JP2023088800A - Information processing device, information processing method and information processing program - Google Patents

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

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

Conventionally, there has been known a technique for proposing a specific object such as footwear or clothing suitable for a target user. For example, there is known a technique for proposing a specific target size suitable for a target user based on other users' evaluations of the specific target size.

Japanese Patent No. 5256362

However, with the conventional technology, it was not possible to provide a service suitable for the target user based on the correlation between the sizes of different specific targets.

The present application has been made in view of the above, and an object of the present application is to appropriately provide services according to the size of target users based on evaluation information from a plurality of users.

An information processing apparatus according to the present application includes an acquisition unit that acquires first evaluation information indicating a user's evaluation of one or more sizes of a specific target having a plurality of sizes, and based on the first evaluation information acquired by the acquisition unit: a generation unit for generating first correlation information indicating a first correlation between a plurality of different sizes of the specific target, and a size of the target user based on the first correlation information generated by the generation unit and a providing unit that provides a service according to.

According to one aspect of the embodiment, it is possible to appropriately provide a service according to the size of the target user based on evaluation information from a plurality of users.

FIG. 1 is a diagram illustrating a configuration example of an information processing system according to an embodiment. FIG. 2 is a diagram illustrating an example of information processing according to the embodiment; FIG. 3 is a diagram illustrating an example of second evaluation information according to the embodiment; FIG. 4 is a diagram illustrating a configuration example of a terminal device according to the embodiment; FIG. 5 is a diagram illustrating a configuration example of an information processing apparatus according to the embodiment; 6 is a diagram illustrating an example of a first evaluation information storage unit according to the embodiment; FIG. 7 is a diagram illustrating an example of a second evaluation information storage unit according to the embodiment; FIG. 8 is a diagram illustrating an example of a user information storage unit according to the embodiment; FIG. 9 is a diagram illustrating an example of a specific target information storage unit according to the embodiment; FIG. FIG. 10 is a diagram illustrating a configuration example of a management server according to the embodiment; FIG. 11 is a flowchart illustrating an example of information processing according to the embodiment; FIG. 12 is a diagram illustrating an example of information processing according to the modification. FIG. 13 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus.

Embodiments for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Also, in each of the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

(embodiment)
[1. Configuration of information processing system]
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 communicably connected by wire or wirelessly via a predetermined communication network (network N). FIG. 1 is a diagram showing a configuration example of an 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 .

The terminal device 10 is an information processing device used by a user. The terminal device 10 may be any device as long as it can implement the processing in the embodiments. Also, the terminal device 10 may be a device such as a smart phone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, or a PDA. The example shown in FIG. 2 shows a case where the terminal device 10 is a smart phone.

The terminal device 10 is, for example, a smart device such as a smartphone or a tablet, and is a mobile terminal device capable of communicating with an arbitrary server device via a wireless communication network such as 3G (Generation) or LTE (Long Term Evolution). is. The terminal device 10 has a screen such as a liquid crystal display, which has a touch panel function. operation may be accepted.

In FIG. 2, terminal _10-1 is used by user U11, terminal _10-2 is used by user U12, terminal _10-3 is used by user U13, and terminal _10-4 is used by user U14. In addition, below, when it is not necessary to distinguish between the terminal devices 10 ₁ , 10 ₂ , 10 ₃ and 10 ₄ , they are referred to as “terminal devices 10 ”. Moreover, when there is no need to distinguish between the users U11, U12, U13 and U14, they are simply referred to as "users". Moreover, below, the terminal device 10 may be described as a user. That is, hereinafter, the user can also be read as the terminal device 10 .

Note that FIG. 2 shows a case where the user is a user who has tried on a specific object in order to evaluate the size of the specific object (hereinafter referred to as an “evaluation user” as appropriate). For example, an evaluation user is a user who has expertise in evaluating the size of a specific target. For example, the evaluation user is a seller (clerk, store staff, etc.) who sells the specific target. The evaluation user uses, for example, a fitting tool (for example, an application) predetermined for the evaluation user to reply about the degree of fitting of the size of the specific target. It should be noted that the method by which the evaluation user answers the degree of fitting of the size of the specific target is not limited to the method using the fitting tool predetermined for the evaluation user. For example, the evaluating user may reply in the same way as the purchasing user, which will be described later.

The evaluation user tries on specific objects of a plurality of sizes in order, and answers the degree of fitting of each size of the specific object (for example, all sizes of the specific object). Therefore, in FIG. 2, the information processing apparatus 100 acquires evaluation information indicating the evaluation by the evaluation user for each size of the specific target. In other words, the information processing apparatus 100 acquires, for each evaluation user, evaluation information indicating the degree of fitting for each size of the specific target (for example, for each size of all sizes of the specific target).

In FIG. 12, terminal ₁₀₁₁ is used by user U21, terminal ₁₀₁₂ is used by user U22, terminal ₁₀₁₃ is used by user U23, and terminal ₁₀₁₄ is used by user U24. In addition, below, when there is no need to distinguish between the terminal devices 10 ₁₁ , 10 ₁₂ , 10 ₁₃ and 10 ₁₄ , they are referred to as “terminal devices 10 ”. Moreover, when there is no need to distinguish between the users U21, U22, U23 and U24, they are simply referred to as "users".

Note that FIG. 12 shows a case where the user is a user who has purchased and used a specific target (hereinafter referred to as a "purchasing user" as appropriate). For example, a purchasing user is a general user who has purchased a specific target at a predetermined online shopping mall. The purchasing user uses, for example, a questionnaire notified by a predetermined online shopping mall to answer the degree of fitting of the size of the specific target. It should be noted that the method by which the purchasing user answers the degree of fitting of the size of the specific object is not limited to the method using the questionnaire sent from the predetermined online shopping mall. For example, the purchasing user may reply on a specific target dedicated page (for example, product page) of a predetermined electronic shopping mall.

The purchasing user answers the degree of fitting of one size of the specific object purchased by him/herself. For this reason, in FIG. 12, the information processing apparatus 100 acquires evaluation information indicating the evaluation by the purchasing user for one size of the specific target. In other words, the information processing apparatus 100 acquires evaluation information indicating the degree of fitting of one size of the specific target for each purchasing user. It should be noted that, of course, if the purchase user has purchased a plurality of specific objects of different sizes and has answered the degree of fitting for each purchased size, the information processing apparatus 100 will provide the evaluation information for each size. get.

In this way, the user is a user who has actually worn (or worn) the specific target at least once, such as an evaluation user who has tried on the specific target, or a purchasing user who has purchased and used the specific target. Note that the user is not limited to the evaluating user or the purchasing user, and may be any user as long as the user has actually worn (or worn) the specific target at least once.

The information processing device 100 is an information processing device for appropriately providing services according to the size of target users based on evaluation information from a plurality of users, and is realized by, for example, a server device, a cloud system, or the like. . For example, the information processing apparatus 100 has a function of specifying the correlation between different sizes of specific targets based on evaluation information indicating user's evaluation of the size of the specific targets. In addition, the evaluation information indicating the user's evaluation of the size of the specific target is hereinafter appropriately referred to as "first evaluation information". Further, the correlation between the sizes of different identification targets, which is identified based on the first evaluation information, is hereinafter appropriately referred to as "first correlation", and the information indicating the first correlation is referred to as "first correlation information.

The management server 200 is an information processing device for managing a predetermined online shopping mall that provides specific objects, and is realized by, for example, a server device, a cloud system, or the like. For example, the management server 200 has a function of providing a specific target purchasing user with a questionnaire for evaluating the specific target. It should be noted that hereinafter, the specific target is not particularly limited, and may be anything that can be worn (or worn) by the user, such as footwear or clothes. For example, the specific target may be sneakers, sandals, boots, pumps, dress shoes, running shoes, and the like. Further, for example, the specific target may be tops, dresses, dresses, T-shirts, bottoms, skirts, socks, and the like. Also, the specific object may be a ring, a brooch, or the like.

Note that FIG. 1 shows a case where the information processing apparatus 100 and the management server 200 are separate apparatuses, but the information processing apparatus 100 and the management server 200 may be integrated.

[2. Example of information processing]
FIG. 2 is a diagram showing an example of information processing of the information processing system 1 according to the embodiment. In FIG. 2, it is assumed that evaluations are received from evaluation users via the terminal device 10 . In FIG. 2, a case where evaluations are received from users U11 to U14 as evaluation users who evaluate the size of a specific target will be described as an example, but the number of evaluation users is not particularly limited. The number of evaluation users is not limited to the four users U11 to U14, and may be one, two, three, or five or more.

Note that the users U11 to U14 are assumed to be evaluated users with similar sizes, for example, in order to specify the first correlation using the evaluations of the users U11 to U14 for each size. The users U11 to U14 may be rating users identified based on rating user size information, for example. In this way, the users U11 to U14 are evaluation users whose evaluation tendencies are estimated to be similar to those of the evaluation users. Note that the users U11 to U14 may be, for example, evaluation users identified based on evaluation trends of evaluation users. Note that the size information of the evaluating user may be measured before the evaluation, or may be measured during the evaluation, and is not particularly limited.

Also, in order to specify the first correlation between sizes, it is assumed that the evaluation user who evaluates each size is the same. Note that the target user to whom the service is provided according to the size is any user who is related to trying on or purchasing one size among the sizes for which the first correlation is specified. shall be good.

The degree of fitting is a degree based on the feeling of size felt by the evaluation user, such as looseness, tightness, pain, or a specific part of the body protruding from the specific object. It is assumed that the answer is "OK" or "BAD". For example, by selecting "GOOD" from "GOOD", "OK", and "BAD" for the size M11 of the specific target, the degree of fitting of the size M11 of the specific target is answered as "GOOD". shall be Then, it is assumed that the first evaluation information indicating that the degree of fitting of the specific target size M11 is “GOOD” is transmitted to the information processing apparatus 100 .

For convenience of explanation, the case where the specific object is footwear will be described below as an example. That is, the description will be made assuming that the specific targets AA1 to AA3 are footwear. In FIG. 2, a case where specific targets AA1 to AA3 are evaluated as specific targets evaluated by the evaluation user will be described as an example, but the number of specific targets is not particularly limited. The number of specific targets is not limited to the three specific targets AA1 to AA3, and may be one, two, or four or more. For example, the number of specific targets may be all products that can be offered in a predetermined online shopping mall, or a part of all products.

Also, each specific target has a plurality of sizes in increments of 5 mm. In FIG. 2, a case where the multiple sizes of each specific target are 26 cm, 26.5 cm, 27 cm, and 27.5 cm will be described as an example, but the multiple sizes of each specific target are not particularly limited. and Also, the number of multiple sizes for each specific target is not particularly limited.

The information processing apparatus 100 acquires evaluation information DT11 indicating evaluations by the users U11 to U14 for each size of the specific targets AA1 to AA3 (step S101). In the evaluation information DT11, "⊚" is "GOOD", "o" is "OK", and "x" is "BAD".

In the evaluation information DT11, for example, for each size of the specific targets AA1 to AA3, the user U11 determines that the specific target AA1 of 26 cm is "x", the specific target AA1 of 26.5 cm is "o", and the specific target AA1 of 27 cm is "o". is "◎", 27.5 cm for specific target AA1 is "×", 26 cm for specific target AA2 is "×", 26.5 cm for specific target AA2 is "◎", 27 cm for specific target AA2 is "○", specific 27.5 cm for target AA2 is "x", 26 cm for specific target AA3 is "x", 26.5 cm for specific target AA3 is "○", 27 cm for specific target AA3 is "◎", 27.5 cm for specific target AA3 indicates that it was evaluated as "x".

In addition, the evaluation information DT11 indicates that, for example, the size of 26 cm of the specific target AA1 was evaluated as "x" by the user U11, "x" by the user U12, "x" by the user U13, and "x" by the user U14. indicates that

The user U11, for example, tries on each size of the specific targets AA1 to AA3 in order, and transmits the first evaluation information of each size of each specific target. At this time, the user U11 may transmit the first evaluation information for each size, for each of a plurality of sizes, for each specific target, or for each of a plurality of specific targets. , and transmission of the first evaluation information is not particularly limited.

The information processing apparatus 100 acquires and aggregates the first evaluation information transmitted from each evaluation user (step S102). The evaluation information DT11 is obtained by collecting and storing the first evaluation information transmitted by each evaluation user by the information processing apparatus 100 .

The information processing apparatus 100 identifies a first correlation between sizes of different identification targets among the sizes of the identification targets AA1 to AA3 based on the acquired first evaluation information (step S103).

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

Specifically, the information processing apparatus 100 identifies, among the sizes of the specific target AA1, the sizes for which the degree of fitting is highly evaluated by each evaluation user, and the size of the specific target AA1 with the high evaluation and the size of the specific target AA2. A first correlation with each size and each size of the specific target AA3 is identified.

Here, among the sizes of the specific target AA1, all of the users U11 to U14 have evaluated the 27 cm specific target AA1 as "excellent." As the size, 27 cm of the specific target AA1 is specified. Then, the information processing apparatus 100 identifies a 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.

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

On the other hand, among the sizes of the specific target AA3, all of the users U11 to U14 evaluated the 27 cm specific target AA3 as "excellent." Therefore, it is assumed that the first correlation between 27 cm of the specific target AA1 and 27 cm of the specific target AA3 is high. The information processing apparatus 100 calculates a high score indicating the first correlation between 27 cm of the specific target AA1 and 27 cm of the specific target AA3.

In addition, half of the users U11 to U14 evaluated the size of the specific target AA2 of 26.5 cm as “excellent” and “good”, so the evaluation of the specific target AA1 of 27 cm different. Therefore, the first correlation between 27 cm of the specific target AA1 and 26.5 cm of the specific target AA2 is lower than the first correlation with 27 cm of the specific target AA3, but the first correlation with 26 cm of the specific target AA2 assumed to be higher. The information processing apparatus 100 sets the score indicating the first correlation between the specific target AA1 of 27 cm and the specific target AA2 of 26.5 cm to be lower than the score indicating the first correlation between the specific target AA3 of 27 cm and the specific target AA3. It is calculated to be higher than the score showing the first correlation with 26 cm of AA2.

In addition, among the sizes of the specific target AA2, since all of the users U11 to U14 evaluated the 27 cm specific target AA2 as "○", the evaluation for the 27 cm specific target AA1 and the 26 cm specific target AA2 slightly more than .5 cm. Therefore, the first correlation between the specific target AA1 of 27 cm and the specific target AA2 of 27 cm is lower than the first correlation with the specific target AA2 of 26.5 cm, but the first correlation with the specific target AA2 of 26 cm assumed to be higher. The information processing apparatus 100 sets the score indicating the first correlation between the specific target AA1 of 27 cm and the specific target AA2 of 27 cm to be lower than the score indicating the first correlation of the specific target AA2 of 26.5 cm. It is calculated to be higher than the score showing the first correlation with 26 cm of AA2.

Then, the information processing apparatus 100 calculates a score indicating a 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, thereby obtaining a score of 27 cm of the specific target AA1, A first correlation between each size of the specific target AA2 and each size of the specific target AA3 is specified.

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

For example, the information processing apparatus 100 identifies, among the sizes of the specific objects, the sizes for which the degree of fitting is highly evaluated by each evaluation user, and identifies the first correlation between the sizes of the specific objects highly evaluated. may For example, the information processing apparatus 100 identifies sizes (for example, 26.5 cm and 27 cm) for which the degree of fitting is highly evaluated by each evaluation user among the sizes of the specific target AA2 in addition to the size of the specific target AA1 of 27 cm. A first correlation may be specified between the size of the specific target AA2 with a high evaluation and the size of 27 cm of the specific target AA1. Further, for example, the information processing apparatus 100 specifies, in addition to the size of 27 cm of the specific target AA1, among the sizes of the specific target AA3, the size (for example, 27 cm) for which each evaluation user highly evaluated the degree of fitting, and the specified evaluation A first correlation may be identified between the size of the specific target AA3 with a high , and 27 cm of the specific target AA1.

Further, in the above-described embodiment, the information processing apparatus 100 identifies 27 cm of the specific target AA1 among the sizes of the specific target AA1 as a reference for identifying the first correlation, and then specifies 27 cm of the specific target AA1. , to identify the first correlation with each size of each identification target, but the present invention is not limited to this example.

For example, the information processing apparatus 100 calculates a score indicating a first correlation between sizes of each specific target, and then specifies a first correlation between sizes highly evaluated by each evaluation user. good too.

The information processing apparatus 100 generates first correlation information based on the specified first correlation (step S104).

The information processing apparatus 100 generates the first correlation information SDT11, for example, based on the first correlation between the sizes highly evaluated by each evaluation user.

For example, the first correlation information SDT11 has a high first correlation with 27 cm of the specific target AA3 and an average first correlation with 26.5 cm of the specific target AA2 with respect to 27 cm of the specific target AA1. , indicates that the first correlations with 27 cm of the specific target AA2 and 26.5 cm of the specific target AA3 are slightly low, although not low.

The information processing apparatus 100 provides a service according to the size of the target user based on the generated first correlation information (step S105). Note that the target user is a user to whom the service is provided according to the size. The target user may be any user who is related to trying on or purchasing one size among the sizes for which the first correlation is specified. Of course, the target user may be an evaluation user or a purchasing user.

For example, when the target user has tried on or purchased a 27 cm specific target AA1, the information processing apparatus 100 has a high first correlation with the 27 cm specific target AA1 based on the first correlation information SDT11. is 27 cm of the specific target AA3, information for proposing to try on or purchase the 27 cm specific target AA3 is provided.

Further, for example, when the 27 cm specific target AA1 does not match the taste of the target user, or when there is no stock at the time when the target user accesses, the information processing apparatus 100 determines based on the first correlation information SDT11 27 cm of the specific target AA1 and the next highest first correlation is the 26.5 cm of the specific target AA2. good too. Further, the information processing apparatus 100, for example, determines that the 26.5 cm of the specific target AA3, which has the highest first correlation with the 27 cm of the specific target AA1 next to the 26.5 cm of the specific target AA2, is the target user's preference. If the fit is better than 26.5 cm for AA2, information may be provided to suggest fitting or purchasing a specific target AA3 of 26.5 cm. For example, the specific target AA3 belongs to a brand that matches the taste of the target user.

Processing for providing a service in consideration of the target user's preference will be described below.

In addition, although a brand is mentioned as an example and demonstrated as an attribute of a specific object, it shall not be limited to this example. For example, attributes to be specified may be categories such as clothes or footwear, tops or bottoms, dresses or dresses, sneakers or sandals. Also, for example, the attribute of the specific target may be the specific target itself. In this case, the service is provided in consideration of the target user's preference for the specific target himself/herself.

In addition, the evaluation information indicating the evaluation by the user (e.g., the evaluation user or the purchase user) for the attribute of the specific target is hereinafter appropriately referred to as "second evaluation information". Further, the correlation between attributes with different specific targets, which is specified based on the second evaluation information, is hereinafter referred to as a "second correlation", and the information indicating the second correlation is referred to as a "second correlation information.

The information processing apparatus 100 acquires evaluation information DT21 (see FIG. 3) indicating evaluations of the brands of the specific targets AA1 to AA3 by the users U11 to U14. FIG. 3 is a diagram illustrating an example of second evaluation information according to the embodiment; In the evaluation information DT21, "GOOD", "OK", and "BAD" indicate the degree of preference, since they are responses to preferences for each brand.

For example, when "GOOD" is selected from among "GOOD", "OK", and "BAD" for brand BB1, the degree of preference for brand BB1 is answered as "GOOD". Assume that the evaluation information is transmitted to the information processing apparatus 100 .

Further, it is assumed that the specific target AA1 belongs to the brand BB1, the specific target AA2 belongs to the brand BB2, and the specific target AA3 belongs to the brand BB3. When the attribute of the specific target is the specific target itself, it can be read that the specific target AA1 belongs to the specific target AA1, the specific target AA2 belongs to the specific target AA2, and the specific target AA3 belongs to the specific target AA3. shall be

The evaluation information DT21 indicates, for example, that the user U11 evaluated each brand as "⊚" for the brand BB1, "∘" for the brand BB2, and "⊚" for the brand BB3.

The evaluation information DT21 also indicates that the brand BB1 has been evaluated by the user U11 as "⊚", the user U12 as "⊚", the user U13 as "⊚", and the user U14 as "◯".

The information processing apparatus 100 acquires and aggregates the second evaluation information transmitted from each evaluation user. The evaluation information DT21 is obtained by collecting and storing the second evaluation information transmitted by each evaluation user by the information processing apparatus 100 .

The information processing apparatus 100 identifies a second correlation between brands whose identification targets are different based on the acquired second evaluation information.

The information processing device 100 identifies, for example, the second correlation between the brand BB1 and the brands BB2 and BB3.

A majority of the users U11 to U14 evaluate the brand BB1 as "excellent". Also, half of the users U11 to U14 evaluated the brand BB2 as "x". In addition, the majority of the users U11 to U14 evaluated the brand BB3 as "excellent".

Therefore, since the evaluation of brand BB1 and the evaluation of brand BB3 are more similar than the evaluation 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. be done. The information processing device 100 calculates a score indicating the second correlation between the brand BB1 and the brand BB3 to be higher than a score indicating the second correlation with the brand BB2.

The information processing apparatus 100 identifies the second correlations between the brand BB1 and the brands BB2 and BB3 by calculating scores indicating the second correlations between the brand BB1 and the brands BB2 and BB3.

The information processing apparatus 100 generates second correlation information based on the specified second correlation.

The information processing apparatus 100 provides a service according to the preferences of the target user based on the generated second correlation information. The target user may be any user who is related to trying on or purchasing one of the brands for which the second correlation is specified.

For example, when the target user has tried on or purchased a specific target of the brand BB1, the information processing apparatus 100 determines that the brand having a high second correlation with the brand BB1 is the brand BB3 based on the second correlation information. Therefore, the information for suggesting the try-on or purchase of the specific target of the brand BB3 is provided.

The information processing apparatus 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 apparatus 100 adds the score indicating the second correlation to the score indicating the first correlation to calculate the total score, thereby proposing the size of the specific target with the high total score. provide information.

Note that in the above embodiment, the information processing apparatus 100 may generate a model that outputs a score indicating the first correlation when a combination of a specific target and a size is input. At this time, the information processing apparatus 100 may generate, for example, a model learned by using sizes with high evaluations from each evaluation user as positive examples. Then, the information processing apparatus 100 may specify a combination of a specific target having a high score and a size among the scores output using the generated model, and provide the service. For example, based on the user information of the target user, the information processing apparatus 100 inputs into the model a combination of the specific target and the size that the target user tried on or purchased, and outputs the specific target and size with the highest score output from the model. , and provide information for proposing a combination of the identified specific object and the size.

In the above-described embodiment, when a combination of a specific target, a size, and an attribute is input, the information processing apparatus 100 outputs a total score obtained by adding the score indicating the second correlation to the score indicating the first correlation. model may be generated. At this time, the information processing apparatus 100 may generate, for example, a model learned by using sizes and attributes highly evaluated by each evaluation user as positive examples. Then, the information processing apparatus 100 may specify a combination of a specific target having a high total score, a size, and an attribute among the total scores output using the generated model, and provide the service. For example, based on the user information of the target user, the information processing apparatus 100 inputs into the model the combination of the specific object that the target user has tried on or purchased, the size, and the attribute, and the specified total score output from the model is the highest. Information may be provided for identifying combinations of objects, sizes, and attributes, and proposing combinations of the identified specific objects, sizes, and attributes.

In the above-described embodiment, the information processing apparatus 100 may generate, for example, a model indicating the relationship of the degree of fit between each size of each specific target and the sizes of the users U11 to U14. For example, models based on sigmoid functions. For example, this is a model in which the more users U11 to U14 evaluate their size as being too large, the higher the positive score, and the more they evaluate the size as being too small, the higher the negative score. When the size information of the target user is input, the information processing apparatus 100 outputs a score indicating the first correlation or a total score obtained by adding the score indicating the second correlation to the score indicating the first correlation. may be generated. It should be noted that the timing of measuring the size information of the target user is not particularly limited.

In the above embodiment, the information processing apparatus 100 identifies the first correlation between the sizes of the specific targets AA1 to AA3 having the same category of footwear. A first correlation between one size may be identified. In addition, when at least a part of the grounding portion is common to the user (for example, the evaluating user or the purchasing user) when wearing the item, it is assumed that there is a high possibility that the first correlation can be identified. For example, sneakers and socks have a common grounding portion on the user's feet, and a dress and a dress have a common grounding portion on the user's upper body. The information processing apparatus 100 may specify, for example, a first correlation between sizes of one size of sneakers (an example of footwear) and one size of socks (an example of clothing). Further, the information processing apparatus 100 may specify, for example, a first correlation between sizes of one dress (one category of clothing) and one size of a dress (two categories of clothing). good. In this way, the information processing apparatus 100 identifies the first correlation between the sizes of the specific objects of different categories, although at least a part of the portion that touches the user when worn is common, and the first correlation information may be generated.

It should be noted that, when predetermined as a combination of identification targets of different categories with a high possibility of identifying the first correlation, it is not particularly necessary to limit at least a part of the grounding portion to the user when wearing it in common. Assume that there is

When the information processing apparatus 100 identifies the first correlation between one size of the category difference identification target and generates the first correlation information, the category difference Information may be provided to suggest trying on or purchasing a specific object of one size. For example, when target information including a specific target that is sneakers and the size of the sneakers is input as the user information of the target user, the information processing apparatus 100 selects one size according to the size of the target user. Information may be provided to suggest trying on or purchasing socks.

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

(Communication unit 11)
The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. 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 apparatus 100 and the like via the predetermined network N.

(Input unit 12)
The input unit 12 receives various operations from the evaluation user. In the example shown in FIG. 2, various operations from users U11 to U14 are accepted. For example, the input unit 12 may receive various operations from the evaluation user via the display surface using a touch panel function. The input unit 12 may also accept various operations from buttons provided on the terminal device 10 or from a keyboard or mouse connected to the terminal device 10 .

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

(control unit 14)
The control unit 14 is, for example, a controller, and a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like stores various programs stored in a storage device inside the terminal device 10 into a RAM (Random Access Memory). ) as a work area. For example, the various programs include application programs installed in the terminal device 10 . For example, the various programs include an application program for displaying information transmitted from the information processing apparatus 100 . Also, the control unit 14 is implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 4, the control unit 14 has a receiving unit 141 and a transmitting unit 142, and implements or executes the information processing operation described below.

(Receiver 141)
The receiving unit 141 receives various information. The receiving unit 141 receives various information from an external information processing device. The receiving unit 141 receives various information from other information processing devices such as the information processing device 100 .

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

The receiving unit 141 receives, for example, the degree of fitting answered by the evaluation user for each size of each specific target.

(Sending unit 142)
The transmission unit 142 transmits various types of information to an external information processing device. The transmission unit 142 transmits various types of information to other information processing devices such as the information processing device 100 .

The transmission unit 142 transmits, for example, the first evaluation information indicating the evaluation by the evaluation user for each size of each specific target.

[4. Configuration of Information Processing Device]
Next, the configuration of the information processing apparatus 100 according to the embodiment will be described using FIG. FIG. 5 is a diagram illustrating a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 5, the information processing apparatus 100 has a communication section 110, a storage section 120, and a control section . The information processing apparatus 100 has an input unit (for example, a keyboard, a mouse, etc.) that receives various operations from the administrator of the information processing apparatus 100, and a display unit (for example, a liquid crystal display, etc.) for displaying various information. You may

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

(storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM or 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 .

The first evaluation information storage unit 121 stores first evaluation information indicating an evaluation by an evaluation user 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".

“User ID” indicates identification information for identifying an evaluation user. "Specific target" indicates a specific target. "First evaluation information" indicates the first evaluation information evaluated by the evaluation user.

That is, in FIG. 6, the specific target evaluated by the evaluation user identified by the user ID "U11" is "specific target AA1", and the first evaluation information is "size 26 cm; evaluation "x", size 26.5 cm. evaluation "O", size 27 cm; evaluation "⊚", size 27.5 cm; evaluation "x".

The second evaluation information storage unit 122 stores second evaluation information indicating the evaluation of each brand by evaluation users. Here, 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".

“User ID” indicates identification information for identifying an evaluation user. "Second evaluation information" indicates the second evaluation information evaluated by the evaluation user.

That is, in FIG. 7, the second evaluation information evaluated by the evaluation user identified by the user ID "U11" is "Brand BB1: Evaluation 'A', Brand BB2: Evaluation 'O', Brand BB3: Evaluation 'A'. ” shows an example.

The user information storage unit 123 stores user information of evaluation users. Here, FIG. 8 shows an example of the user information storage unit 123 according to the embodiment. As shown in FIG. 8, the user information storage unit 123 has items such as "user ID" and "user information".

“User ID” indicates identification information for identifying an evaluation user. “User information” indicates user information (for example, measurement information) of the evaluation user. In the example shown in FIG. 8, conceptual information such as "user information #11" and "user information #12" is stored in "user information". ; measurement time: September 2021" is stored.

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".

The specified target information storage unit 124 stores target information of specified targets. For example, it stores target information of a specific target 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".

"Specific target" indicates a specific target. "Target information" indicates target information of a specific target (for example, size information of a specific target). In the example shown in FIG. 9, conceptual information such as "object information #11" and "object information #12" is stored in "object information". Information such as ".5 cm, 27 cm, 27.5 cm" is stored.

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

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

As shown in FIG. 5, the control unit 130 includes an acquisition unit 131, a specification unit 132, a generation unit 133, a calculation unit 134, and a provision unit 135, and implements the information processing operation described below. or run. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 5, and may be another configuration as long as it performs information processing described later.

(Acquisition unit 131)
Acquisition unit 131 acquires various types of information. Acquisition unit 131 acquires various types of information from an external information processing device. The acquisition unit 131 acquires various types of information from other information processing devices such as the terminal device 10 .

Acquisition unit 131 acquires various types of information from 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 . The acquisition unit 131 also stores the acquired various information in the storage unit 120 . The acquisition unit 131 stores 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 .

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

The acquisition unit 131 acquires, for example, second evaluation information indicating the evaluation of each brand by the evaluation user. In other words, the acquiring unit 131 acquires the second evaluation information indicating the preference of each brand for each evaluated user.

(Specifying unit 132)
For example, based on the first evaluation information acquired by the acquiring unit 131 , the identifying unit 132 identifies the first correlation between one size of different specific targets among a plurality of different specific target sizes.

For example, the identifying unit 132 identifies, among the sizes of one specific target, a size for which each evaluation user highly evaluated the degree of fitting, and specifies the size of the one specific target with a high evaluation and the size of each of the other specific targets. A first correlation with each size is identified.

The specifying unit 132, for example, based on the score indicating the first correlation calculated by the calculating unit 134 to be described later, determines the size of one specified target with a high evaluation and each size of each of the other specified targets. A first correlation is identified.

For example, the specifying unit 132 specifies, among the sizes of the specific targets, the sizes for which the degree of fitting is highly evaluated by each evaluation user, and specifies the first correlation between the sizes of the specified specific targets having high evaluations.

The specifying unit 132 specifies the first correlation between the sizes highly evaluated by each evaluating user, for example, based on the score indicating the first correlation calculated by the calculation unit 134 described later.

The identifying unit 132 identifies the second correlation between brands whose specific targets are different, based on the second evaluation information acquired by the acquiring unit 131, for example.

The information processing apparatus 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 to be described later.

(Generating unit 133)
The generation unit 133 generates the first correlation information based on the first correlation identified by the identification unit 132, for example.

The generation unit 133 generates the first correlation information, for example, based on the first correlation between the sizes highly evaluated by each evaluation user.

The generation unit 133 generates the second correlation information based on the second correlation identified by the identification unit 132, for example.

For example, the generation unit 133 makes a model that outputs a score indicating the first correlation when a combination of a specific target and a size is input.

The generating unit 133 generates, for example, a model that is learned by using sizes with high evaluations from each evaluation user as positive examples.

For example, when a combination of a specific target, a size, and an attribute is input, the generating unit 133 generates a model that outputs a total score obtained by adding a score indicating a second correlation to a score indicating the first correlation.

The generating unit 133 generates, for example, a model that is learned by using, as positive examples, the sizes and attributes that are highly evaluated by each evaluation user.

(Calculation unit 134)
The calculation unit 134 calculates, for example, a score indicating the first correlation between each size of each specific target.

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

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

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

For example, the calculation unit 134 adds the score indicating the second correlation to the score indicating the first correlation to calculate the total score.

(Providing unit 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.

The providing unit 135 provides, for example, information for suggesting a try-on or purchase of a specific target of one size.

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.

The providing unit 135 provides, for example, information for proposing a try-on or purchase of a specific target of one brand.

The providing unit 135 provides, for example, information for proposing to try on or purchase a specific object of one size having a high score (including a total score) calculated by the calculating unit 134 .

The providing unit 135 provides, for example, information for proposing a size of a specific target with a high score (including a total score).

[5. Management server configuration]
Next, the configuration of the management server 200 according to the embodiment will be described using FIG. 10 . FIG. 10 is a diagram showing a configuration example of the management server 200 according to the embodiment. As shown in FIG. 10 , the management server 200 has a communication section 210 , a storage section 220 and a control section 230 . Note that the management server 200 may have an input unit for receiving various operations from the administrator of the management server 200 and a display unit for displaying various information.

(Communication unit 210)
The communication unit 210 is implemented by, for example, a NIC. The communication unit 210 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the information processing apparatus 100 and the like via the network N.

(storage unit 220)
The storage unit 220 is implemented by, for example, a semiconductor memory device such as a RAM or flash memory, or a storage device such as a hard disk or optical disk.

The storage unit 220 stores information similar to that of the specific target information storage unit 124 . Therefore, the description is omitted.

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

As shown in FIG. 10, the control unit 230 has an acquisition unit 231 and a provision unit 232, and implements or executes the information processing operation described below. Note that the internal configuration of the control unit 230 is not limited to the configuration shown in FIG. 10, and may be another configuration as long as it performs information processing to be described later.

(Acquisition unit 231)
Acquisition unit 231 acquires various types of information. Acquisition unit 231 acquires various types of information from an external information processing device. Acquisition unit 231 acquires various types of information from other information processing apparatuses such as information processing apparatus 100 .

Acquisition unit 231 acquires various types of information from storage unit 220 . In addition, the acquisition unit 231 stores the acquired various information in the storage unit 220 .

The acquisition unit 231 acquires target information of a specific target provided by a predetermined online shopping mall.

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

[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 flow chart showing the procedure of information processing by the information processing system 1 according to the embodiment.

As shown in FIG. 11, the information processing apparatus 100 acquires first evaluation information indicating the evaluation by the evaluation user for each size to be specified (step S201).

The information processing apparatus 100 generates first correlation information indicating the first correlation based on the acquired first evaluation information (step S202).

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

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

In the above embodiment, the case where the specific target is evaluated by the evaluation user has been described. Hereinafter, in the modified example, a case where the specific target is evaluated by the purchasing user will be described. Note that descriptions similar to those in FIG. 2 will be omitted as appropriate.

For convenience of explanation, the case where the specific target is evaluated only by the purchasing user will be described, but the modification includes the case where the specific target is evaluated by the evaluating user and then by the purchasing user. . On the other hand, in the above embodiment, similarly, the case where the specific target was evaluated only by the evaluation user was described. including cases.

Depending on the specific target, the number of purchasing users who have purchased may be small, and the number of evaluations may not be sufficient. For example, the specific target may be a new product. Here, the case where the number of evaluations is not sufficient means that in providing a service according to the size of the target user, it is highly accurate, for example, in order to propose a combination of a specific target and a size that matches the size of the target user. is when the number of evaluations is not sufficient. For this reason, by having evaluation users try on each specific target of all sizes and evaluate it, even if the number of evaluations by purchasing users is not sufficient, it is possible to provide highly accurate services according to the target user's size. It becomes possible.

Also, it may be difficult to get the evaluation user to try on and evaluate each particular object in all and all sizes. For this reason, for example, for a specific target for which there is no evaluation information of an evaluation user, by using the evaluation information of a purchasing user, it is possible to provide a highly accurate service according to the size of the target user.

FIG. 12 is a diagram illustrating an example of information processing according to the modification.

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

The information processing apparatus 100 acquires evaluation information DT12 indicating evaluations by the users U21 to U24 for each size of the specific targets AA1 to AA3 (step S301).

The evaluation information DT12 indicates, for example, that the user U11 evaluated the 26 cm of the specific target AA1 as "x". Note that the "-" given to the specific targets AA1 of 26.5 cm, 27 cm, and 27.5 cm, and the "-" given to the sizes of the specific targets AA2 and AA3 are determined by the user U11. Indicates no rating.

Also, in the evaluation information DT12, for example, "-" assigned to users U22 to U24 of 26 cm of the specific target AA1 indicates that there is no evaluation for the 26 cm of the specific target AA1.

User U11 purchases and uses, for example, a 26 cm specific target AA1, and transmits first evaluation information for the 26 cm specific target AA1.

The information processing apparatus 100 acquires and aggregates the first evaluation information transmitted from each purchasing user (step S302). The evaluation information DT12 is obtained by collecting and storing the first evaluation information transmitted by each purchasing user by the information processing apparatus 100 .

It should be noted that the processing after step S302 is the same as in the above-described embodiment, so description thereof will be omitted.

[8. effect〕
As described above, the information processing apparatus 100 according to the embodiment has 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. Based on the first evaluation information acquired by the acquisition unit 131, the generation unit 133 generates first correlation information indicating a first correlation between a plurality of different sizes of specific targets. The providing unit 135 provides a service according to the size of the target user based on the first correlation information generated by the generating unit 133 .

Accordingly, the information processing apparatus 100 according to the embodiment can provide a service suitable for the target user based on the first correlation. It is possible to appropriately provide services according to the size of

Also, the user is a user who has tried on the specific target for evaluation, or a user who has purchased and used the specific target.

As a result, the information processing apparatus 100 according to the embodiment can provide a highly accurate service according to the size of the target user based on the evaluation information from the evaluation user or the purchase user.

Moreover, the user is the same user who has evaluated a plurality of different specific target sizes in common.

Accordingly, the information processing apparatus 100 according to the embodiment can provide a highly accurate service according to the size of the target user based on the evaluation information from the same user.

In addition, when a combination of a specific target and a size is input, the providing unit 135 selects a specific target having a high score indicating the first correlation and the size, which is specified using a model that outputs a score indicating the first correlation. We provide services according to the combination of

Accordingly, the information processing apparatus 100 according to the embodiment can provide a highly accurate service according to the size of the target user based on the score indicating the first correlation.

The acquisition unit 131 also acquires second evaluation information indicating the user's evaluation of the attribute of the specific target. The generation unit 133 also generates second correlation information indicating a second correlation between a plurality of different specific target attributes based on the second evaluation information acquired by the acquisition unit 131 . Further, based on the second correlation information generated by the generating unit 133, the providing unit 135, when inputting the combination of the specific target, the size, and the attribute, indicates the combination of the first correlation and the second correlation. A service is provided according to a combination of a specific target having a high score indicating a combination of a first correlation and a second correlation, and a size and an attribute, which are identified using a model that outputs scores.

Accordingly, the information processing apparatus 100 according to the embodiment can provide a service suitable for the target user based on the first correlation and the second correlation. Based on the second evaluation information, it is possible to appropriately provide a service according to the size of the target user.

In addition, the generation unit 133 generates first correlation information indicating a first correlation between specific target sizes having at least a part of the contact area with the user when worn but having different categories.

Thereby, the information processing apparatus 100 according to the embodiment can appropriately provide services according to the size of the target user across categories.

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

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

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

The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice, through an input/output interface 1600 . CPU 1100 acquires data from an input device via input/output interface 1600 . CPU 1100 also outputs the generated data to an output device via input/output interface 1600 .

Media interface 1700 reads programs or data stored in recording medium 1800 and provides them to CPU 1100 via RAM 1200 . CPU 1100 loads such a program from recording medium 1800 onto RAM 1200 via media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or 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. etc.

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 embodiment, the CPU 1100 of the computer 1000 executes the program loaded on the RAM 1200 to control the control units 14 and 130. and 230 functions. CPU 1100 of computer 1000 reads these programs from recording medium 1800 and executes them, but as another example, these programs may be obtained from another device via a predetermined communication network.

[10. others〕
Further, among the processes described in the above embodiments, all or part of the processes described as being automatically performed can be manually performed, or the processes described as being performed manually can be performed manually. All or part of this can also be done automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

Further, the embodiments described above can be appropriately combined within a range that does not contradict the processing contents.

As described above, some of the embodiments of the present application have been described in detail based on the drawings. It is possible to carry out the invention in other forms with modifications.

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

1 information processing system 10 terminal device 11 communication unit 12 input unit 13 output unit 14 control unit 100 information processing device 110 communication unit 120 storage unit 121 first evaluation information storage unit 122 second evaluation information storage unit 123 user information storage unit 124 identification Target information storage unit 130 control unit 131 acquisition unit 132 identification unit 133 generation unit 134 calculation unit 135 provision unit 141 reception unit 142 transmission unit 200 management server 210 communication unit 220 storage unit 230 control unit 231 acquisition unit 232 provision unit N network

Claims (8)

an acquisition unit that acquires first evaluation information indicating a user's evaluation of one or more sizes of a specific target having a plurality of sizes;
a generation unit that generates first correlation information indicating a first correlation between a plurality of different sizes of the specific targets based on the first evaluation information acquired by the acquisition unit;
a providing unit that provides a service according to the size of a target user based on the first correlation information generated by the generating unit;
An information processing device comprising: The information processing apparatus according to claim 1, wherein the user is a user who has tried on the specific object for the evaluation, or a user who has purchased and used the specific object. The information processing apparatus according to claim 1 or 2, wherein the user is the same user who has evaluated a plurality of different sizes of the specific targets in common. The providing unit
When a combination of the specific target and the size is input, the specific target having a high score indicating the first correlation, which is identified using a model that outputs a score indicating the first correlation, and the size 4. The information processing apparatus according to any one of claims 1 to 3, wherein the service is provided according to the combination. The acquisition unit
Acquiring second evaluation information indicating the user's evaluation of the attribute of the specific target;
The generating unit
generating second correlation information indicating a second correlation between a plurality of different attributes of the specific target based on the second evaluation information acquired by the acquisition unit;
The providing unit
When a combination of the specific object, the size, and the attribute is input based on the second correlation information generated by the generation unit, a score indicating the combination of the first correlation and the second correlation is generated. Providing the service according to the combination of the specified object, the size, and the attribute, which have a high score indicating the combination of the first correlation and the second correlation, which are specified using the model to be output. The information processing apparatus according to any one of claims 1 to 4, characterized by: The generating unit
Generating the first correlation information indicating the first correlation between the sizes of the specific targets of different categories, although at least a part of the portion that touches the user when worn is common. 6. The information processing device according to any one of 1 to 5. A computer-executed information processing method comprising:
an acquisition step of acquiring first evaluation information indicating a user's evaluation of one or more sizes of a specific object having a plurality of sizes;
a generating step of generating first correlation information indicating a first correlation between a plurality of different sizes of the specific targets based on the first evaluation information obtained by the obtaining step;
a providing step of providing a service according to the size of the target user based on the first correlation information generated by the generating step;
An information processing method comprising: an acquisition procedure for acquiring first evaluation information indicating a user's evaluation of one or more sizes of a specific target having a plurality of sizes;
a generation procedure for generating first correlation information indicating a first correlation between a plurality of different sizes of the specific targets based on the first evaluation information acquired by the acquisition procedure;
a providing procedure for providing a service according to the size of the target user based on the first correlation information generated by the generating procedure;
An information processing program characterized by causing a computer to execute

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