the first correlation to calculate a total score, and provides information for proposing a size of a specific target with a high total score.

[0071] In the above embodiment, the information processing device 100 may generate a model that outputs a score indicating a first correlation when a combination of a specific object and a size is input. In this case, the information processing device 100 may generate a model that is trained, for example, on sizes that are highly rated by each evaluation user as positive examples. The information processing device 100 may then identify a combination of a specific object and a size that has a high score among the scores output using the generated model, and provide a service. For example, the information processing device 100 may input a combination of a specific object and a size that the target user has tried on or purchased into the model based on the user information of the target user, identify the combination of a specific object and a size that has the highest score output from the model, and provide information for proposing the identified combination of the specific object and the size.

[0072] In the above embodiment, the information processing device 100 may generate a model that, when a combination of a specific object, a size, and an attribute is input, outputs an overall score by adding a score indicating a second correlation to a score indicating a first correlation. In this case, the information processing device 100 may generate a model that is trained, for example, on sizes and attributes that are highly rated by each rating user as positive examples. The information processing device 100 may then identify a combination of a specific object, a size, and an attribute that has a high overall score among the overall scores output using the generated model, and provide a service. For example, the information processing device 100 may input a combination of a specific object, a size, and an attribute that the target user has tried on or purchased into the model based on the user information of the target user, identify the combination of the specific object, a size, and an attribute that has the highest overall score output from the model, and provide information for proposing the identified combination of the specific object, a size, and an attribute.

[0073] In the above embodiment, the information processing device 100 may generate a model that indicates the relationship between the fit between the size of each specific target and the size of the users U11 to U14. For example, the model may be based on a sigmoid function. For example, the model may calculate a positive score that increases as the users U11 to U14 evaluate the target size as being too large for their own size, and a negative score that increases as the users U11 to U14 evaluate the target size as being too small. The information processing device 100 may generate a model that, when inputting the size information of the target user, outputs a score indicating a first correlation or an overall score in which a score indicating a second correlation is added to the score indicating the first correlation. Note that the timing of measuring the size information of the target user is not particularly limited.

[0074] In the above embodiment, the information processing device 100 identifies a first correlation between sizes of specific objects AA1 to AA3 that belong to the same footwear category. However, a first correlation between sizes of specific objects of different categories may also be identified. Furthermore, if at least a portion of the parts that come into contact with the user (e.g., the evaluator user or the purchasing user) when worn are in common, it is assumed that a first correlation can be identified with a high probability. For example, sneakers and socks share a common part that comes into contact with the user's feet, and a dress and a dress share a common part that comes into contact with the user's upper body. The information processing device 100 may identify a first correlation between a size of sneakers (an example of footwear) and a size of socks (an example of clothing). The information processing device 100 may identify a first correlation between a size of a dress (a first clothing category) and a size of a dress (a second clothing category). In this way, the information processing device 100 may identify a first correlation between one size of specific objects that have at least a portion of the part that comes into contact with the user when worn in common but are in different categories, and generate first correlation information.

[0075] In addition, in cases where a combination of specific targets of different categories that is highly likely to identify a first correlation has been predetermined, there is no particular need to restrict the combination to having at least a portion of the contact area with the user when worn in common.

[0076] When the information processing device 100 identifies a first correlation between one size of specific objects in a different category and generates first correlation information, the information processing device 100 may provide information suggesting trying on or purchasing a specific object in one size of a different category in accordance with input of user information of a target user. For example, when target information including a specific object that is a sneaker and the size of the sneaker is input as user information of the target user, the information processing device 100 may provide information suggesting trying on or purchasing a sock in one size corresponding to the size of the target user.

[0077] [3. Configuration of terminal device] Next, the configuration of the terminal device 10 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of the configuration of the terminal device 10 according to the embodiment. As shown in Fig. 4, the terminal device 10 has a communication unit 11, an input unit 12, an output unit 13, and a control unit 14.

[0078] (Communications Department 11) The communication unit 11 is realized by, for example, a network interface card (NIC) etc. The communication unit 11 is connected to a predetermined network N by wire or wirelessly, and transmits and receives information to and from the information processing device 100 etc. via the predetermined network N.

[0079] (Input section 12) The input unit 12 accepts various operations from the evaluation users. In the example shown in FIG. 2, various operations are accepted from users U11 to U14. For example, the input unit 12 may accept various operations from the evaluation users via a display screen using a touch panel function. Alternatively, the input unit 12 may accept various operations from buttons provided on the terminal device 10 or a keyboard or mouse connected to the terminal device 10.

[0080] (Output section 13) The output unit 13 is a display screen of a tablet terminal or the like realized by, for example, a liquid crystal display, an organic EL (Electro-Luminescence) display, etc., and is a display device for displaying various information. For example, the output unit 13 displays information transmitted from the information processing device 100.

[0081] (Control unit 14) The control unit 14 is, for example, a controller, and is realized by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like executing various programs stored in a storage device inside the terminal device 10 using a RAM (Random Access Memory) as a work area. For example, these various programs include application programs installed in the terminal device 10. For example, these various programs include application programs that display information transmitted from the information processing device 100. The control unit 14 is also realized by an integrated circuit, for example, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

[0082] As shown in FIG. 4, the control unit 14 has a receiving unit 141 and a transmitting unit 142, and realizes or executes the information processing operations described below.

[0083] (Receiving unit 141) The receiving unit 141 receives various types of information. The receiving unit 141 receives various types of information from an external information processing device. The receiving unit 141 receives various types of information from other information processing devices such as the information processing device 100.

[0084] The receiving unit 141 receives, for example, information for the evaluating user to answer the degree of fitting of each size of each specific target.

[0085] The receiving unit 141 receives, for example, the degree of fitting answered by the evaluator for each size of each specific target.

[0086] (Transmitter 142) The transmitting unit 142 transmits various types of information to an external information processing device. The transmitting unit 142 transmits various types of information to other information processing devices such as the information processing device 100.

[0087] The transmitting unit 142 transmits, for example, first evaluation information indicating the evaluation by the evaluating user for each size of each specific target.

[0088] 4. Configuration of Information Processing Device Next, the configuration of the information processing device 100 according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Fig. 5, the information processing device 100 has a communication unit 110, a storage unit 120, and a control unit 130. Note that the information processing device 100 may also have an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information processing device 100, and a display unit (e.g., a liquid crystal display, etc.) that displays various information.

[0089] (Communication unit 110) The communication unit 110 is realized by, for example, a NIC etc. The communication unit 110 is connected to a network N by wire or wirelessly, and transmits and receives information to and from the terminal device 10 etc. via the network N.

[0090] (Storage unit 120) The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in Fig. 5, the storage unit 120 has a first evaluation information storage unit 121, a second evaluation information storage unit 122, a user information storage unit 123, and a specific target information storage unit 124.

[0091] The first evaluation information storage unit 121 stores first evaluation information indicating evaluations by the evaluating users for each size of each specific target. Here, Fig. 6 shows an example of the first evaluation information storage unit 121 according to the embodiment. As shown in Fig. 6, the first evaluation information storage unit 121 has items such as "user ID," "specific target," and "first evaluation information."

[0092] "User ID" indicates identification information for identifying the rating user. "Specific target" indicates a specific target. "First rating information" indicates first rating information rated by the rating user.

[0093] That is, in FIG. 6, the specific object evaluated by the evaluating user identified by the user ID "U11" is "specific object AA1", and the first evaluation information is "size 26 cm; evaluation "x", size 26.5 cm; evaluation "good", size 27 cm; evaluation "good", size 27.5 cm; evaluation " 〇 Here is an example where "" is used.

[0094] The second evaluation information storage unit 122 stores second evaluation information indicating evaluations by the evaluating users for each brand. FIG. 7 shows an example of the second evaluation information storage unit 122 according to the embodiment. As shown in FIG. 7, the second evaluation information storage unit 122 has items such as "user ID" and "second evaluation information."

[0095] The "user ID" indicates identification information for identifying the rating user. The "second rating information" indicates second rating information evaluated by the rating user.

[0096] That is, Figure 7 shows an example in which the second evaluation information evaluated by the evaluation user identified by user ID "U11" is "Brand BB1; evaluation "◎", Brand BB2; evaluation "〇", Brand BB3; evaluation "◎"".

[0097] The user information storage unit 123 stores user information of the evaluating user. An example of the user information storage unit 123 according to the embodiment is shown in Fig. 8. As shown in Fig. 8, the user information storage unit 123 has items such as "user ID" and "user information."

[0098] "User ID" indicates identification information for identifying the evaluating user. "User information" indicates the user information of the evaluating user (for example, measurement information). In the example shown in FIG. 8, conceptual information such as "User information #11" and "User information #12" is stored in "User information," but in reality, information such as "Size: 26 cm; Measurement date: September 2021" is stored.

[0099] That is, FIG. 8 shows an example in which the user information of the evaluation user identified by the user ID "U11" is "user information #11."

[0100] The specific target information storage unit 124 stores target information of specific targets. For example, it stores target information of specific targets provided in a predetermined online shopping mall managed by the management server 200. Here, FIG. 9 shows an example of the specific target information storage unit 124 according to the embodiment. As shown in FIG. 9, the specific target information storage unit 124 has items such as "specific target" and "target information."

[0101] "Specific target" indicates a specific target. "Target information" indicates target information of a specific target (for example, size information possessed by the specific target). In the example shown in FIG. 9, conceptual information such as "target information #11" and "target information #12" is stored in "target information", but in reality, information such as "26 cm, 26.5 cm, 27 cm, 27.5 cm" is stored.

[0102] That is, FIG. 9 shows an example in which the target information of the specific target AA1 is "target information #11."

[0103] (control unit 130) The control unit 130 is a controller, and is realized, for example, by a CPU, an MPU, or the like, executing various programs stored in a storage device inside the information processing device 100 using RAM as a work area. The control unit 130 is also a controller, and is realized, for example, by an integrated circuit such as an ASIC or an FPGA.

[0104] 5, the control unit 130 has an acquisition unit 131, an identification unit 132, a generation unit 133, a calculation unit 134, and a provision unit 135, and realizes or executes the information processing action described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 5, and may be any other configuration as long as it performs the information processing described below.

[0105] (Acquisition part 131) The acquisition unit 131 acquires various types of information. The acquisition unit 131 acquires various types of information from an external information processing device. The acquisition unit 131 acquires various types of information from another information processing device such as the terminal device 10.

[0106] The acquisition unit 131 acquires various types of information from the storage unit 120. The acquisition unit 131 acquires various types of information from the first evaluation information storage unit 121, the second evaluation information storage unit 122, the user information storage unit 123, and the specific target information storage unit 124. The acquisition unit 131 also stores the acquired various types of information in the storage unit 120. The acquisition unit 131 stores the various types of information in the first evaluation information storage unit 121, the second evaluation information storage unit 122, the user information storage unit 123, and the specific target information storage unit 124.

[0107] The acquisition unit 131 acquires, for example, first evaluation information indicating evaluations by the evaluating users for each size of the specific target. In other words, the acquisition unit 131 acquires, for each evaluating user, first evaluation information indicating the degree of fitting for each size of the specific target.

[0108] The acquisition unit 131 acquires, for example, second evaluation information indicating evaluations by the rating users for each brand. In other words, the acquisition unit 131 acquires, for each rating user, second evaluation information indicating preferences for each brand.

[0109] (Specific Section 132) The specifying unit 132 specifies, for example, based on the first evaluation information acquired by the acquiring unit 131, a first correlation between specific targets of different sizes among the different sizes of the specific targets.

[0110] The identification unit 132, for example, identifies the size of one identified target for which each evaluation user has rated the degree of fitting highly, and identifies a first correlation between the identified size of the one identified target that has received a high rating and each size of each of the other identified targets.

[0111] The identification unit 132 identifies the first correlation between the size of the identified identified target with a high evaluation and each size of each of the other identified targets, for example, based on a score indicating the first correlation calculated by the calculation unit 134 described below.

[0112] The specifying unit 132, for example, specifies sizes for which each evaluating user has given a high rating to the degree of fitting among the sizes of each specific target, and specifies a first correlation between the specified sizes of the specific targets that have received high ratings.

[0113] The specifying unit 132 specifies the first correlation between sizes that have received high ratings from each rating user, based on the score indicating the first correlation calculated by the calculation unit 134, which will be described later, for example.

[0114] The identifying unit 132 identifies a second correlation between brands having different identification targets based on the second evaluation information acquired by the acquiring unit 131, for example.

[0115] The information processing device 100 identifies the second correlation between one brand and each of the other brands, for example, based on the score indicating the second correlation calculated by the calculation unit 134, which will be described later.

[0116] (Generation unit 133) The generating unit 133 generates first correlation information based on the first correlation identified by the identifying unit 132, for example.

[0117] The generating unit 133 generates the first correlation information based on, for example, the first correlation between sizes that have received high ratings from each rating user.

[0118] The generating unit 133 generates second correlation information based on the second correlation identified by the identifying unit 132, for example.

[0119] The generation unit 133 generates a model that outputs a score indicating the first correlation when a combination of a specific object and a size is input, for example.

[0120] The generation unit 133 generates a model that is trained, for example, on sizes that have received high ratings from each rating user as positive examples.

[0121] For example, when a combination of a specific target, a size, and an attribute is input, the generation unit 133 generates a model that outputs a total score in which a score indicating the second correlation is added to a score indicating the first correlation.

[0122] The generation unit 133 generates a model that is trained, for example, on sizes and attributes that have received high ratings from each rating user as positive examples.

[0123] (Calculation unit 134) The calculation unit 134 calculates, for example, a score indicating a first correlation between the sizes of the specific targets.

[0124] The calculation unit 134 calculates a score indicating the first correlation using the model generated by the generation unit 133, for example.

[0125] The calculation unit 134 calculates, for example, a score indicating the second correlation between the brands.

[0126] The calculation unit 134 calculates a score indicating the second correlation using the model generated by the generation unit 133, for example.

[0127] For example, the calculation unit 134 calculates the overall score by adding the score indicating the second correlation to the score indicating the first correlation.

[0128] (Provider 135) The providing unit 135 provides (transmits) a service according to the size of the target user based on the first correlation information generated by the generating unit 133, for example.

[0129] The providing unit 135 provides, for example, information for suggesting trying on or purchasing a specific item of one size.

[0130] The providing unit 135 provides a service according to the preference of the target user based on the second correlation information generated by the generating unit 133, for example.

[0131] The providing unit 135 provides, for example, information for suggesting a specific target of a brand to try on or purchase.

[0132] The providing unit 135 provides, for example, information for suggesting trying on or purchasing a specific item of a size having a high score (including the overall score) calculated by the calculating unit 134.

[0133] The providing unit 135 provides, for example, information for proposing a size of a specific object having a high score (including a total score).

[0134] [5. Management Server Configuration] Next, the configuration of the management server 200 according to the embodiment will be described with reference to Fig. 10. Fig. 10 is a diagram showing an example of the configuration of the management server 200 according to the embodiment. As shown in Fig. 10, the management server 200 includes a communication unit 210, a storage unit 220, and a control unit 230. The management server 200 may also include an input unit that accepts various operations from an administrator of the management server 200, and a display unit that displays various information.

[0135] (Communication unit 210) The communication unit 210 is realized by, for example, a NIC etc. The communication unit 210 is connected to a network N by wire or wirelessly, and transmits and receives information to and from the information processing device 100 etc. via the network N.

[0136] (Storage unit 220) The storage unit 220 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk.

[0137] The storage unit 220 stores the same information as the specific target information storage unit 124. Therefore, a description thereof will be omitted.

[0138] (control unit 230) The control unit 230 is a controller, and is realized by, for example, a CPU, an MPU, or the like, executing various programs stored in a storage device inside the management server 200 using RAM as a work area. The control unit 230 is also a controller, and is realized by, for example, an integrated circuit such as an ASIC or FPGA.

[0139] 10, control unit 230 has acquisition unit 231 and provision unit 232, and realizes or executes the information processing action described below. Note that the internal configuration of control unit 230 is not limited to the configuration shown in Fig. 10, and may be any other configuration as long as it performs the information processing described below.

[0140] (Acquisition part 231) The acquisition unit 231 acquires various types of information. The acquisition unit 231 acquires various types of information from an external information processing device. The acquisition unit 231 acquires various types of information from another information processing device such as the information processing device 100.

[0141] The acquisition unit 231 acquires various types of information from the storage unit 220. Furthermore, the acquisition unit 231 stores the acquired various types of information in the storage unit 220.

[0142] The acquisition unit 231 acquires target information of a specific target provided in a predetermined online shopping mall.

[0143] (Providing Department 232) The providing unit 232 provides (transmits) the target information acquired by the acquiring unit 231.

[0144] [6. Information Processing Flow] Next, the procedure of information processing by the information processing system 1 according to the embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the procedure of information processing by the information processing system 1 according to the embodiment.

[0145] As shown in FIG. 11, the information processing device 100 acquires first evaluation information indicating evaluations by the evaluating users for each size of the identified target (step S201).

[0146] The information processing device 100 generates first correlation information indicating the first correlation based on the acquired first evaluation information (step S202).

[0147] The information processing device 100 provides a service according to the size of the target user based on the generated first correlation information (step S203).

[0148] [7. Modifications] The information processing system 1 according to the embodiment described above may be implemented in various different forms other than the above embodiment, so other embodiments of the information processing system 1 will be described below.

[0149] In the above embodiment, a case where a specific target is evaluated by an evaluating user has been described. In the following modified example, a case where a specific target is evaluated by a purchasing user will be described. Note that the same description as in FIG. 2 will be omitted as appropriate.

[0150] For convenience of explanation, a case where a specific target is evaluated only by a purchasing user will be described, but a modified example is intended to include a case where a specific target is evaluated by an evaluating user and then evaluated by the purchasing user. Meanwhile, the above embodiment also describes a case where a specific target is evaluated only by an evaluating user, but the above embodiment is intended to include a case where a specific target is evaluated by a purchasing user and then evaluated by the evaluating user.

[0151] Depending on the specific target, the number of purchasing users who have purchased the specific target may be small, and the number of reviews may be insufficient. For example, this may be the case when the specific target is a new product. Here, the case where the number of reviews is insufficient means that, in order to provide a service tailored to the size of the target user, the number of reviews is insufficient to accurately suggest, for example, a combination of the specific target and size that matches the size of the target user. Therefore, by having the reviewing users try on and review each specific target in all sizes, it is possible to provide a service tailored to the size of the target user with high accuracy, even when the number of reviews by purchasing users is insufficient.

[0152] In addition, it may be difficult for the evaluating user to try on and evaluate each specific object in every size. For this reason, for example, for specific objects for which there is no evaluation information from the evaluating user, it is possible to provide a highly accurate service according to the size of the target user by using the evaluation information from the purchasing user.

[0153] FIG. 12 is a diagram illustrating an example of information processing according to the modified example.

[0154] In the following description, it is assumed that users U21 to U24 are purchasing users who have purchased specific objects provided in a predetermined online shopping mall managed by the management server 200. It is also assumed that user U21 is a purchasing user who has purchased the specific object AA1 of 26 cm, user U22 is a purchasing user who has purchased the specific object AA2 of 26.5 cm, user U23 is a purchasing user who has purchased the specific object AA3 of 27 cm, and user U24 is a purchasing user who has purchased the specific object AA1 of 27.5 cm, the specific object AA2 of 27 cm, and the specific object AA3 of 27.5 cm.

[0155] The information processing device 100 acquires evaluation information DT12 indicating evaluations by users U21 to U24 for each size of specific objects AA1 to AA3 (step S301).

[0156] The evaluation information DT12 indicates, for example, that the user U11 evaluated the specific target AA1 of 26 cm as "x." Note that the "-" assigned to the specific target AA1 of 26.5 cm, 27 cm, and 27.5 cm, and the "-" assigned to each size of the specific target AA2 and the specific target AA3 indicate that the user U11 did not evaluate them.

[0157] In addition, in the evaluation information DT12, for example, "-" given to users U22 to U24 who have a specific target AA1 of 26 cm indicates that there is no evaluation for the specific target AA1 of 26 cm.

[0158] For example, the user U11 purchases and uses a specific target AA1 of 26 cm, and transmits first evaluation information regarding the specific target AA1 of 26 cm.

[0159] The information processing device 100 acquires and aggregates the first evaluation information transmitted from each purchasing user (step S302). The evaluation information DT12 is the first evaluation information transmitted from each purchasing user aggregated and stored by the information processing device 100.

[0160] The processing after step S302 is the same as in the above embodiment, and therefore the description thereof will be omitted.

[0161] [8. Effects] As described above, the information processing device 100 according to the embodiment includes the acquisition unit 131, the generation unit 133, and the provision unit 135. The acquisition unit 131 acquires first evaluation information indicating a user's evaluation of one or more sizes of a specific target having a plurality of sizes. The generation unit 133 generates first correlation information indicating a first correlation between the sizes of different specific targets, based on the first evaluation information acquired by the acquisition unit 131. The provision unit 135 provides a service according to the size of the target user, based on the first correlation information generated by the generation unit 133.

[0162] As a result, the information processing device 100 according to the embodiment can provide services suited to the target user based on the first correlation, and can therefore appropriately provide services according to the size of the target user based on the first evaluation information from multiple users.

[0163] The user is a user who has tried on the specific object for evaluation, or a user who has purchased and used the specific object.

[0164] As a result, the information processing apparatus 100 according to the embodiment can provide highly accurate services suited to the size of the target user based on the evaluation information from the evaluating users or purchasing users.

[0165] Furthermore, the user is the same user who commonly evaluated the sizes of a plurality of different specific targets.

[0166] As a result, the information processing apparatus 100 according to the embodiment can provide highly accurate services according to the size of the target user based on the evaluation information from the same user.

[0167] In addition, when the provision unit 135 receives an input of a combination of a specific object and a size, it provides a service according to the combination of the specific object and the size that has a high score indicating the first correlation, which is identified using a model that outputs a score indicating the first correlation.

[0168] As a result, the information processing apparatus 100 according to the embodiment can provide highly accurate services according to the size of the target user, based on the score indicating the first correlation.

[0169] Furthermore, the acquiring unit 131 acquires second evaluation information indicating a user's evaluation of the attributes of the identified targets. Furthermore, the generating unit 133 generates second correlation information indicating a second correlation between the attributes of different identified targets, based on the second evaluation information acquired by the acquiring unit 131. Furthermore, the providing unit 135 provides a service according to a combination of a identified target, a size, and an attribute that has a high score indicating the combination of the first correlation and the second correlation, which is identified using a model that outputs a score indicating the combination of the first correlation and the second correlation when a combination of a identified target, a size, and an attribute is input, based on the second correlation information generated by the generating unit 133.

[0170] As a result, the information processing device 100 according to the embodiment can provide services suited to the target user based on the first correlation and the second correlation, and can therefore appropriately provide services according to the size of the target user based on the first evaluation information and the second evaluation information from multiple users.

[0171] Furthermore, the generating unit 133 generates first correlation information indicating a first correlation between sizes of specific targets that have at least a part of the part that comes into contact with the user when worn in common but are in different categories.

[0172] As a result, the information processing apparatus 100 according to the embodiment can appropriately provide services according to the size of the target user across categories.

[0173] [9. Hardware Configuration] The terminal device 10, the information processing device 100, and the management server 200 according to the above-described embodiments are realized, for example, by a computer 1000 configured as shown in Fig. 13. Fig. 13 is a hardware configuration diagram showing an example of a computer that realizes the functions of the terminal device 10, the information processing device 100, and the management server 200. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0174] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0175] 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 predetermined communication network and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network.

[0176] 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 generated data to the output devices via the input / output interface 1600.

[0177] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1200. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1200 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.

[0178] For example, when the computer 1000 functions as the terminal device 10, the information processing device 100, and the management server 200 according to the embodiments, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200 to realize the functions of the control units 14, 130, and 230. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from other devices via a predetermined communication network.

[0179] [10. Other] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0180] Furthermore, the components of each device shown in the figure are conceptual functional components and do 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 depending on various loads, usage conditions, etc.

[0181] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0182] 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 implemented in other forms that include the embodiments described in the Disclosure of the Invention section and that have undergone various modifications and improvements based on the knowledge of those skilled in the art.

[0183] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit," etc. For example, an acquisition unit can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0184] 1. Information Processing Systems 10 Terminal Equipment 11 Communications Department 12 Input section 13 Output section 14 Control Unit 100 Information processing device 110 Communications Department 120 Storage section 121 First evaluation information storage unit 122 second evaluation information storage unit 123 User information storage unit 124 Specific target information storage unit 130 Control Unit 131 Acquisition Department 132 Specific part 133 Generation part 134 Calculation Unit 135 Provision Department 141 Receiving unit 142 Transmitter 200 Management Server 210 Communications Department 220 Storage section 230 Control Unit 231 Acquisition Department 232 Provision Department N Network

Claims

1. an acquisition unit that acquires first evaluation information indicating user evaluations of sizes of multiple types of specific targets; a generation unit that generates first correlation information indicating a first correlation between sizes of the plurality of types of specific targets based on the first evaluation information acquired by the acquisition unit, for use in a service according to the size of a target user; a providing unit that provides information according to the size of the target user to a terminal device that provides the service to the target user based on the first correlation information generated by the generating unit; An information processing device comprising:

2. The user is a user who tried on the specific object for the evaluation, or a user who wore the specific object after purchasing it. The information processing device according to claim 1 .

3. The user is the same user who commonly evaluated the sizes of the plurality of types of specific targets.

3. The information processing device according to claim 1.

4. the acquiring unit acquires second evaluation information indicating evaluations by the user with respect to a plurality of types of attributes of the identified target; the generation unit generates second correlation information indicating second correlations between attributes of the plurality of types of the identified targets based on the second evaluation information acquired by the acquisition unit, for use in a service according to the size of the target user; 4. The information processing device according to claim 1.

5. the providing unit provides information according to a size of the target user based on the first correlation information and the second correlation information generated by the generating unit. The information processing device according to claim 4 .

6. 1. A computer-implemented information processing method, comprising: an acquisition step of acquiring first evaluation information indicating user evaluations of sizes of multiple types of specific targets; a generating step of generating first correlation information indicating a first correlation between sizes of the plurality of types of specific targets based on the first evaluation information acquired by the acquiring step, for use in a service according to the size of the target user; a providing step of providing information according to the size of the target user to a terminal device for providing the service to the target user based on the first correlation information generated in the generating step; An information processing method including:

7. an acquisition step of acquiring first evaluation information indicating user evaluations of sizes of multiple types of specific targets; a generation step of generating first correlation information indicating a first correlation between sizes of the plurality of types of specific targets based on the first evaluation information acquired by the acquisition step, for use in a service according to the size of the target user; a providing step of providing information according to the size of the target user to a terminal device for providing the service to the target user based on the first correlation information generated by the generating step; An information processing program that causes a computer to execute the above.

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