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

Abstract

The information to be presented to the evaluator is selected depending on the content of the evaluation by the evaluator. [Solution] The information processing device of the present application is an information processing device having a selection unit that selects multiple pieces of target information to present to an evaluator from among the target information indicating the evaluation target, and a reception unit that receives from the evaluator an evaluation indicating which of the multiple pieces of target information selected by the selection unit is more favorable, and is characterized in that the selection unit selects new target information based on the evaluation results of the target information by the evaluators, excluding evaluation results by evaluators whose evaluation content for the target information meets specified conditions.

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 are known techniques for collecting reliable answers from respondents. One example of such a technique is a technique for collecting data input from a user, measuring the time required for the user to input the data, comparing the measured time with a predetermined allowable range of data input time, and determining that the input data is valid if the measured time is within the allowable range of data input time. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-280482 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the above-described technology, it is not always possible to select information to be presented to an evaluator depending on the content of the evaluation by the evaluator.

[0005] For example, the above-mentioned technology merely determines whether the data entered by the user is valid or not, and it is not necessarily possible to select the information to be presented to the evaluator depending on the content of the evaluator's evaluation.

[0006] The present application has been made in view of the above, and aims to select information to be presented to an evaluator in accordance with the content of the evaluation by the evaluator. [Means for solving the problem]

[0007] The information processing device of the present application is an information processing device having a selection unit that selects multiple pieces of target information to present to an evaluator from among the target information indicating the evaluation target, and a reception unit that receives from the evaluator an evaluation indicating which of the multiple pieces of target information selected by the selection unit is favorable, and is characterized in that the selection unit selects new target information based on the evaluation results of the target information by the evaluators, excluding evaluation results by evaluators whose evaluation content for the target information meets specified conditions. [Effects of the Invention]

[0008] According to one aspect of the embodiment, it is possible to obtain an effect that information to be presented to the evaluator can be selected depending on the content of the evaluation by the evaluator. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of an information processing system 1 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 (1) showing an example of target information according to the embodiment. [Figure 4] FIG. 4 is a diagram (2) showing an example of target information according to the embodiment. [Figure 5] FIG. 5 is a diagram showing an example of the configuration of the information processing device 10 according to the embodiment. [Figure 6] FIG. 6 is a diagram showing an example of the target information database 31 according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of the evaluator information database 32 according to the embodiment. [Figure 8] FIG. 8 is a diagram showing an example of the user information database 33 according to the embodiment. [Figure 9] FIG. 9 is a flowchart (1) showing an example of the procedure of information processing according to the embodiment. [Figure 10]FIG. 10 is a flowchart (2) showing an example of the procedure of information processing according to the embodiment. [Figure 11] FIG. 11 is a flowchart (3) showing an example of the procedure of information processing according to the embodiment. [Figure 12] FIG. 12 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. DETAILED DESCRIPTION OF THE INVENTION

[0010] 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.

[0011] (Embodiment) [1. Information Processing System Configuration] First, an information processing system 1 according to an embodiment will be described. FIG. 1 is a diagram illustrating an example of the configuration of the information processing system 1 according to an embodiment. As illustrated in FIG. 1, the information processing system 1 includes an information processing device 10, a user terminal 100, and an evaluator terminal 200. The information processing device 10, the user terminal 100, and the evaluator terminal 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. Note that the information processing system 1 illustrated in FIG. 1 may include a plurality of information processing devices 10, a plurality of user terminals 100, and a plurality of evaluator terminals 200.

[0012] The information processing device 10 is an information processing device that receives an evaluation of target information indicating an evaluation target from an evaluator and realizes information processing according to the evaluation, and is realized by, for example, a server device, a cloud system, etc. For example, in the example shown in Fig. 2, the information processing device 10 receives an evaluation of target information indicating an evaluation target that is a combination (also called "coordinate") of multiple clothes (also called fashion items, including footwear (also called "shoes"), headwear (e.g., caps and hats), ornaments (also called "accessories"), small items (e.g., bags), etc.), indicating whether the combination is favorable or not (in other words, whether the combination of clothes is appropriate or not, whether the combination of clothes is compatible or not, or whether the combination of multiple clothes suits or not), from an evaluator (annotator), and realizes information processing according to the evaluation. The information processing device 10 may receive from the evaluator an evaluation of target information indicating an evaluation target, which is a single piece of clothing, indicating whether the single piece of clothing is favorable (in other words, whether the single piece of clothing is appropriate, whether the single piece of clothing is good, or whether the single piece of clothing looks good), and may perform information processing in accordance with the evaluation. The evaluation may be based on various perspectives. For example, the information processing device 10 may receive from the evaluator an evaluation indicating whether a combination of multiple pieces of clothing (or one piece of clothing) is cool, or whether a combination of multiple pieces of clothing (or one piece of clothing) is cute, or whether a combination of multiple pieces of clothing (or one piece of clothing) is fashionable, or whether a combination of multiple pieces of clothing (or one piece of clothing) is trendy, and is not limited to these examples. In this way, any evaluation content can be adopted depending on the situation.

[0013] Furthermore, for example, the information processing device 10 provides an electronic commerce service for providing (selling, leasing, etc.) clothing. The information processing device 10 also provides a coordination service for accepting content (for example, still images, moving images, articles, etc.) showing clothing coordination from users and providing the content to other users.

[0014] The information processing device 10 may have a function as a web server that provides a website related to an e-commerce service or a coordination service. The information processing device 10 may also be a device that distributes information to be displayed on an application related to an e-commerce service or a coordination service installed on the user terminal 100 or the evaluator terminal 200 to the information processing device 10. The information processing device 10 may also be a device that distributes the application data itself.

[0015] The information processing device 10 may also function as a distribution device that distributes control information to the user terminal 100 and the evaluator terminal 200. Here, the control information is written in, for example, a script language such as JavaScript (registered trademark) or a style sheet language such as CSS (Cascading Style Sheets). Note that the application itself distributed from the information processing device 10 may also be considered as control information.

[0016] The user terminal 100 is an information processing device used by a user. The user terminal 100 is realized, for example, by a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. The user terminal 100 displays information distributed by the information processing device 10 or a server device that provides a predetermined service, using a web browser or an application. The example shown in FIG. 2 shows a case where the user terminal 100 is a smartphone.

[0017] The evaluator terminal 200 is an information processing device used by an evaluator who evaluates the target information. The evaluator terminal 200 is realized, for example, by a smartphone, a tablet terminal, a laptop PC, a desktop PC, a mobile phone, a PDA, or the like. The evaluator terminal 200 displays information distributed by the information processing device 10 or a server device that provides a predetermined service, using a web browser or an application. Note that the example shown in FIG. 2 illustrates a case where the evaluator terminal 200 is a smartphone.

[0018] [2. An example of information processing] Next, an example of information processing realized by an information processing device etc. according to this embodiment will be described with reference to FIG. 2. FIG. 2 is a diagram showing an example of information processing according to this embodiment. In the following description, it is assumed that the user terminal 100 is used by a user (user U1) identified by the user ID "UID#1". In addition, in the following description, the user terminal 100 may be considered to be the same as the user U1. In other words, in the following, user U1 can also be read as the user terminal 100.

[0019] In the following description, the evaluator terminals 200 are referred to as evaluator terminals 200-1 to 200-N (N is an arbitrary natural number) according to the evaluator using the evaluator terminal 200. For example, the evaluator terminal 200-1 is the evaluator terminal 200 used by the evaluator (evaluator A1) identified by the evaluator ID "AID#1". In the following description, the evaluator terminals 200-1 to 200-N will be referred to as evaluator terminals 200 when there is no particular distinction between them. In the following description, the evaluator terminal 200 may be regarded as the same as the evaluator. That is, in the following description, the evaluator may be read as the evaluator terminal 200.

[0020] In the following description, a plurality of evaluators having corresponding attributes are classified into groups G1 to G4, and target information is presented to the evaluators belonging to each group. Each evaluator belonging to groups G1 to G4 is assumed to have at least one of the following attributes: gender, age, place of residence or work location, preferred fashion category, preferred fashion brand, preferred fashion genre, preferred fashion influencer, level of interest in fashion (fashion sensitivity) (for example, "low" indicating no interest, "medium" indicating some interest, or "high" indicating high interest, which may be estimated from search trends, browsing trends, purchasing trends (purchase trends), purchase amounts, etc.), fashion references (frequently accessed or bookmarked websites, SNS, magazines, etc.), purchasing tendencies, purchase amounts (monthly, annually), and occasions where fashion is often worn (for example, frequently attending weddings, etc.). Note that multiple evaluators may be classified into groups regardless of their attributes (for example, in the order in which they log in or randomly).

[0021] In the following description, it is assumed that code #1 to code #25 are the targets of evaluation.

[0022] In the following description, the information processing device 10 presents two pieces of target information to an evaluator and receives an evaluation indicating which of the pieces of target information represents a favorable outfit (in other words, the two pieces of target information are matched up, and which piece of target information wins).The information processing device 10 then repeats this process and determines a rating (Elo rating) for each piece of target information based on each evaluation.

[0023] First, the information processing device 10 selects target information indicating evaluation targets to be presented to the evaluators (step S1). For example, the information processing device 10 selects two pieces of target information to be presented to the evaluators belonging to groups G1 to G4 from target information group #1, which is a plurality of pieces of target information corresponding to outfits #1 to #25, respectively, and is composed of target information (in other words, target information without any additional target) that is images showing only outfits #1 to #25 (in other words, target information without any additional target), which does not include information such as the head (face (before or after makeup) and / or hairstyle) or body (body type) of a person wearing the outfits that make up the outfits).

[0024] To cite a specific example, when selecting target information to be presented to evaluator A1 from target information group #1, the information processing device 10 first selects, from target information group #1, target information #1 having the smallest number of evaluations (in other words, the number of matches) currently indicated by evaluations by each evaluator belonging to group G1. Then, based on the ratings of each piece of target information included in target information group #1 (ratings based on the evaluation results by each evaluator belonging to group G1), the information processing device 10 selects target information whose rating difference with target information #1 is within a predetermined range (in other words, target information that is estimated to be likely to result in a draw with target information #1). To cite one example, the information processing device 10 selects target information #2 whose rating difference with target information #1 is the smallest (in other words, target information #2 that is estimated to be most likely to result in a draw with target information #1).

[0025] In this way, by matching target information that is likely to result in a draw (in other words, target information where it is difficult to determine which outfit is more popular), the amount of information obtained from the evaluator's evaluation can be increased.

[0026] Next, the information processing device 10 presents the target information to the evaluator (step S2). For example, the information processing device 10 presents target information #1 and target information #2 to the evaluator A1. To give a specific example, the information processing device 10 displays the target information #1 and the target information #2 side by side on the screen of the evaluator terminal 200-1, and displays either one that the evaluator A1 evaluates as favorable so that the evaluator A1 can select it.

[0027] Next, the information processing device 10 receives evaluations of the presented target information from the evaluators (step S3). For example, the information processing device 10 receives an evaluation from evaluator A1 indicating which of target information #1 and target information #2 is more favorable. Then, the information processing device 10 adds 1 to the number of evaluations of target information #1 and target information #2 in group G1, and sets ratings for target information #1 and target information #2 in group G1 based on the evaluations from evaluator A1.

[0028] For example, if the target information #1 is evaluated as being more favorable, the information processing device 10 increases the value by which the rating of the target information #1 is increased and decreases the value by which the rating of the target information #2 is decreased, as the difference in ratings between the target information #1 and #2 decreases. Also, if the target information #1 is evaluated as being more favorable and the target information #1 has a higher rating than the target information #2, the information processing device 10 decreases the value by which the rating of the target information #1 is increased and decreases the value by which the rating of the target information #2 is decreased, as the difference in ratings increases. Also, if the target information #1 is evaluated as being more favorable and the target information #2 has a higher rating than the target information #1, the information processing device 10 increases the value by which the rating of the target information #1 is increased and decreases the value by which the rating of the target information #2 is decreased, as the difference in ratings increases.

[0029] The information processing device 10 performs the same processes as steps S1 to S3 when receiving further evaluations of the target information from evaluator A1 or when receiving evaluations of the target information from other evaluators. Here, after receiving evaluations of target information #1 and target information #2 from evaluator A1, when selecting target information to present to evaluators belonging to group G1, the information processing device 10 selects target information according to the number of evaluations of each piece of target information in group G1 that have changed according to the evaluations and the rating of each piece of target information in group G1. In other words, the information processing device 10 does not present the same combination of target information to each evaluator, but selects a combination of target information according to the number of evaluations of each piece of target information and the rating of each piece of target information, which change from time to time, and presents it to the evaluators.

[0030] Next, the information processing device 10 determines whether to exclude the evaluation results of the evaluators based on the evaluation contents of the target information by the evaluators (step S4). For example, if the evaluator A2 always or at a predetermined rate or more (for example, if the evaluator A2 always or at a predetermined rate or more selects the target information displayed in a predetermined area (for example, the right or left area) of the screen of the evaluator terminal 200), if the evaluator A2 evaluates in a certain pattern (for example, if the evaluator A2 selects the target information displayed in a certain area of ​​the screen of the evaluator terminal 200 in a certain pattern (for example, alternately), or if the time from the display of the target information to the selection is greater than a predetermined threshold (if the time until the evaluation is too long) or less than a predetermined threshold (if the time until the evaluation is too short) (in other words, if the evaluator is estimated to be insincere in evaluating the target information), the information processing device 10 excludes the evaluation results of the evaluator A2 from the evaluation results of the group G1, and further sets the evaluator A2 not to be presented with the target information (in other words, sets the evaluator A2 as an excluded person). Note that evaluator A2 may be moved to group G5 (a group of evaluators presumed to be unscrupulous), where he or she may select and present the target information and continue evaluation. If the evaluator in that group is presumed to be conscientious in evaluating the target information (in other words, if the evaluator is not presumed to be unscrupulous in evaluating the target information), he or she may be returned to the original group, where he or she may select and present the target information and resume evaluation. Furthermore, evaluator A2 may not be an unscrupulous evaluator, but may be an evaluator with unique preferences. For example, an evaluator with unique preferences may appear to be making unscrupulous evaluations. Therefore, evaluator A2 may be moved to group G6 (a group of evaluators presumed to have unique preferences), where he or she may select and present the target information and continue evaluation. The ranking for the group may be determined based on the evaluation results in that group.As will be described later, if the information processing device 10 presents dummy information together with (or instead of) the target information in the original group or group G6, and the evaluator evaluates the dummy information as favorable, the evaluator does not have any particular preferences, so the evaluation results by that evaluator may be excluded.

[0031] Next, the information processing device 10 excludes the evaluation results by the excluded users and selects target information to be presented to evaluators who are not set as excluded users (step S5). For example, the information processing device 10 recalculates the number of evaluations of each target information in group G1 by subtracting the number of evaluations by evaluator A2. Furthermore, the information processing device 10 excludes the evaluation results by evaluator A2 and recalculates the rating of each target information in group G1. Then, based on the recalculated number of evaluations and rating of each target information, the information processing device 10 selects target information indicating the evaluation target to be presented to evaluators belonging to group G1. Note that, because the information processing device 10 subtracts the number of evaluations by evaluator A2, target information whose number of evaluations has been subtracted is more likely to be selected (in other words, target information whose number of evaluations has been subtracted is preferentially displayed on the screens of 200 of evaluators belonging to group G1 other than evaluator A2).

[0032] Next, the information processing device 10 presents the selected target information to the evaluators who are not set as excluded persons (step S6) and receives evaluations of the presented target information (step S7).The information processing device 10 then determines whether to exclude the evaluation results of the evaluators based on the evaluation contents of the target information (step S8).The processing in steps S6 to S8 is the same as steps S2 to S4, so a description thereof will be omitted.

[0033] The information processing device 10 performs the above process until the number of evaluations by each evaluator for the target information belonging to the target information group #1 reaches or exceeds a predetermined threshold (for example, 25 times or more).

[0034] The information processing device 10 may calculate the accuracy of the rating of the target information belonging to the target information group #1 in each group, and perform the above process until the accuracy reaches or exceeds a predetermined threshold. For example, the information processing device 10 calculates the accuracy of the rating of the target information #1 in group G1 to be higher the more times the target information #1 in group G1 is evaluated, and calculates the accuracy of the rating of the target information #1 in group G1 to be lower the more times the target information #1 in group G1 is evaluated.

[0035] Furthermore, when an excluded evaluator is set, the information processing device 10 may set a new evaluator, present the target information to the new evaluator, and accept an evaluation.

[0036] After the above processing for target information group #1 is completed, the information processing device 10 selects two pieces of target information to present to the evaluators belonging to groups G1 and G3 from target information group #2, which is composed of multiple pieces of target information corresponding to outfits #1 to #25, respectively, and which is composed of target information that, in addition to images of outfits #1 to #25, further shows images of the head of a person wearing the outfit (in other words, target information to which the additional object "head" is added to the outfit). The information processing device 10 then presents the selected target information and accepts evaluations of the presented target information. The information processing device 10 also determines whether to exclude the evaluation results by the evaluators based on the evaluation content of the evaluators. These processes are performed until the number of evaluations by each evaluator for the target information belonging to target information group #2 reaches or exceeds a predetermined threshold. Note that these processes are similar to steps S1 to S8, and therefore description thereof will be omitted.

[0037] After the above process for target information group #1 is completed, the information processing device 10 selects two pieces of target information to be presented to the evaluators belonging to groups G2 and G4 from target information group #3, which is a plurality of pieces of target information corresponding to outfits #1 to #25, respectively, and which is composed of target information that is an image showing the body shape of a person wearing outfits #1 to #25 (in other words, an image of a person from the head down (an image excluding the head)) (in other words, target information to which the additional object "body shape" is added to the outfit). The information processing device 10 then presents the selected target information and accepts evaluations of the presented target information. The information processing device 10 also determines whether to exclude the evaluation results by the evaluators based on the evaluation content of the evaluators. This process is repeated until the number of evaluations by each evaluator for the target information belonging to target information group #3 reaches or exceeds a predetermined threshold. Note that this process is similar to steps S1 to S8, and therefore a description thereof will be omitted.

[0038] After the above processing for target information group #2 is completed, the information processing device 10 selects two pieces of target information to present to the evaluators belonging to groups G1 and G3 from target information group #4, which is composed of a plurality of pieces of target information corresponding to outfits #1 to #25, respectively, and which is comprised of target information that is an image of a person wearing outfits #1 to #25 (in other words, an image showing the head and body shape of a person wearing the outfit) (in other words, target information to which the additional objects "head" and "body shape" are added to the outfit). The information processing device 10 then presents the selected target information and accepts evaluations of the presented target information. The information processing device 10 also determines whether to exclude the evaluation results of the evaluators based on the evaluation content of the evaluators. These processes are performed until the number of evaluations by each evaluator for the target information belonging to target information group #4 reaches or exceeds a predetermined threshold. Note that these processes are similar to steps S1 to S8, and therefore description thereof will be omitted.

[0039] After the above processing for target information group #3 is completed, the information processing device 10 selects two pieces of target information from target information group #4 to be presented to the evaluators belonging to groups G2 and G4. The information processing device 10 then presents the selected pieces of target information and accepts evaluations for the presented target information. The information processing device 10 also determines whether to exclude the evaluation results of the evaluators based on the evaluation content for the evaluators. These processing steps are repeated until the number of evaluations by each evaluator for the target information belonging to target information group #4 reaches or exceeds a predetermined threshold. Note that these processing steps are similar to steps S1 to S8, and therefore will not be described further.

[0040] That is, the information processing device 10 presents target information of target information groups #1, #2, and #4 to groups G1 and G3, and presents target information of target information groups #1, #3, and #4 to groups G2 and G4. By presenting target information selected from at least one or more similar target information groups to multiple groups in this way, for example, when the groups are classified according to the attributes of the evaluators, it is possible to grasp whether similar evaluation results (ratings) can be obtained between group G1 and group G3 (in other words, whether evaluation results (ratings) can be obtained for each attribute, whether an evaluation result (rating) that combines the evaluation result (rating) of group G1 and the evaluation result (rating) of group G3 can be obtained, or whether the evaluation results (ratings) have converged). Furthermore, if the groups are not classified by the attributes of the evaluators, it is possible to determine whether similar evaluation results (ratings) can be obtained between group G1 and group G3 (in other words, whether there is any bias in the attributes of the evaluators (if there is a bias in the attributes of the evaluators, should the group be moved?), whether an evaluation result (rating) can be obtained that combines the evaluation results (ratings) of group G1 and the evaluation results (ratings) of group G3, or whether the evaluation results (ratings) have converged).

[0041] Here, examples of target information to be presented to the evaluator will be described with reference to Figures 3 and 4. Figure 3 is a diagram (1) showing an example of target information according to an embodiment. Figure 4 is a diagram (2) showing an example of target information according to an embodiment.

[0042] 3, the information processing device 10 first selects and presents two pieces of target information to the evaluators belonging to groups G1 and G3 from target information group #1, which shows only outfits, as shown in image C11, and accepts their evaluations. Then, the information processing device 10 selects and presents two pieces of target information to the evaluators belonging to groups G1 and G3 from target information group #2, which shows not only images of outfits but also images of the heads of people wearing the outfits, as shown in image C12, and accepts their evaluations. Then, the information processing device 10 selects and presents two pieces of target information to the evaluators belonging to groups G1 and G3 from target information group #4, which is an image of a person wearing the outfit, as shown in image C13, and accepts their evaluations.

[0043] 4, the information processing device 10 first selects and presents two pieces of target information to the evaluators belonging to groups G2 and G4 from target information group #1, which shows only outfits, as shown in image C21, and accepts their evaluations. Then, the information processing device 10 selects and presents two pieces of target information to the evaluators belonging to groups G2 and G4 from target information group #3, which is an image showing the physique of a person wearing the outfit, as shown in image C22, and accepts their evaluations. Then, the information processing device 10 selects and presents two pieces of target information to the evaluators belonging to groups G2 and G4 from target information group #4, which is an image showing a person wearing the outfit, as shown in image C23, and accepts their evaluations.

[0044] Here, for example, if evaluator A1 evaluates target information showing outfit #1 to which the additional object "head" has been added, and then evaluates target information showing outfit #1 to which no additional object has been added, evaluator A1 may be reminded of the additional object "head" that was presented beforehand, and may not be able to properly evaluate outfit #1 alone without the additional object added.

[0045] Therefore, as described above, the information processing device 10 presents the target information to groups G1 and G3 in the order of target information groups #1, #2, and #4 (in other words, in order from least to most information), and presents the target information to groups G2 and G4 in the order of target information groups #1, #3, and #4. This allows the information processing device 10 to obtain appropriate evaluations of the target information.

[0046] Returning to FIG. 2, the explanation will continue. Next, the information processing device 10 estimates the influence that the attachment target will have on the evaluation of the outfit based on the relative relationship of the evaluations of the target information groups #1 to #4 by the evaluators (step S9). For example, the information processing device 10 determines a ranking #1 in a state where no attachment target is attached to outfits #1 to #25 based on the ratings of the target information group #1 in group G1. Furthermore, the information processing device 10 determines a ranking #2 in a state where the attachment target "head" is attached to outfits #1 to #25 based on the ratings of the target information group #2 in group G1. Furthermore, the information processing device 10 determines a ranking #3 in a state where the attachment targets "head" and "body type" are attached to outfits #1 to #25 based on the ratings of the target information group #4 in group G1.

[0047] Then, the information processing device 10 calculates a score Sc1 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #1 and the rankings of outfits #1 to #25 in ranking #3, using ranking #3 as the correct answer data (for example, a score indicated by a number ranging from "1" indicating a perfect match with ranking #3 to "0" indicating no match at all with ranking #3). The information processing device 10 also calculates a score Sc2 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #2 and the rankings of outfits #1 to #25 in ranking #3, using ranking #3 as the correct answer data.

[0048] Furthermore, the information processing device 10 determines a ranking #4 for outfits #1 to #25 in a state where no additional object is added, based on the ratings of the target information group #1 in group G2. Furthermore, the information processing device 10 determines a ranking #5 for outfits #1 to #25 in a state where the additional object "body type" is added, based on the ratings of the target information group #2 in group G1. Furthermore, the information processing device 10 determines a ranking #6 for outfits #1 to #25 in a state where the additional objects "head" and "body type" are added, based on the ratings of the target information group #4 in group G1.

[0049] Then, the information processing device 10 calculates a score Sc3 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #4 and the rankings of outfits #1 to #25 in ranking #6, using ranking #6 as the correct data. Also, the information processing device 10 calculates a score Sc4 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #5 and the rankings of outfits #1 to #25 in ranking #6, using ranking #6 as the correct data.

[0050] Furthermore, the information processing device 10 determines a ranking #7 for outfits #1 to #25 in a state where no additional object is added, based on the ratings of target information group #1 in group G3. Furthermore, the information processing device 10 determines a ranking #8 for outfits #1 to #25 in a state where the additional object "head" is added, based on the ratings of target information group #2 in group G1. Furthermore, the information processing device 10 determines a ranking #9 for outfits #1 to #25 in a state where the additional objects "head" and "body type" are added, based on the ratings of target information group #4 in group G1.

[0051] Then, the information processing device 10 calculates a score Sc5 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #7 and the rankings of outfits #1 to #25 in ranking #9, using ranking #9 as the correct data. Also, the information processing device 10 calculates a score Sc6 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #8 and the rankings of outfits #1 to #25 in ranking #9, using ranking #9 as the correct data.

[0052] Furthermore, the information processing device 10 determines a ranking #10 in a state where no additional object is added to the outfits #1 to #25, based on the ratings of the target information group #1 in group G4. Furthermore, the information processing device 10 determines a ranking #11 in a state where the additional object "body type" is added to the outfits #1 to #25, based on the ratings of the target information group #2 in group G1. Furthermore, the information processing device 10 determines a ranking #12 in a state where the additional objects "head" and "body type" are added to the outfits #1 to #25, based on the ratings of the target information group #4 in group G1.

[0053] Then, the information processing device 10 calculates a score Sc7 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #10 and the rankings of outfits #1 to #25 in ranking #12, using ranking #12 as the correct data. Also, the information processing device 10 calculates a score Sc8 indicating the degree of agreement between the rankings of outfits #1 to #25 in ranking #11 and the rankings of outfits #1 to #25 in ranking #12, using ranking #12 as the correct data.

[0054] In the example of FIG. 2, it is assumed that scores Sc1 to Sc8 have been calculated as shown in graph Gr1. The information processing device 10 estimates the influence of the addition target based on each score shown in graph Gr1. For example, in the example of FIG. 2, it is assumed that score Sc2 is higher than score Sc1 by a predetermined threshold or more, and score Sc6 is higher than score Sc5 by a predetermined threshold or more (in other words, the evaluation results between group G1 and group G3 have converged). In this case, when the addition target "head" is added to outfits #1 to #25, the degree of match with the correct data changes by a predetermined threshold or more compared to when the addition target "head" is not added, and therefore the information processing device 10 estimates that the addition target "head" has an influence on the evaluation of the outfit. To give a specific example, when the information processing device 10 adds the addition object "head" to outfits #1 to #25, the degree of match with the correct answer data improves, and therefore the addition object "head" will have a positive influence on the evaluation of the outfit (in other words, when the addition object "head" is added, the outfit is more likely to be evaluated favorably by the evaluator). In other words, the information processing device 10 presumes that it is important to consider the head of the person wearing the outfit when determining whether the outfit (the fashion items that make it up) is appropriate or whether the outfits go well together. In other words, when recommending appropriate or well-matched outfits, the information processing device 10 preferably makes the recommendation taking into consideration the head of the person wearing the outfit.

[0055] In the example of FIG. 2, it is assumed that score Sc4 is higher than score Sc3 by a predetermined threshold or more, and score Sc8 is higher than score Sc7 by a predetermined threshold or more (in other words, the evaluation results converge between group G2 and group G4). In this case, when the addition target "body type" is added to outfits #1 to #25, the degree of match with the correct answer data changes by a predetermined threshold or more compared to when the addition target "body type" is not added. Therefore, the information processing device 10 estimates that the addition target "body type" has an influence on the evaluation of the outfit. To give a specific example, when the addition target "body type" is added to outfits #1 to #25, the degree of match with the correct answer data improves, and therefore the information processing device 10 estimates that the addition target "body type" has a positive influence on the evaluation of the outfit (in other words, when the addition target "body type" is added, the outfit is more likely to be evaluated favorably by the evaluator). In other words, the information processing device 10 estimates that it is important to consider the body type of the person wearing the outfit when determining whether the outfit is appropriate and whether the outfits are a good match. In other words, when recommending an appropriate or compatible outfit, the information processing device 10 preferably makes the recommendation taking into consideration the body type of the person who will wear the outfit.

[0056] Furthermore, in the example of FIG. 2, because scores Sc4 and Sc8 are higher than scores Sc2 and Sc6, the information processing device 10 estimates that the addition target "body type" has a higher degree of positive influence on the evaluation of the outfit than the addition target "head." In other words, the information processing device 10 estimates that, when determining whether an outfit is appropriate or whether the outfits go well together, it is more important to consider the body type than the head of the person wearing the outfit. In other words, when recommending an outfit that is appropriate or goes well together, the information processing device 10 preferably recommends it while taking into consideration the body type rather than the head of the person wearing the outfit.

[0057] Note that if score Sc1 is higher than score Sc2 by a predetermined threshold or more, and score Sc5 is higher than score Sc6 by a predetermined threshold or more, the information processing device 10 may estimate that when the addition target "head" is added to outfits #1 to #25, the degree of match with the correct answer data is lower than when the addition target "head" is not added, and therefore the addition target "head" has a negative impact on the evaluation of the outfit (in other words, when the addition target "head" is added, the outfit is less likely to be evaluated favorably by the evaluator). In other words, the information processing device 10 estimates that it is important not to take into account the head of the person wearing the outfit when determining whether the outfit is appropriate or whether the outfits are a good match. In other words, it is preferable that the information processing device 10 recommends an appropriate or a good match outfit without taking into account the head of the person wearing the outfit.

[0058] Furthermore, if score Sc3 is higher than score Sc4 by a predetermined threshold or more, and score Sc7 is higher than score Sc8 by a predetermined threshold or more, the information processing device 10 may estimate that when the addition target "body type" is added to outfits #1 to #25, the degree of match with the correct answer data is lower than when the addition target "body type" is not added, and therefore the addition target "body type" may have a negative impact on the evaluation of the outfit (in other words, when the addition target "body type" is added, the outfit is less likely to be evaluated favorably by the evaluator). In other words, the information processing device 10 estimates that it is important not to take into account the body type of the person wearing the outfit when determining whether the outfit is appropriate or whether the outfits are a good match. In other words, it is preferable that the information processing device 10 recommends an appropriate or a good match outfit without taking into account the body type of the person wearing the outfit.

[0059] Furthermore, if the scores Sc2 and Sc6 are higher than the scores Sc4 and Sc8, the information processing device 10 estimates that the additional target "body type" has a greater negative impact on the evaluation of the outfit than the additional target "head." In other words, the information processing device 10 estimates that, when determining whether an outfit is appropriate or a good combination of outfits, it is more important to consider the head of the person wearing the outfit than the body type of the person wearing it. In other words, when recommending an outfit that is appropriate or a good combination of outfits, it is preferable for the information processing device 10 to recommend an outfit that takes into consideration the head of the person wearing the outfit rather than the body type of the person wearing it.

[0060] Furthermore, a ranking for each group of target information is determined based on the rating for each group of target information, and it is estimated for each group whether each additional target has a positive or negative impact on the evaluation of an outfit. However, it is also possible to determine a ranking for each group of target information based on the rating for each group of target information, which is obtained by integrating the ratings for each group of target information, and it is estimated whether each additional target has a positive or negative impact on the evaluation of an outfit.

[0061] Next, the information processing device 10 generates new target information to be presented to the evaluator based on the influence of the target on the outfit or fashion item. For example, the information processing device 10 generates new content related to an outfit or fashion item to which the target "head" and / or the target "body type" are added, which are estimated to have a positive influence on the evaluation of the outfit or fashion item, as target information to be presented to the evaluator. As a specific example, if the target "head" and the target "body type" are estimated to have a positive influence, the information processing device 10 generates new images of people wearing the outfit or fashion item from images showing only the outfit or fashion item, as target information to be presented to the evaluator. This allows the information processing device 10 to increase the number of images showing people wearing the outfit or fashion item and determine more accurate rankings for outfits or fashion items to which the target "head" and the target "body type" are added.

[0062] Next, the information processing device 10 provides the user with content related to an outfit or fashion item based on the influence of the attachment target on the outfit or fashion item (step S10). For example, the information processing device 10 provides user U1 with content related to an outfit or fashion item to which the attachment target "head" and / or the attachment target "body type" that are estimated to have a positive influence on the evaluation of the outfit or fashion item have been added. As a specific example, the information processing device 10 provides content related to an outfit or fashion item to which the attachment target "head" and / or the attachment target "body type" have been added in an e-commerce service or a coordination service. As a more specific example, when providing content showing an image of an outfit or fashion item, the information processing device 10 provides content showing an image of an outfit or fashion item to which the attachment target "head" and / or the attachment target "body type" of user U1 or a target person designated by user U1 (such as user U1's family, partner, friend, or gift recipient) have been added (for example, by combining the head and / or body type). The information processing device 10 provides content showing images of user U1 or a target person and outfits or fashion items to which an additional target "head" and / or additional target "body type" similar to the additional target "head" and / or additional target "body type" has been added. In this case, information about the head and / or body type of user U1 or the target person designated by user U1 (e.g., images or numerical information) is provided by user U1 or the target person designated by user U1. As a more specific example, the information processing device 10 sets the priority of content related to outfits or fashion items to which an additional target "head" and / or additional target "body type" has been added higher than the priority of content related to outfits or fashion items to which an additional target "head" and / or additional target "body type" has not been added, and provides content related to outfits or fashion items based on the priority thus set preferentially, or provides content showing their rankings.

[0063] Furthermore, for example, the information processing device 10 provides user U1 with content related to an outfit or fashion item that takes into consideration the additional target "head" and / or the additional target "body type" that are estimated to have a positive effect on the evaluation of the outfit or fashion item. To give a specific example, the information processing device 10 provides content related to an outfit or fashion item that takes into consideration the additional target "head" and / or the additional target "body type" using a model in which rankings determined based on evaluation results related to target information to which the additional target "head" and / or the additional target "body type" that are estimated to have a positive effect on the evaluation of the evaluation target, which is an outfit or fashion item, are added, are learned as learning data. To give a more specific example, when a first object group, which is a combination of some of the fashion items that make up the outfit to be evaluated, a second object group, which is a combination of the remaining fashion items that make up the outfit to be evaluated, and an additional object that is a "head" and / or "body type" that is estimated to have a positive effect on the evaluation of the outfit to be evaluated, are input, the information processing device 10 calculates a set matching score that indicates the degree of matching between the first object group to be calculated, the second object group to be calculated, and the additional object to be calculated, using a model trained to output a set matching score that is higher the degree of matching between the first object group, the second object group, and the additional object (the closer the degree of matching between the first object group, the second object group, and the additional object is to be calculated, the higher the ranking of the predetermined evaluation object (the predetermined first object group and predetermined second object group that make it up) and the predetermined additional object).The information processing device 10 then provides content related to the combination of the first object group to be calculated, the second object group to be calculated, and the additional information to be calculated, based on the calculated set matching score.For example, the information processing device 10 may provide content related to an outfit that is a combination of a first object group that is a calculation target and a second object group that is a calculation target, taking into consideration the additional object "head" to be calculated and / or the additional object "body type" to be calculated, or content related to a plurality of fashion items that are the first object group that is a calculation target or the second object group that is a calculation target, constituting an outfit that is a combination of the first object group that is a calculation target and the second object group that is a calculation target, taking into consideration the additional object "head" to be calculated and / or the additional object "body type" to be calculated. Furthermore, for example, the information processing device 10 may provide content related to the additional object "head" to be calculated and / or the additional object "body type" to be calculated that matches an outfit that is a combination of the first object group that is a calculation target and the second object group that is a calculation target, or content related to the matching degree (set matching score) between an outfit that is a combination of the first object group that is a calculation target and the second object group that is a calculation target and the additional information that is a calculation target and / or the additional object "body type" to be calculated.

[0064] The target information for determining rankings to be learned by the model may be prepared for each fashion genre or for each occasion, and the information processing device 10 may determine the rankings for each fashion genre or for each occasion based on the evaluation results of the target information prepared for each fashion genre or for each occasion. This allows the model to learn the rankings for each fashion genre or for each occasion, and the information processing device 10 can use such a model to provide content related to outfits or fashion items for each fashion genre or for each occasion.

[0065] Furthermore, if the coordinate or fashion item indicated in the content provided to user U1 does not have the target "head" attached, the information processing device 10 provides the content in a state where the target "head" is attached to the coordinate or fashion item. As a specific example, the information processing device 10 provides the content using model #1 that has been trained to generate an image in a state where the target "head" is attached to the coordinate or fashion item from an image of the coordinate or fashion item.

[0066] Furthermore, if the coordinate or fashion item indicated in the content provided to user U1 does not have the target "body type" added to it, the information processing device 10 provides the content in a state where the target "body type" is added to the coordinate or fashion item. As a specific example, the information processing device 10 provides the content using model #1 that has been trained to generate an image in a state where the target "body type" is added to the coordinate or fashion item from an image of the coordinate or fashion item.

[0067] Here, model #1 is trained to output a training image when, for example, an image of only an outfit shown in a training image (an image in which the target "head" or "body shape" is added to an outfit or fashion item) is input. Any known technology can be applied to training model #1, and a learning method appropriately selected depending on the information used as training data may be used. For example, model #1 may be trained using various conventional machine learning technologies (e.g., supervised machine learning technologies such as SVM (Support Vector Machine)). Furthermore, model #1 may be trained using deep learning technologies. For example, model #1 may be trained using various deep learning technologies such as RNN (Recurrent Neural Network) and CNN (Convolutional Neural Network).

[0068] In addition, the information processing device 10 may provide content related to outfits or fashion items to which the additional target ``head'' and / or the additional target ``body type'' has been added when user U1 or the target person designated by user U1 has attributes corresponding to the evaluators belonging to groups G1 to G4.

[0069] Furthermore, if it is estimated that an attachment target has a negative impact on the evaluation of an outfit or fashion item, the information processing device 10 may provide content related to outfits or fashion items to which the attachment target is not attached. As a specific example, the information processing device 10 provides content related to outfits or fashion items to which the attachment target is not attached in an e-commerce service or a coordination service. As a more specific example, when providing content showing images of outfits or fashion items, the information processing device 10 provides content showing images of outfits or fashion items to which the attachment target "head" and / or the attachment target "body type" of user U1 or a target person designated by user U1 is not attached. Furthermore, for example, if it is estimated that the attachment target "head" has a negative impact on the evaluation of an outfit, the information processing device 10 sets the priority of content related to outfits or fashion items to which the attachment target "head" is attached lower than the priority of content related to outfits or fashion items to which the attachment target "head" is not attached, and preferentially provides content related to outfits or fashion items based on the thus set priority, or provides content showing their rankings. In addition, if the coordinate or fashion item indicated in the content provided to user U1 has the target "head" added to it, the information processing device 10 provides the content with the target "head" deleted from the coordinate or fashion item.

[0070] Furthermore, for example, the information processing device 10 provides user U1 with content related to outfits or fashion items that does not take into consideration the additional target "head" and / or additional target "body type" that are estimated to have a negative impact on the evaluation of the outfit or fashion item. To give a specific example, the information processing device 10 provides content related to outfits or fashion items that does not take into consideration the additional target "head" and / or additional target "body type" that are estimated to have a negative impact on the evaluation of the evaluation target that is an outfit or fashion item, using a model in which rankings determined based on evaluation results related to target information that does not have the additional target "head" and / or additional target "body type" that are estimated to have a negative impact on the evaluation of the evaluation target that is an outfit or fashion item are trained as training data. To give a more specific example, when a first object group, which is a combination of some of the fashion items that make up the outfit to be evaluated, a second object group, which is a combination of the remaining fashion items that make up the outfit to be evaluated, and an additional object (for example, an additional object "pose") other than the additional object that is the "head" and / or "body type" that is estimated to have a negative impact on the evaluation of the outfit to be evaluated, the information processing device 10 calculates a set matching score that indicates the degree of matching between the first object group to be calculated, the second object group to be calculated, and the additional object to be calculated, using a model trained to output a set matching score that is higher the degree of matching between the first object group, the second object group, and the additional object (the closer the degree of matching between the first object group, the second object group, and the additional object is to the combination of a higher-ranked predetermined evaluation object (the predetermined first object group and predetermined second object group that make up it) and the predetermined additional object).The information processing device 10 then provides content related to the combination of the first object group to be calculated, the second object group to be calculated, and the additional information to be calculated, based on the calculated set matching score.For example, the information processing device 10 may provide content related to an outfit that is a combination of a first object group that is a calculation target and a second object group that is a calculation target, taking into account the additional object "pose" that is a calculation target, or content related to a plurality of fashion items that are the first object group that is a calculation target or the second object group that is a calculation target, constituting an outfit that is a combination of the first object group that is a calculation target and the second object group that is a calculation target, taking into account the additional object "pose" that is a calculation target. Furthermore, the information processing device 10 may provide content related to an additional object "pose" that is a calculation target that matches an outfit that is a combination of the first object group that is a calculation target and the second object group that is a calculation target, or content related to the degree of matching (set matching score) between an outfit that is a combination of the first object group that is a calculation target and the second object group that is a calculation target and the additional object "pose" that is a calculation target.

[0071] In addition, the information processing device 10 may provide content in which an attachment target estimated to have a positive influence is added to an outfit or fashion item in preference to content in which an attachment target estimated to have a negative influence is added to an outfit or fashion item.

[0072] As described above, the information processing device 10 according to the embodiment can grasp the influence of additional objects such as head and body shape on the evaluation of an outfit, in addition to the compatibility of the clothes that make up the outfit, when evaluating the outfit. Similarly, the information processing device 10 according to the embodiment can grasp the influence of additional objects such as head and body shape on the evaluation of a fashion item when evaluating the fashion item. In other words, the information processing device 10 according to the embodiment can grasp the influence of objects added to an evaluation object on the evaluation of the evaluation object.

[0073] Furthermore, the information processing device 10 according to the embodiment can provide a user with preferentially content to which an additional object that is estimated to have a positive effect on the evaluation of an outfit or a fashion item has been added, and can also provide content to which the additional object has been added if the additional object has not been added. That is, the information processing device 10 according to the embodiment can provide content related to an evaluation object according to the effect that the object added to the evaluation object has on the evaluation of the evaluation object.

[0074] Furthermore, in the above-described embodiment, if there is an evaluator who is not serious about evaluating the target information, the reliability of the ratings and the like may decrease, and there is a possibility that inappropriate target information may be selected when selecting target information to present to the evaluator. Therefore, the information processing device 10 according to the embodiment can eliminate evaluation results by evaluators who are presumed to be not serious at any time, set an appropriate rating based on evaluation results by other serious evaluators, and appropriately select target information to present to the evaluator. In other words, the information processing device 10 according to the embodiment can select information to present to the evaluator depending on the content of the evaluation by the evaluator.

[0075] [3. Other processing examples] The above-described process is merely an example, and the information processing device 10 may perform various processes using various information. In this regard, examples are listed below.

[0076] [3-1. Additional items] In the example of FIG. 2, the information processing device 10 may select target information to which additional objects such as a pose of a person wearing the outfit, how the clothes constituting the outfit are worn (in other words, the manner in which they are worn), a background image, a description of the setting in which the outfit is worn, a description of the weather in which the outfit is worn, and the outfit worn by a companion of the person wearing the outfit are added, and present this to the evaluator. For example, the information processing device 10 selects an image of a person wearing the outfit and striking a predetermined pose, an image of the person from head down (an image that does not include the head; it may also be an image that does not include the body shape), as target information to which an additional object "pose" has been added, and presents this to the evaluator. Furthermore, the information processing device 10 selects an image of a person wearing the outfit and striking a predetermined outfit, an image of the person from head down (an image that does not include the head; it may also be an image that does not include the body shape), as target information to which an additional object "outfit" has been added, and presents this to the evaluator. The information processing device 10 also selects an image of an outfit superimposed on a predetermined background image (which may be an image excluding the head or body shape of the person wearing the outfit) as target information to which an additional target "background image" has been added, and presents this to the evaluator. The information processing device 10 also selects content explaining the scene in which the outfit is worn and the weather, together with an image of a person wearing the outfit (which may be an image excluding the head or body shape), as target information to which an additional target "wearing scene" and "weather" has been added, and presents this to the evaluator. The information processing device 10 also selects an image of a person wearing the outfit (which may be an image excluding the head or body shape) together with an image of a companion (which may be an image excluding the head or body shape), as target information to which an additional target "companion" has been added, and presents this to the evaluator. The information processing device 10 then provides content related to the outfit to user U1 based on the influence of the additional target "pose," the additional target "outfit," the additional target "background image," the additional target "wearing scene," the additional target "weather," and the additional target "companion" on the evaluation of the outfit.

[0077] In addition, an image of a person wearing an outfit and standing motionless may be treated as target information without an additional target "pose" added, and an image of a person in a posture that has undergone some change (for example, bending an arm or pulling a leg back) may be treated as target information with an additional target "pose" added.

[0078] In addition, an image of a person wearing an outfit may be treated as target information without the additional object "outfit" attached, and an image in which some change has been made to the way the person is wearing the outfit (for example, the clothes are worn over the body rather than being worn, the clothes are not buttoned, or the clothes are tied around the waist) may be treated as target information with the additional object "outfit" attached.

[0079] In addition, an image showing an outfit with a plain background (for example, a white background) may be considered as target information without an additional target "background image" added, and an image with some change made to the background (for example, changing from a white background to an image of a party venue, or changing from a white background to an image of the sea) may be considered as target information with an additional target "background image" added.

[0080] In addition, the information processing device 10 may use an outfit or fashion item expressed in grayscale as the evaluation target, and the color of the fashion item as an additional target to estimate whether the additional target "color" has a positive or negative impact on the evaluation of the outfit or fashion item.

[0081] Furthermore, when a "head" or a "body type" is an addition target, target information may be prepared in which the same "head" or "body type" is added to a fixed person, or target information in which different "heads" or "body types" are added without fixing a person. When preparing target information in which different "heads" or "body types" are added without fixing a person, the information processing device 10 may treat the different "heads" or "body types" as target information to which the same type of addition target "head" or "body type" is added, or may treat the different types of addition targets "head A" or "body type A" and "head B" or "body type B" are added. When treating the different types of addition targets "head A" or "body type A" and "head B" or "body type B" as target information to which different types of addition targets are added, the information processing device 10 may determine a ranking for each piece of target information based on the evaluation results for each piece of target information. The information processing device 10 may then calculate a score indicating the degree of agreement between the rankings and estimate the influence of the addition target.

[0082] [3-2. Estimation of the degree of impact] 2, the information processing device 10 may estimate that the greater the difference between the score Sc1 and the score Sc2, the greater the degree of influence that the addition object "head" has on the evaluation of the outfit. To give a specific example, the information processing device 10 estimates that the greater the score Sc2 is than the score Sc1, the greater the degree of positive influence that the addition object "head" has on the evaluation of the outfit, and that the greater the score Sc2 is than the score Sc1, the greater the degree of negative influence that the addition object "head" has on the evaluation of the outfit.

[0083] [3-3. About Coordination] In the example of Fig. 2, the information processing device 10 may select target information to be presented to an evaluator from target information indicating outfits identified using a model #2 that is generated in advance using posted information posted to a predetermined web service (e.g., a coordination service) as training data (correct answer data). The information processing device 10 may then train the model #2 based on the evaluation of the target information. For example, the information processing device 10 trains the model #2 using outfits with ratings equal to or higher than a predetermined threshold as correct answer data.

[0084] The information processing device 10 may train model #2 depending on whether the attachment target has an influence on the evaluation of the outfit. For example, if the attachment target "head" has an influence on the evaluation of the outfit, the information processing device 10 causes model #2 to learn an image of the outfit to which the attachment target "head" has been added. Furthermore, if the attachment target "head" does not have an influence on the evaluation of the outfit, the information processing device 10 causes model #2 to learn an image of the outfit to which the attachment target "head" has not been added.

[0085] As a result, for example, if the additional object "head" affects the evaluation of an outfit (in other words, if the additional object "head" is necessary to evaluate an outfit), and if the additional object "head" is not added to the correct answer data, the additional object "head" can be added and model #2 can be trained, thereby improving the accuracy of model #2. Also, if the additional object "head" does not affect the evaluation of an outfit (in other words, if the additional object "head" is not necessary to evaluate an outfit), an image of an outfit without the additional object "head" can be used as the correct answer data, thereby reducing the effort required to prepare correct answer data and improving convenience.

[0086] [3-4. Subdivision of additional items] In the example of FIG. 2, the information processing device 10 may select target information showing a part of an additional object that is estimated to have an impact on the evaluation of the outfit together with the outfit, present it to the evaluator, accept an evaluation of the target information, and estimate the impact that part of the additional object will have on the evaluation of the outfit. For example, if the additional object "body type" is estimated to have an impact on the evaluation of the outfit, the information processing device 10 selects target information to which the additional object "body type: other than hands" has been added and presents it to the evaluator. As a specific example, the information processing device 10 presents to the evaluator an image of a person wearing the outfit from head to toe, which does not include hands (hands have been removed), as target information to which the additional object "body type: other than hands" has been added. Then, the information processing device 10 estimates the impact that the additional object "body type: other than hands" will have on the evaluation of the outfit based on the evaluation from the evaluator.

[0087] In this way, by subdividing the additional object that has an influence on the evaluation of the outfit and estimating the influence, it is possible to accurately grasp which part of the additional object has an influence.

[0088] The addition target may be, for example, "body type: hands only" indicating only the hands, "body type: legs only" indicating only the legs, or "body type: waist only" indicating only the waist, among the addition target "body type." Also, the addition target may be "head: other than hair" indicating everything other than hair, or "head: hair only" indicating only hair, among the addition target "head."

[0089] [3-5. About the Content] 2, the information processing device 10 may provide content to which an additional object that is estimated to have an influence on the evaluation of the outfit by the user U1 satisfies a predetermined condition is added. For example, if the additional object "background image" is estimated to have a positive influence on the evaluation of the outfit and it is estimated based on a questionnaire or the like that the user U1 is considering purchasing clothes for a party, the information processing device 10 provides content to which a party image is added as a background image to the outfit.

[0090] Furthermore, the information processing device 10 may provide content based on the purchase history of user U1. For example, if it is estimated that the addition target "head" has a positive effect on the evaluation of an outfit, the information processing device 10 provides content in which a head image corresponding to a product image of clothing purchased by user U1 through an e-commerce service or the like (for example, an image of the head of a model wearing the clothing purchased by user U1) is added to the outfit. In other words, the information processing device 10 provides content in which a head image estimated to be preferred by user U1 is added to the outfit. Note that user U1 may be asked to register a head image, and the information processing device 10 may provide content in which the head image of user U1 is added to a product image of clothing purchased by user U1 through an e-commerce service or the like.

[0091] Furthermore, the information processing device 10 may provide content based on the browsing history of the user U1. For example, if it is estimated that the "face" to be added has a positive influence on the evaluation of an outfit, the information processing device 10 may provide content in which an image of an outfit to which the user U1 gave a positive reaction (e.g., pressing the "Like" button) and a corresponding head image (e.g., an image of the head of the person who gave the positive reaction) are added to the outfit. In other words, the information processing device 10 provides content in which an image of a head that is estimated to be preferred by the user U1 is added to the outfit. Note that the user U1 may be asked to register a head image, and the information processing device 10 may provide content in which an image of an outfit to which the user U1 gave a positive reaction in a coordination service or the like and a head image of the user U1 are added to the outfit.

[0092] [3-6. Exclusion of evaluation results] 2, the information processing device 10 may present dummy information together with the target information, and if the evaluator evaluates the dummy information as being favorable, exclude the evaluation result by that evaluator. For example, the information processing device 10 presents dummy information, which is an image including a character string such as "Do not select this image," to the evaluator together with the target information, and if the evaluator evaluates the dummy information as being favorable, exclude the evaluation result by that evaluator.

[0093] Furthermore, when two pieces of the same target information are presented and an evaluator evaluates one of them as favorable, the information processing device 10 may exclude the evaluation result by that evaluator.

[0094] Furthermore, the information processing device 10 may present target information that is correct (for example, target information that anyone would agree is a valid outfit) and target information that is incorrect (for example, target information that anyone would agree is not a valid outfit), and if an evaluator evaluates the incorrect target information as favorable, the evaluation result by that evaluator may be excluded.

[0095] Furthermore, if the time from when the target information is displayed until the evaluator makes a selection is equal to or greater than a predetermined threshold, the information processing device 10 may exclude the evaluation result by that evaluator.

[0096] Furthermore, the information processing device 10 may present target information to an evaluator via an e-commerce service or a coordination service, and during the presentation, if an app (e.g., a messaging app) or a web page related to another service is displayed on the evaluator terminal 200, the information processing device 10 may exclude the evaluation result by the evaluator. Even if an app (e.g., a messaging app) or a web page related to another service is displayed on the evaluator terminal 200, the information processing device 10 may not exclude the evaluation result by the evaluator if the time it takes for the evaluator to return to the evaluation is equal to or less than a predetermined threshold, or if the time from the evaluator returning to the evaluation to making a selection is equal to or less than a predetermined threshold.

[0097] Furthermore, the information processing device 10 may exclude the evaluation result of the evaluator if the time from when the target information is displayed until the evaluator makes a selection is equal to or less than a predetermined threshold. Instead of immediately excluding the evaluation result, the information processing device 10 may encourage the evaluator to make a serious evaluation. For example, if the time from when the target information is displayed until the evaluator makes a selection is equal to or less than a predetermined threshold, the information processing device 10 controls the time from when the next target information is displayed until the evaluator can make a selection to be longer than usual. This ensures that the evaluator has time to carefully check the displayed target information and can control the system so that evaluators who make a serious evaluation can finish their evaluation more quickly, thereby encouraging the evaluator to give a serious response.

[0098] Furthermore, the information processing device 10 may exclude the evaluation results of an evaluator if the evaluation content of the evaluator satisfies conditions set based on information about the evaluator. For example, if the fashion category that the evaluator is not good at (in other words, the fashion category that the evaluator does not usually wear) is estimated to be "mode" based on information about the evaluator, such as a questionnaire for the evaluator, gender, age, place of residence, clothing purchase history, and outfit browsing history, it is estimated that it takes a long time to evaluate target information showing outfits belonging to "mode." Therefore, the information processing device 10 does not exclude the evaluation results of the evaluator when evaluating target information showing outfits belonging to "mode," even if the time from when the target information is displayed to when the evaluator selects it is equal to or greater than a predetermined threshold. On the other hand, when evaluating target information showing outfits belonging to "mode," if the time from when the target information is displayed to when the evaluator selects it is equal to or greater than a specific threshold, which is longer than the predetermined threshold, the information processing device 10 excludes the evaluation results of the evaluator.

[0099] Furthermore, if the fashion category in which the evaluator excels (in other words, the fashion category that the evaluator usually wears) is estimated to be "casual," it is estimated that it will not take much time to evaluate target information showing outfits belonging to "casual." Therefore, the information processing device 10 sets a time limit for the evaluator to make a selection from the time the target information is displayed when evaluating target information showing outfits belonging to "casual" to be shorter than that for evaluators who are not good at "casual," and excludes the evaluation results by that evaluator if the time limit is exceeded.

[0100] Note that when an evaluator who evaluates outfits #1 to #25 is set as an excluded evaluator, the information processing device 10 may exclude the evaluation results that the excluded evaluator has previously performed on other outfits. For example, if the excluded evaluator has previously performed evaluations on outfits #26 to #50, the information processing device 10 excludes the evaluation results of the excluded evaluator, determines the ranking of outfits #26 to #50 based on the evaluation results of other evaluators, and estimates the influence that additional items added to outfits #26 to #50 have on the evaluations.

[0101] [3-7. Regarding excluded persons] In the example of FIG. 2, the information processing device 10 may determine whether or not to present the target information to the excluded person (in other words, whether or not to reinstate the excluded person as an evaluator) based on information about the excluded person. For example, the excluded person may have previously made an insincere evaluation because they were presented with target information related to a fashion category that they are not good at (in other words, if they had been presented with target information related to a fashion category that they are good at, they may have made a serious evaluation). Therefore, the information processing device 10 determines whether or not to reinstate the excluded person as an evaluator based on information about the excluded person. As a specific example, if target information related to a fashion category that the excluded person is estimated to be bad at based on information about the excluded person is presented and the excluded person has been set as an excluded person based on their evaluation of the target information, the information processing device 10 reinstates the excluded person as an evaluator. Furthermore, the information processing device 10 determines whether or not to reinstate the excluded person as an evaluator based on the content of the excluded person's evaluation of other target information. As a specific example, if target information related to a fashion category that the excluded person is estimated to be good at based on information about the excluded person is presented, and the excluded person has not been set as an excluded person based on their evaluation of the target information (in other words, if it is determined that the excluded person has made a serious evaluation), the information processing device 10 reinstates the excluded person as an evaluator. Note that the information processing device 10 may reinstate the excluded person as an evaluator only when the excluded person presents target information related to a fashion category in which the excluded person is presumed to be good at it.

[0102] Furthermore, the information processing device 10 may present predetermined information and determine whether to reinstate the excluded person as an evaluator based on the evaluation results for the predetermined information. For example, the information processing device 10 may present correct target information and incorrect target information to the excluded person a predetermined number of times, and reinstate the excluded person as an evaluator if the rate at which the correct target information is selected is equal to or greater than a predetermined threshold.

[0103] Furthermore, when evaluating target information related to a fashion category in which the excluded person excels, the information processing device 10 may restore the excluded person to the status of an evaluator.

[0104] Furthermore, when presenting target information to an evaluator corresponding to an attribute possessed by an excluded person, the information processing device 10 may restore the excluded person to the evaluator.

[0105] [3-8. Evaluation] 2, the information processing device 10 presents two pieces of target information to the evaluator and receives an evaluation indicating which piece of target information is more favorable, but the evaluation by the evaluator is not limited to this example and may be performed in any manner. For example, when presenting target information #1 and #2, the information processing device 10 may present options such as (1) "target information #1 is more favorable," (2) "target information #1 is somewhat more favorable," (3) "target information #2 is more favorable," (4) "target information #2 is somewhat more favorable," or (5) "both are equally favorable," and receive a selection for one of them.

[0106] When (2) is selected, the information processing device 10 may increase the rating of the target information #1 by a smaller amount than when (1) is selected. When (4) is selected, the information processing device 10 may increase the rating of the target information #2 by a smaller amount than when (3) is selected. When (5) is selected, the information processing device 10 may not change the ratings of the target information #1 and #2.

[0107] Furthermore, instead of accepting an evaluation indicating which of two pieces of target information is more favorable, the information processing device 10 may present three or more pieces of target information and accept an evaluation indicating which of the pieces is more favorable.

[0108] [3-9. About the Group] In the example of FIG. 2, the evaluators may be classified into groups arbitrarily. For example, the information processing device 10 may select and present target information to each evaluator based on the ratings of the target information and the number of evaluations by all evaluators, without classifying the evaluators into groups, and may receive evaluations of the target information from each evaluator. The information processing device 10 may then extract evaluators having attributes corresponding to user U1, who is the target of providing content, and estimate the influence of the added target on the evaluation of the outfit (in other words, the influence of the added target on the evaluation of the outfit by user U1) based on the evaluation results of the extracted evaluators. The information processing device 10 may then provide content related to outfits to user U1 based on the influence of the added target on the outfit.

[0109] Furthermore, the information processing device 10 may select and present target information to each evaluator based on the ratings of the target information and the number of evaluations by all evaluators, without classifying the evaluators into groups, and may receive evaluations of the target information from each evaluator.The information processing device 10 may then extract evaluators with attributes specified by an administrator of an e-commerce service, a coordination service, or the like, and estimate the influence of the added target on the evaluation of the outfit (in other words, the influence of the added target on the evaluation of the outfit in the specified attributes) based on the evaluation results of the extracted evaluators.The information processing device 10 may then provide the administrator with content related to the influence of the added target on the outfit.

[0110] In the example of FIG. 2, the classification of evaluators into groups may be performed dynamically. For example, the information processing device 10 may select and present target information to each evaluator based on the ratings and number of ratings of the target information of all evaluators, without classifying the evaluators into groups, and receive evaluations of the target information from each evaluator. Alternatively, for example, the information processing device 10 may randomly classify the evaluators into groups, select and present target information to each evaluator based on the ratings and number of ratings of the target information in each group, and receive evaluations of the target information from each evaluator. Then, midway (when a predetermined number of evaluations or more have been received, for example, when the evaluation trends of each evaluator have emerged), the information processing device 10 may move the groups based on the similarity of the evaluation trends (also referred to as the attributes of each evaluator) of each evaluator so that evaluators with the same or similar evaluation trends belong to the same group (at this time, a new group may be generated depending on the number of evaluation trends that have emerged), and select and present target information to each evaluator based on the ratings and number of ratings of the target information in each group after the movement, and receive evaluations of the target information from each evaluator. Here, evaluators with similar evaluation tendencies are, for example, evaluators whose evaluations of the same outfit are similar, or whose evaluations of similar outfits (for example, outfits that include the same items of clothing, outfits that have similar appearances such as color or shape, outfits in the same category, outfits that are similar in price, etc.) are similar.

[0111] The information processing device 10 may then identify a group to which evaluators who have attributes corresponding to the user U1 to whom the content is to be provided belong, determine a ranking based on the evaluation results of the identified group, and estimate the influence of the target to be added on the evaluation of the outfit (in other words, the influence of the target to be added on the evaluation of the outfit by user U1).The information processing device 10 may then provide content related to the outfit to user U1 based on the influence of the target to be added on the outfit.

[0112] In the example of FIG. 2, the classification of evaluators into groups may be performed dynamically. For example, the information processing device 10 may select and present target information to each evaluator based on the ratings and number of ratings of the target information of all evaluators, without classifying the evaluators into groups, and receive evaluations of the target information from each evaluator. Alternatively, for example, the information processing device 10 may randomly classify the evaluators into groups, select and present target information to each evaluator based on the ratings and number of ratings of the target information in each group, and receive evaluations of the target information from each evaluator. Then, the information processing device 10 may select and present target information suitable for estimating the similarity of the evaluation tendencies (also referred to as attributes) of the evaluators, and receive evaluations of the target information from each evaluator. Specifically, if the evaluators' evaluation tendency is a predetermined evaluation tendency, the information processing device 10 selects and presents a pair of target information pieces that are known to definitely evaluate the left target information as preferable, moves the groups so that evaluators with the same or similar evaluation tendency belong to the same group (at this time, new groups may be generated depending on the number of evaluation tendencies that appear), selects and presents target information pieces to each evaluator based on the ratings and number of evaluations of the target information in each group after the movement, and receives evaluations of the target information from each evaluator.The information processing device 10 may then identify groups to which evaluators with attributes corresponding to user U1, who is the target of providing content, belong, determine rankings based on the evaluation results of the identified groups, and estimate the influence of the added object on the evaluation of the outfit (in other words, the influence of the added object on user U1's evaluation of the outfit).The information processing device 10 may then provide content related to outfits to user U1 based on the influence of the added object on the outfit.

[0113] [3-10. About the evaluators] The information processing device 10 may present multiple pieces of target information to an artificial intelligence, such as a large-scale language model, instead of an evaluator, and accept an evaluation of the target information. Furthermore, the information processing device 10, in principle, presents multiple pieces of target information to the artificial intelligence instead of an evaluator, and accepts an evaluation of the target information. However, if the information processing device 10 is unable to accept a correct evaluation from the artificial intelligence, it may present the same multiple pieces of target information to the evaluator and accept an evaluation of the target information. The information processing device 10 may present multiple pieces of target information to the artificial intelligence in a first order and accept an evaluation of the target information, and may present the same multiple pieces of target information to the artificial intelligence in a second order and accept an evaluation of the target information. If the two evaluations are the same, the information processing device 10 may determine the evaluation to be correct, or if the two evaluations are different, the information processing device 10 may determine the evaluation to be incorrect (an evaluation that is somehow affected by the order). Furthermore, the information processing device 10 may present a plurality of pieces of target information to the artificial intelligence, accept evaluations of the target information and reasons for the evaluation, and may determine the evaluation as correct if the reason for the evaluation is reasonable (for example, because the outfit presented on the left looks like the multiple clothes are more harmonious), or may determine the evaluation as incorrect if the reason for the evaluation is not reasonable (for example, because it is simply presented on the left). Furthermore, when having the artificial intelligence evaluate, the information processing device 10 may determine and instruct the attributes of the artificial intelligence so that the evaluator has attributes (for example, it may generate a prompt instructing the artificial intelligence to evaluate as a man in his twenties), or it may have the artificial intelligence itself determine the attributes (for example, it may generate a prompt instructing the artificial intelligence to evaluate from a perspective determined by itself).

[0114] 4. Configuration of Information Processing Device Next, the configuration of the information processing device 10 will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the configuration of the information processing device 10 according to the embodiment. As shown in Fig. 5, the information processing device 10 has a communication unit 20, a storage unit 30, and a control unit 40.

[0115] (Regarding the communication unit 20) The communication unit 20 is realized by, for example, a network interface card (NIC) etc. The communication unit 20 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the user terminal 100, the evaluator terminal 200 etc.

[0116] (Regarding the storage unit 30) The storage unit 30 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in Fig. 5, the storage unit 30 has a target information database 31, an evaluator information database 32, and a user information database 33.

[0117] (Regarding Target Information Database 31) The target information database 31 stores various types of information related to evaluation targets. An example of the information stored in the target information database 31 will now be described with reference to FIG. 6. FIG. 6 is a diagram showing an example of the target information database 31 according to the embodiment. In the example of FIG. 6, the target information database 31 has items such as "target information ID," "evaluation target ID," "evaluation target information," "addition target," "rating," and "number of evaluations."

[0118] "Target information ID" indicates identification information for identifying the target information. "Evaluation target ID" indicates identification information for identifying the evaluation target indicated by the target information. "Evaluation target information" indicates information about the evaluation target indicated by the target information, and for example, an image of the evaluation target is stored. "Additional target" indicates an additional target added to the evaluation target, and for example, information such as an image of the head of the person wearing the evaluation target, information (including images) about the body shape of the person wearing the evaluation target, the pose of the person wearing the evaluation target, the manner in which the evaluation target is worn, and a background image is stored. "Rating" indicates the rating of the target information. "Number of evaluations" indicates the number of times the target information has been evaluated.

[0119] That is, Figure 6 shows an example in which the evaluation target indicated by the target information identified by the target information ID "DID#1" is identified by the evaluation target ID "CID#1", the evaluation target information of the evaluation target is "Evaluation target information #1", the addition target is "Addition target #1", the rating of the target information is "Rating #1", and the number of evaluations is "Number of evaluations #1".

[0120] (Regarding Evaluator Information Database 32) The rater information database 32 stores various information related to raters. An example of the information stored in the rater information database 32 will now be described with reference to FIG. 7. FIG. 7 is a diagram illustrating an example of the rater information database 32 according to the embodiment. In the example of FIG. 7, the rater information database 32 has items such as "rater ID," "attribute information," "purchase history," "browsing history," and "rater information."

[0121] "Evaluator ID" indicates identification information for identifying the evaluator. "Attribute information" indicates the attributes of the evaluator. "Purchase history" indicates the purchase history of the evaluator in e-commerce services, etc. "Browse history" indicates the content browsing history of the evaluator in e-commerce services, coordination services, etc.

[0122] "Evaluation information" indicates information regarding the evaluator's evaluation of the target information, and includes items such as "presented target information" and "evaluation." "Presented target information" indicates information regarding the target information presented to the evaluator (in other words, the evaluator has evaluated it). "Evaluation" indicates the evaluation of the target information presented to the evaluator, and stores information indicating, for example, which pieces of target information were favorably evaluated.

[0123] That is, Figure 7 shows an example in which the attribute information of an evaluator identified by the evaluator ID "AID#1" is "attribute information #11", the purchase history is "purchase history #11", the browsing history is "browsing history #11", the target information presented to the evaluator is "presented target information #1", and the evaluation of the target information is "evaluation #1".

[0124] (Regarding User Information Database 33) The user information database 33 stores various types of information related to users. Here, an example of information stored in the user information database 33 will be described with reference to FIG. 8. FIG. 8 is a diagram showing an example of the user information database 33 according to the embodiment. In the example of FIG. 8, the user information database 33 has items such as "user ID," "attribute information," "purchase history," and "browsing history."

[0125] "User ID" indicates identification information for identifying a user. "Attribute information" indicates the user's attributes. "Purchase history" indicates the user's purchase history in e-commerce services, etc. "Browse history" indicates the user's content browsing history in e-commerce services, coordination services, etc.

[0126] That is, FIG. 8 shows an example in which the attribute information of a user identified by a user ID "UID#1" is "attribute information #21", the purchase history is "purchase history #21", and the browsing history is "browsing history #21".

[0127] (Regarding the control unit 40) The control unit 40 is a controller, and is realized by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs stored in a storage device inside the information processing device 10 using RAM as a work area. The control unit 40 is also a controller, and is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in FIG. 5 , the control unit 40 according to the embodiment has a selection unit 41, a reception unit 42, an estimation unit 43, a provision unit 44, a setting unit 45, a determination unit 46, and a learning unit 47, and realizes or executes the functions and actions of information processing described below.

[0128] (Regarding the selection unit 41) The selection unit 41 selects a plurality of first target information pieces and a plurality of second target information pieces to be presented to the evaluator from among first target information pieces that indicate only the evaluation target pieces and second target information pieces that indicate both the evaluation target pieces and additional targets. For example, in the example of FIG. 2, the selection unit 41 references the target information database 31 and the evaluator information database 32 and selects target information pieces to be presented to the evaluator from target information group #1 (first target information), which is an image showing only outfits #1 to #25. The selection unit 41 also selects target information pieces to be presented to the evaluator from target information group #2 (second target information), which shows an image of a person's head in addition to the images of outfits #1 to #25. The selection unit 41 also selects two pieces of target information pieces to be presented to the evaluator from target information group #3 (second target information), which is an image showing the body shapes of people wearing outfits #1 to #25. Furthermore, the selection unit 41 selects target information to be presented to the evaluator from target information group #4 (second target information) which is an image showing people wearing outfits #1 to #25.

[0129] The selection unit 41 may select a plurality of first target information and a plurality of second target information to be presented to the evaluator from among first target information, which is an image showing only a plurality of clothing combinations, and second target information, which is an image showing a plurality of clothing combinations and an additional target. For example, in the example of FIG. 2, the selection unit 41 selects target information to be presented to the evaluator from target information group #1, which is an image showing only outfits #1 to #25, which are clothing combinations. The selection unit 41 also selects target information to be presented to the evaluator from target information group #2, which shows images of people's heads in addition to images of outfits #1 to #25, which are clothing combinations. The selection unit 41 also selects target information to be presented to the evaluator from target information group #4, which is an image showing people wearing outfits #1 to #25, which are clothing combinations.

[0130] The selection unit 41 may also select multiple pieces of second target information to be presented to the evaluator from second target information indicating, as additional targets, at least one of an image of a person's head, information about the body shape of the person using the evaluation target, the pose of the person using the evaluation target, the manner in which the evaluation target is used, the situation in which the evaluation target is used (more specifically, TPO (Time Place Occasion)), and a background image. For example, in the example of FIG. 2, the selection unit 41 selects target information to be presented to the evaluator from target information group #2, which further indicates an image of a person's head in addition to images of outfits #1 to #25. The selection unit 41 also selects two pieces of target information to be presented to the evaluator from target information group #3, which is an image showing the body shapes of people wearing outfits #1 to #25. The selection unit 41 also selects target information to be presented to the evaluator from target information group #4, which is an image showing people wearing outfits #1 to #25.

[0131] The selection unit 41 may also select a plurality of pieces of first target information to be presented to the evaluator from the first target information based on a rating of the first target information calculated based on the first evaluation, and may select a plurality of pieces of second target information to be presented to the evaluator from the second target information based on a rating of the second target information calculated based on the second evaluation. For example, in the example of FIG. 2, the selection unit 41 selects target information to be presented to the evaluator based on a rating of each piece of target information included in target information group #1. Similarly, the selection unit 41 selects target information to be presented to the evaluator from target information groups #2 to #4.

[0132] The selection unit 41 may also select, from the first target information, a plurality of pieces of first target information whose rating difference is within a predetermined range, and may select, from the second target information, a plurality of pieces of second target information whose rating difference is within a predetermined range. For example, in the example of FIG. 2, the selection unit 41 selects target information whose rating difference from target information #1 is within a predetermined range, based on the ratings of each piece of target information included in target information group #1. Similarly, the selection unit 41 selects target information to be presented to the evaluator from target information groups #2 to #4.

[0133] The selection unit 41 may also select multiple pieces of first target information to be presented to the evaluators from the first target information based on the number of times the first target information has been evaluated by the evaluators, and select multiple pieces of second target information to be presented to the evaluators from the second target information based on the number of times the second target information has been evaluated by the evaluators. For example, in the example of FIG. 2, the selection unit 41 selects, from the target information group #1, target information #1 that currently has the fewest number of evaluations, indicating that evaluations have been performed by each evaluator belonging to group G1. Similarly, the selection unit 41 selects target information to be presented to the evaluators from the target information groups #2 to #4.

[0134] Furthermore, the selection unit 41 may select a plurality of pieces of first target information and a plurality of pieces of third target information to be presented to the evaluator from first target information indicating only the evaluation target and third target information indicating, together with the evaluation target, some of the additional targets that are estimated to have an effect on the evaluation of the evaluation target. For example, in the example of Fig. 2, if it is estimated that the additional target "body type" will have an effect on the evaluation of the outfit, the selection unit 41 selects the target information to be presented to the evaluator from the target information (third target information) to which the additional target "body type: other than hands" has been added.

[0135] Furthermore, the selection unit 41 may select a plurality of pieces of first target information to be presented to the evaluator from among the first target information indicating combinations of evaluation targets identified using a model that has been trained to determine whether or not the combinations of evaluation targets satisfy predetermined conditions, and may select a plurality of pieces of second target information to be presented to the evaluator from among the second target information indicating combinations of evaluation targets identified using the model. For example, in the example of Fig. 2, the selection unit 41 selects the target information to be presented to the evaluator from the target information indicating outfits identified using model #2.

[0136] Furthermore, the selection unit 41 may select multiple pieces of target information to be presented to the evaluator from among the target information indicating the evaluation target.The selection unit 41 may then select new target information based on evaluation results obtained by excluding, from among the evaluation results of the target information by the evaluators, evaluation results by evaluators whose evaluation content on the target information satisfies a predetermined condition.For example, in the example of FIG. 2, the selection unit 41 excludes evaluation results by excluded evaluators and selects target information indicating the evaluation target to be presented to evaluators who are not set as excluded evaluators.

[0137] Furthermore, when an evaluator evaluates dummy information presented together with the target information or dummy information presented instead of the target information as favorable, the selection unit 41 may select new target information based on the evaluation results excluding the evaluation results by the evaluator. For example, in the example of FIG. 2, the selection unit 41 presents dummy information together with the target information, and when the evaluator evaluates the dummy information as favorable, the selection unit 41 may exclude the evaluation results by the evaluator and select new target information. Note that the selection unit 41 may present dummy information instead of the target information, and when the evaluator evaluates the dummy information as favorable, the selection unit 41 may exclude the evaluation results by the evaluator and select new target information.

[0138] Furthermore, when an evaluator evaluates any of the same target information as being favorable, the selection unit 41 may select new target information based on an evaluation result excluding the evaluation result by that evaluator. For example, in the example of Fig. 2, when two pieces of the same target information are presented and an evaluator evaluates one of them as being favorable, the selection unit 41 excludes the evaluation result by that evaluator and selects new target information.

[0139] Furthermore, when an evaluator evaluates target information previously set as a correct answer as unfavorable, the selection unit 41 may select new target information based on an evaluation result excluding the evaluation result by the evaluator. For example, in the example of Fig. 2, the selection unit 41 presents target information that is the correct answer and target information that is an incorrect answer, and when the evaluator evaluates the incorrect target information as favorable, the selection unit 41 excludes the evaluation result by the evaluator and selects new target information.

[0140] Furthermore, when the time required for an evaluator to evaluate target information satisfies a predetermined condition, the selection unit 41 may select new target information based on the evaluation results excluding the evaluation results by that evaluator. For example, in the example of FIG. 2, when the time from when the target information is displayed until the evaluator selects it is equal to or greater than a first threshold, the selection unit 41 excludes the evaluation results by that evaluator and selects new target information. Furthermore, when the time from when the target information is displayed until the evaluator selects it is equal to or less than a second threshold, the selection unit 41 excludes the evaluation results by that evaluator and selects new target information.

[0141] Furthermore, when a position on the screen of the terminal device used by the evaluator where the evaluator performed an operation related to the evaluation of the target information satisfies a predetermined condition, the selection unit 41 may select new target information based on the evaluation result excluding the evaluation result by the evaluator. For example, in the example of Fig. 2, when the evaluator always selects the target information displayed in a predetermined area on the screen of the evaluator terminal 200 or selects the target information by pressing an area on the screen of the evaluator terminal 200 in a certain pattern, the selection unit 41 excludes the evaluation result by the evaluator and selects new target information.

[0142] Furthermore, when an evaluator performs an operation to display a screen different from the screen for evaluating the target information on the terminal device used by the evaluator, the selection unit 41 may select new target information based on the evaluation results excluding the evaluation results by the evaluator. For example, in the example of Fig. 2, when the selection unit 41 presents the target information to the evaluator via an e-commerce service or a coordination service and an app or web page related to another service is displayed on the evaluator terminal 200 during the presentation, the selection unit 41 excludes the evaluation results by the evaluator and selects new target information.

[0143] Furthermore, when the evaluator's evaluation of the target information satisfies a condition set based on information about the evaluator, the selection unit 41 may select new target information based on evaluation results that exclude the evaluation results of the evaluator. For example, in the example of FIG. 2, if the fashion category in which the evaluator is not good at is estimated to be "mode," the selection unit 41 does not exclude the evaluation results of the evaluator in the evaluation of target information showing outfits belonging to "mode," even if the time from when the target information is displayed until the evaluator selects it is equal to or exceeds a predetermined threshold. Furthermore, when the fashion category in which the evaluator is good at is estimated to be "casual," the selection unit 41 sets a time limit from when the target information is displayed until the evaluator selects it for the evaluator who is not good at "casual" fashion, shorter than that for other evaluators who are not good at "casual." If the time limit is exceeded, the selection unit 41 excludes the evaluation results of the evaluator and selects new target information.

[0144] Furthermore, when the content of an evaluator's evaluation of the target information satisfies a condition set based on the evaluator's purchase history of the item being rated, the selection unit 41 may select new target information based on evaluation results excluding the evaluation results by the evaluator. For example, in the example of FIG. 2, when the content of an evaluator's evaluation of the target information satisfies a condition set based on the evaluator's clothing purchase history, the selection unit 41 selects new target information based on evaluation results excluding the evaluation results by the evaluator. For example, in the example of FIG. 2, when the fashion category that the evaluator does not usually purchase is estimated to be "mode," the selection unit 41 does not exclude the evaluation results by the evaluator in evaluating target information showing an outfit belonging to "mode," even if the time from when the target information is displayed to when the evaluator selects it is equal to or exceeds a predetermined threshold. Furthermore, if it is estimated that the fashion category that the evaluator normally purchases is "casual," the selection unit 41 sets a time limit for the evaluator to select the target information showing an outfit that belongs to "casual" from the time the target information is displayed to the time the evaluator selects it, shorter than that for other evaluators who do not normally purchase "casual," and if the time limit is exceeded, the evaluation result by that evaluator is excluded and new target information is selected.

[0145] Furthermore, when the evaluator's evaluation of the target information satisfies a condition set based on the evaluator's browsing history of the target information, the selection unit 41 may select new target information based on the evaluation results excluding the evaluation results by the evaluator. For example, in the example of FIG. 2, when the evaluator's evaluation of the target information satisfies a condition set based on the evaluator's browsing history of outfits, the selection unit 41 selects new target information based on the evaluation results excluding the evaluation results by the evaluator. Furthermore, for example, in the example of FIG. 2, if the fashion category that the evaluator does not usually browse is estimated to be "mode," the selection unit 41 does not exclude the evaluation results by the evaluator in evaluating target information showing outfits belonging to "mode," even if the time from when the target information is displayed until the evaluator selects it is equal to or exceeds a predetermined threshold. Furthermore, if it is estimated that the fashion category that the evaluator normally views is "casual," the selection unit 41 sets a time limit for the evaluator to select the target information showing an outfit that belongs to "casual" from the time the target information is displayed to the time the evaluator makes a selection, which is shorter than that for other evaluators who do not normally view "casual," and if the time limit is exceeded, the evaluation result by that evaluator is excluded and new target information is selected.

[0146] (Regarding reception unit 42) The receiving unit 42 receives, from the evaluator, a first evaluation indicating which of the plurality of first target information selected by the selection unit 41 is favorable, and a second evaluation indicating which of the plurality of second target information selected by the selection unit 41 is favorable. For example, in the example of FIG. 2, the receiving unit 42 receives an evaluation (first evaluation) for target information group #1 and stores it in the evaluator information database 32. The receiving unit 42 also receives an evaluation (second evaluation) for target information group #2. The receiving unit 42 also receives an evaluation (second evaluation) for target information group #3. The receiving unit 42 also receives an evaluation (second evaluation) for target information group #4.

[0147] Furthermore, the receiving unit 42 may receive, from the evaluator, an evaluation indicating which of the plurality of pieces of target information selected by the selecting unit 41 is favorable. For example, in the example of Fig. 2, the receiving unit 42 receives, from the evaluator, an evaluation of the target information groups #1 to #4.

[0148] Furthermore, the receiving unit 42 may receive first and second evaluations from multiple evaluators who have corresponding attributes. For example, in the example of Fig. 2, the receiving unit 42 receives evaluations for the target information groups #1 to #4 from multiple evaluators who have corresponding attributes.

[0149] Furthermore, the receiving unit 42 may receive first and second evaluations from a plurality of evaluators corresponding to at least one of the following attributes: gender, age, place of residence, place of work, preferred category of the object to be evaluated, preferred fashion brand, preferred fashion genre, preferred fashion influencer, level of interest in the object to be evaluated, search tendency, browsing tendency, purchasing tendency, purchase amount, and information used as a reference for fashion. For example, in the example of Fig. 2, the receiving unit 42 receives evaluations of the target information groups #1 to #4 from a plurality of evaluators corresponding to at least one of the attributes: gender, age, preferred fashion category, level of interest in fashion, etc.

[0150] Furthermore, the receiving unit 42 may receive, from the evaluator, a first evaluation indicating which of the plurality of first target information selected by the selection unit 41 is favorable, and a third evaluation indicating which of the plurality of third target information selected by the selection unit 41 is favorable. For example, in the example of Fig. 2, the receiving unit 42 receives an evaluation from the evaluator regarding the target information to which the addition target "body type: other than hands" has been added.

[0151] (Regarding the estimation unit 43) The estimation unit 43 estimates the influence of the addition target on the evaluation of the evaluation target based on the relative relationship between the first evaluation and the second evaluation received by the reception unit 42. For example, in the example of Fig. 2, the estimation unit 43 estimates the influence of the addition target on the evaluation of the outfit based on the relative relationship between the evaluations of the target information groups #1 to #4 by the evaluators.

[0152] Furthermore, the estimation unit 43 may estimate that the greater the difference between the first evaluation and the second evaluation, the greater the degree of influence that the additional object has on the evaluation of the evaluation target. For example, in the example of Fig. 2, the estimation unit 43 estimates that the greater the difference between the score Sc1 and the score Sc2, the greater the degree of influence that the additional object "head" has on the evaluation of the outfit.

[0153] Furthermore, the estimation unit 43 may estimate whether the attachment target has a positive or negative influence on the evaluation of the evaluation target based on the difference between the first evaluation and the second evaluation. For example, in the example of FIG. 2, if the score Sc2 is higher than the score Sc1, the estimation unit 43 estimates that the attachment target "head" has a positive influence on the evaluation of the outfit, and if the score Sc2 is lower than the score Sc1, the estimation unit 43 estimates that the attachment target "head" has a higher degree of positive influence on the evaluation of the outfit, and the estimation unit 43 estimates that the attachment target "head" has a higher degree of negative influence on the evaluation of the outfit, the higher the score Sc2 is than the score Sc1.

[0154] Furthermore, the estimation unit 43 may estimate the influence that a part of the additional object has on the evaluation of the evaluation target, based on the relative relationship between the first evaluation and the third evaluation received by the reception unit 42. For example, in the example of Fig. 2, the estimation unit 43 estimates the influence that the additional object "body type: other than hands" has on the evaluation of the outfit, based on the evaluation from the evaluator.

[0155] Furthermore, the estimation unit 43 may estimate an additional target whose influence on the evaluation of the evaluation target by a predetermined user satisfies a predetermined condition, based on a first evaluation indicating an evaluation from an evaluator of first target information, which is information indicating only the evaluation target, and a second evaluation indicating an evaluation from an evaluator of second target information indicating both the evaluation target and an additional target. For example, in the example of Fig. 2, the estimation unit 43 estimates whether the influence of the additional target on the evaluation of the outfit satisfies a predetermined condition, based on the relative relationship of the evaluations of the target information groups #1 to #4 by the evaluators.

[0156] In addition, the estimation unit 43 may estimate whether the addition target has a positive or negative influence on the user's evaluation of the evaluation target. For example, in the example of Fig. 2, the estimation unit 43 estimates whether the addition target has a positive or negative influence on the evaluation of the outfit.

[0157] Furthermore, the estimation unit 43 may estimate an additional target whose influence on the user's evaluation of the evaluation target satisfies a predetermined condition, based on the first evaluation and the second evaluation by evaluators who have attributes corresponding to the user. For example, in the example of Fig. 2, the estimation unit 43 estimates whether the influence of the additional target on the evaluation of the outfit satisfies a predetermined condition, based on the evaluation of the target information in groups G1 to G4 to which evaluators who have attributes corresponding to the user U1 belong.

[0158] Furthermore, the estimation unit 43 may estimate an additional object whose influence on the user's evaluation of the evaluation object satisfies a predetermined condition based on the first and second evaluations by evaluators who correspond to the user in at least one of the following: gender, age, place of residence, place of work, preferred category of evaluation object, preferred fashion brand, preferred fashion genre, preferred fashion influencer, level of interest in the evaluation object, search tendency, browsing tendency, purchasing tendency, purchase amount, and information used as a reference for fashion. For example, in the example of Fig. 2, the estimation unit 43 estimates whether the influence of the additional object on the evaluation of the outfit satisfies a predetermined condition based on the evaluations of the target information in groups G1 to G4 to which evaluators who correspond to user U1 in attributes such as gender, age, place of residence, preferred fashion category, and level of interest in fashion belong.

[0159] (About the provider 44) The providing unit 44 provides the user with content related to the evaluation target based on the target to be added estimated by the estimation unit 43. For example, in the example of Fig. 2, the providing unit 44 provides content related to outfits to the user U1 based on the influence of the target to be added on the outfit.

[0160] The providing unit 44 may also provide content in which an additional object indicating at least one of an image of a person's head, information about the body type of the person using the evaluation object, the pose of the person using the evaluation object, the manner in which the evaluation object is used, the situation in which the evaluation object is used, and a background image is added to the evaluation object. For example, in the example of Fig. 2, the providing unit 44 provides content related to outfits to the user U1 based on the influence of the additional object "head," the additional object "body type," the additional object "pose," the additional object "outfit," and the additional object "background image" on the evaluation of the outfit.

[0161] Furthermore, the providing unit 44 may provide content in which an additional object estimated to have an influence on the user's evaluation of the evaluation object satisfies a predetermined condition is added to the evaluation object. For example, in the example of Fig. 2, the providing unit 44 provides the user U1 with content showing an outfit to which the additional object "head" or the additional object "body type" is added.

[0162] The providing unit 44 may also provide content in which an additional object corresponding to the purchase history of the evaluation object by the user is added to the evaluation object. For example, in the example of Fig. 2, if it is estimated that the additional object "head" has a positive effect on the evaluation of the outfit, the providing unit 44 provides content in which an image of a head corresponding to an image of clothing purchased by the user U1 through an e-commerce service or the like is added to the outfit.

[0163] Furthermore, the providing unit 44 may provide content in which an additional object corresponding to the browsing history of the evaluation object by the user is added to the evaluation object. For example, in the example of Fig. 2, if it is estimated that the additional object "head" has a positive effect on the evaluation of the outfit, the providing unit 44 provides content in which an image of a head corresponding to an image of an outfit to which the user U1 gave a positive reaction in a coordination service or the like is added to the outfit.

[0164] Furthermore, the providing unit 44 may preferentially provide content in which an additional object that is estimated to have an influence on the user's evaluation of the evaluation object satisfies a predetermined condition is added to the evaluation object. For example, in the example of Fig. 2, the providing unit 44 preferentially provides content related to outfits to which the additional object "head" or the additional object "body type" is added in an e-commerce service or a coordination service.

[0165] Furthermore, the providing unit 44 may provide the user with content related to the evaluation target depending on whether the additional target has a positive or negative influence on the user's evaluation of the evaluation target. For example, in the example of Fig. 2, the providing unit 44 provides content showing an outfit depending on whether the additional target has a positive or negative influence on the evaluation of the outfit.

[0166] Furthermore, the providing unit 44 may provide content in which an additional object estimated to have a positive influence is added to an evaluation object, and may provide content in which an additional object estimated to have a negative influence is not added to an evaluation object. For example, in the example of FIG. 2, if the additional object "head" is estimated to have a positive influence on the evaluation of an outfit, the providing unit 44 provides content showing an outfit to which the additional object "head" is added. Furthermore, if the additional object "head" is estimated to have a negative influence on the evaluation of an outfit, the providing unit 44 provides content showing an outfit to which the additional object "head" is not added.

[0167] Furthermore, the providing unit 44 may provide content in which an attachment target estimated to have a positive influence has been added to an evaluation target in preference to content in which an attachment target estimated to have a negative influence has been added to an evaluation target. For example, in the example of Fig. 2, the providing unit 44 provides content in which an attachment target estimated to have a positive influence has been added to an outfit in preference to content in which an attachment target estimated to have a negative influence has been added to an outfit in preference to content in which an attachment target estimated to have a negative influence has been added to an outfit.

[0168] (Regarding the setting unit 45) The setting unit 45 sets an evaluator whose evaluation content for the target information satisfies a predetermined condition to be excluded from the target for presenting the target information. For example, in the example of Fig. 2, the setting unit 45 sets an evaluator whose evaluation content satisfies a predetermined condition as an excluded person.

[0169] (Regarding the decision unit 46) The determination unit 46 determines whether or not to present the target information to an evaluator who has been set as not a target to present the target information by the setting unit 45, based on information about the evaluator. For example, in the example of FIG. 2, the determination unit 46 determines whether or not to present the target information to an evaluator based on information about an excluded person.

[0170] Furthermore, the determination unit 46 may determine whether or not to include an evaluator as a target for presenting the target information based on the evaluator's evaluation of the target information. For example, in the example of Fig. 2, the determination unit 46 determines whether or not to reinstate an excluded person as an evaluator based on the excluded person's evaluation of the target information.

[0171] Furthermore, the determination unit 46 may determine whether or not to present the target information to the evaluator based on the content of the evaluator's evaluation of the target information for which a correct answer has been set in advance. For example, in the example of Fig. 2, the determination unit 46 presents the correct target information and the incorrect target information to the excluded person a predetermined number of times, and returns the excluded person to the evaluators if the rate at which the correct target information is selected is equal to or greater than a predetermined threshold.

[0172] Furthermore, the determination unit 46 may determine whether or not to present the target to the evaluator based on information about the evaluator and information about the target information. For example, in the example of Fig. 2, when evaluating target information related to a fashion category in which the excluded person excels, the determination unit 46 returns the excluded person to the list of evaluators.

[0173] Furthermore, the determination unit 46 may determine whether to present the target to the evaluator based on information about the evaluator and information about other evaluators who present the target information. For example, in the example of Fig. 2, when presenting the target information to an evaluator corresponding to an attribute possessed by the excluded person, the determination unit 46 returns the excluded person to the evaluator list.

[0174] (About Study Section 47) The learning unit 47 learns a model based on the first evaluation and the second evaluation. For example, in the example of Fig. 2, the learning unit 47 learns model #2 by using outfits with ratings equal to or higher than a predetermined threshold as correct data.

[0175] [5. Information Processing Flow] The information processing procedure (1) of the information processing device 10 according to the embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart (1) showing an example of the information processing procedure according to the embodiment.

[0176] 9, the information processing device 10 selects a plurality of first target information and a plurality of second target information to be presented to the evaluator from among first target information indicating only the evaluation target and second target information indicating the evaluation target and additional targets (step S101). Subsequently, the information processing device 10 determines whether or not a first evaluation indicating which of the plurality of first target information is favorable and a second evaluation indicating which of the plurality of second target information is favorable have been received from the evaluator (step S102). If the first evaluation and the second evaluation have not been received (step S102; No), the information processing device 10 waits until the first evaluation and the second evaluation are received.

[0177] On the other hand, if the first rating and the second rating are received (step S102; Yes), the information processing device 10 estimates the influence of the added object on the rating of the rating object based on the relative relationship between the first rating and the second rating (step S103), and terminates the processing.

[0178] Next, the information processing procedure (2) of the information processing device 10 according to the embodiment will be described with reference to Fig. 10. Fig. 10 is a flowchart (2) showing an example of the information processing procedure according to the embodiment.

[0179] 10, the information processing device 10 determines whether or not a first evaluation indicating an evaluation of first target information, which is information indicating only an evaluation target, and a second evaluation indicating an evaluation of second target information, which indicates both the evaluation target and an additional target, have been received from an evaluator (step S201). If the first evaluation and the second evaluation have not been received (step S201; No), the information processing device 10 waits until the first evaluation and the second evaluation are received.

[0180] On the other hand, if the first evaluation and the second evaluation are received (step S201; Yes), the information processing device 10 estimates an additional target whose influence on the evaluation of the evaluation target by the predetermined user satisfies a predetermined condition based on the first evaluation and the second evaluation (step S202). Subsequently, the information processing device 10 provides the user with content related to the evaluation target based on the additional target that satisfies the predetermined condition (step S203), and ends the process.

[0181] Next, the information processing procedure (3) of the information processing device 10 according to the embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart (3) showing an example of the information processing procedure according to the embodiment.

[0182] 11, the information processing device 10 selects a plurality of pieces of target information to be presented to the evaluator from among pieces of target information indicating evaluation targets (step S301). Subsequently, the information processing device 10 determines whether or not an evaluation indicating which of the plurality of pieces of target information is favorable has been received from the evaluator (step S302). If an evaluation has not been received (step S302; No), the information processing device 10 waits until an evaluation is received.

[0183] On the other hand, if an evaluation is accepted (step S302; Yes), the information processing device 10 selects new target information based on the evaluation results excluding evaluation results by evaluators whose evaluation content for the target information satisfies specified conditions (step S303), and terminates the processing.

[0184] [6. Modifications] The above-described embodiment is merely an example, and various modifications and applications are possible.

[0185] [6-1. Processing mode] Of the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, and conversely, all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information, including the processing procedures, specific names, various data, and parameters shown in the above text 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.

[0186] 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.

[0187] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0188] [7. Effects] As described above, the information processing device 10 according to the embodiment includes a selection unit 41, a reception unit 42, an estimation unit 43, a provision unit 44, a setting unit 45, a determination unit 46, and a learning unit 47. The selection unit 41 selects a plurality of pieces of first target information and a plurality of pieces of second target information to be presented to the evaluator from among first target information indicating only the evaluation target and second target information indicating both the evaluation target and an additional target. The selection unit 41 also selects a plurality of pieces of first target information and a plurality of pieces of second target information to be presented to the evaluator from among first target information which is an image showing only clothing and second target information which is an image showing both clothing and an additional target. The selection unit 41 also selects a plurality of pieces of first target information and a plurality of pieces of second target information to be presented to the evaluator from among first target information which is an image showing only multiple clothing combinations and second target information which is an image showing multiple clothing combinations and an additional target. The selection unit 41 also selects multiple pieces of target information to be presented to the evaluator from among the target information indicating the evaluation targets. The selection unit 41 then selects new target information based on evaluation results obtained by the evaluators, excluding evaluation results by evaluators whose evaluations of the target information satisfy a predetermined condition. The selection unit 41 also selects multiple pieces of first target information to be presented to the evaluator from among first target information indicating combinations of evaluation targets identified using a model that has been trained to determine whether a combination of evaluation targets satisfies a predetermined condition, and selects multiple pieces of second target information to be presented to the evaluator from among second target information indicating combinations of evaluation targets identified using the model. The reception unit 42 receives, from the evaluator, a first evaluation indicating which of the multiple pieces of first target information selected by the selection unit 41 is favorable and a second evaluation indicating which of the multiple pieces of second target information selected by the selection unit 41 is favorable. The reception unit 42 also receives, from the evaluator, an evaluation indicating which of the multiple pieces of target information selected by the selection unit 41 is favorable. The estimation unit 43 estimates the influence of the additional target on the evaluation of the evaluation target based on the relative relationship between the first evaluation and the second evaluation received by the reception unit .The estimation unit 43 estimates an additional target whose influence on the evaluation of the evaluation target by a specific user satisfies a predetermined condition based on a first evaluation indicating an evaluation from an evaluator on first target information, which is information indicating only the evaluation target, and a second evaluation indicating an evaluation from an evaluator on second target information, which indicates both the evaluation target and an additional target. The provision unit 44 provides users with content related to the evaluation target based on the additional target estimated by the estimation unit 43. The setting unit 45 sets an evaluator whose evaluation content on the target information satisfies a predetermined condition to not be a target to which the target information is to be presented. The determination unit 46 determines whether or not to present the target information to an evaluator set by the setting unit 45 as not a target to which the target information is to be presented, based on information about the evaluator. The learning unit 47 learns a model based on the first evaluation and the second evaluation.

[0189] As a result, the information processing device 10 according to the embodiment can grasp the influence of additional features, such as head and body shape, on the evaluation of an outfit, in addition to the compatibility of the clothes that make up the outfit, and can grasp the influence of the features added to the evaluation target on the evaluation of the outfit. Furthermore, the information processing device 10 according to the embodiment can preferentially provide a user with content to which an additional feature estimated to have a positive influence on the evaluation of an outfit has been added, and can provide content to which the additional feature has been added if the additional feature has not been added. The influence of additional features, such as head and body shape, on the evaluation of an outfit can be grasped. In other words, the information processing device 10 according to the embodiment can provide content related to an evaluation target according to the influence of the features added to the evaluation target on the evaluation of the evaluation target. Furthermore, the information processing device 10 according to the embodiment can exclude evaluation results by evaluators estimated to be insincere, set appropriate ratings based on evaluation results by other diligent evaluators, and appropriately select target information to be presented to the evaluator. Therefore, the information processing device 10 according to the embodiment can select information to be presented to the evaluator according to the content of the evaluator's evaluation.

[0190] Furthermore, in the information processing device 10 according to the embodiment, for example, the selection unit 41 selects multiple pieces of second target information to be presented to the evaluator from second target information indicating at least one of an image of a person's head, information regarding the body shape of the person using the evaluation object, the pose of the person using the evaluation object, the manner in which the evaluation object is used, the situation in which the evaluation object is used, and a background image as an additional target.

[0191] As a result, the information processing device 10 according to the embodiment can grasp the influence that various additional objects have on the evaluation of the evaluation target, thereby improving convenience.

[0192] Furthermore, in the information processing device 10 according to the embodiment, for example, the selection unit 41 selects a plurality of pieces of first target information to be presented to the evaluator from the first target information based on a rating of the first target information calculated based on the first evaluation, and selects a plurality of pieces of second target information to be presented to the evaluator from the second target information based on a rating of the second target information calculated based on the second evaluation. The selection unit 41 selects a plurality of pieces of first target information from the first target information, the difference in ratings of which is within a predetermined range, and selects a plurality of pieces of second target information from the second target information, the difference in ratings of which is within a predetermined range. The selection unit 41 selects a plurality of pieces of first target information to be presented to the evaluator from the first target information based on the number of times the first target information has been evaluated by the evaluator, and selects a plurality of pieces of second target information to be presented to the evaluator from the second target information based on the number of times the second target information has been evaluated by the evaluator.

[0193] As a result, the information processing device 10 according to the embodiment can improve the accuracy of the rating of the target information and further increase the amount of information obtained by evaluating the target information, thereby enabling the target information to be evaluated efficiently.

[0194] In the information processing device 10 according to the embodiment, for example, the receiving unit 42 receives first and second evaluations from a plurality of evaluators having corresponding attributes. The receiving unit 42 also receives first and second evaluations from a plurality of evaluators corresponding to at least one of the following: gender, age, place of residence, place of work, preferred category of the evaluation target, preferred fashion brand, preferred fashion genre, preferred fashion influencer, level of interest in the evaluation target, search tendency, browsing tendency, purchasing tendency, purchase amount, and information used as a reference for fashion.

[0195] As a result, the information processing device 10 according to the embodiment can accept evaluations from evaluators with specified attributes, and can therefore understand the impact that the additional object has on the evaluation of the evaluation target for users with specified attributes.

[0196] In the information processing device 10 according to the embodiment, for example, the estimation unit 43 estimates that the greater the difference between the first evaluation and the second evaluation, the greater the degree of influence that the additional target has on the evaluation of the evaluation target. Furthermore, the estimation unit 43 estimates whether the additional target has a positive or negative influence on the evaluation of the evaluation target based on the difference between the first evaluation and the second evaluation.

[0197] As a result, the information processing device 10 according to the embodiment can grasp the degree of influence that the added object has on the evaluation of the evaluation object and the type of influence, and can therefore accurately grasp the influence that the added object has on the evaluation of the evaluation object.

[0198] Furthermore, in the information processing device 10 according to the embodiment, for example, the selection unit 41 selects a plurality of first target information and a plurality of third target information to be presented to the evaluator from among first target information indicating only the evaluation target and third target information indicating, together with the evaluation target, a portion of the additional target estimated to have an influence on the evaluation of the evaluation target. Then, the reception unit 42 receives from the evaluator a first evaluation indicating which of the plurality of first target information selected by the selection unit 41 is favorable, and a third evaluation indicating which of the plurality of third target information selected by the selection unit 41 is favorable. Then, the estimation unit 43 estimates the influence of a portion of the additional target on the evaluation of the evaluation target based on the relative relationship between the first evaluation and the third evaluation received by the reception unit 42.

[0199] As a result, the information processing device 10 according to the embodiment can subdivide the attachment objects that have an influence on the evaluation of the outfit and estimate the influence, thereby making it possible to accurately grasp which parts of the attachment objects have an influence.

[0200] Furthermore, in the information processing device 10 according to the embodiment, for example, the providing unit 44 provides content in which an additional object indicating at least one of an image of a person's head, information regarding the body shape of the person using the evaluation object, the pose of the person using the evaluation object, the manner in which the evaluation object is used, the situation in which the evaluation object is used, and a background image is added to the evaluation object.

[0201] As a result, the information processing device 10 according to the embodiment can provide content relating to an evaluation target to which various additional objects have been added depending on whether or not they have an effect on the evaluation of the evaluation target, thereby improving convenience.

[0202] Furthermore, in the information processing device 10 according to the embodiment, for example, the providing unit 44 provides the content related to the evaluation target taking into consideration an additional target that is estimated to have an influence on the user's evaluation of the evaluation target and that satisfies a predetermined condition. The providing unit 44 also provides content in which an additional target that is estimated to have an influence on the user's evaluation of the evaluation target and that satisfies a predetermined condition has been added to the evaluation target. The providing unit 44 also provides content in which an additional target corresponding to the user's purchase history of the evaluation target has been added to the evaluation target. The providing unit 44 also provides content in which an additional target corresponding to the user's browsing history of the evaluation target has been added to the evaluation target.

[0203] As a result, the information processing device 10 according to the embodiment can provide content relating to the evaluation target to which an additional target according to the user has been added, and therefore can provide content with a high appealing effect.

[0204] Furthermore, in the information processing device 10 according to the embodiment, for example, the providing unit 44 preferentially provides content to which an additional object is added to an evaluation object whose influence on the user's evaluation of the evaluation object is estimated to satisfy a predetermined condition.

[0205] As a result, the information processing device 10 of the embodiment can preferentially provide content related to an evaluation target to which an additional target has been added whose influence on the evaluation of the evaluation target meets specified conditions, and therefore can preferentially provide content with a high appeal.

[0206] Furthermore, in the information processing device 10 according to the embodiment, for example, the estimation unit 43 estimates whether the attachment target has a positive or negative influence on the user's evaluation of the evaluation target. Then, the provision unit 44 provides the user with content related to the evaluation target depending on whether the attachment target has a positive or negative influence on the user's evaluation of the evaluation target. Furthermore, the provision unit 44 provides content in which the attachment target estimated to have a positive influence has been added to the evaluation target, and provides content in which the attachment target estimated to have a negative influence has not been added to the evaluation target. Furthermore, the provision unit 44 provides content in which the attachment target estimated to have a positive influence has been added to the evaluation target, preferentially over content in which the attachment target estimated to have a negative influence has been added to the evaluation target.

[0207] As a result, the information processing device 10 according to the embodiment can provide content related to an evaluation target to which an additional target has been added depending on whether the evaluation target has a positive influence or a negative influence, thereby providing content with a high appeal.

[0208] Furthermore, in the information processing device 10 according to the embodiment, for example, the estimation unit 43 estimates an additional target whose influence on the user's evaluation of the target to be rated satisfies a predetermined condition based on a first evaluation and a second evaluation by an evaluator having attributes corresponding to the user. The estimation unit 43 also estimates an additional target whose influence on the user's evaluation of the target to be rated satisfies a predetermined condition based on a first evaluation and a second evaluation by an evaluator corresponding to the user in at least one of the following: gender, age, place of residence, place of work, preferred category of target to be rated, preferred fashion brand, preferred fashion genre, preferred fashion influencer, level of interest in the target to be rated, search tendency, browsing tendency, purchase tendency, purchase amount, and information used as a reference for fashion.

[0209] As a result, the information processing device 10 according to the embodiment can estimate the impact of the target to be added based on the evaluation by an evaluator who has attributes corresponding to the user, and can provide content, thereby providing content appropriate to the user's attributes.

[0210] Furthermore, in the information processing device 10 according to the embodiment, for example, when an evaluator evaluates dummy information presented together with target information or dummy information presented instead of target information as favorable, the selection unit 41 selects new target information based on the evaluation result excluding the evaluation result by the evaluator. Furthermore, when an evaluator evaluates any of the same target information as favorable, the selection unit 41 selects new target information based on the evaluation result excluding the evaluation result by the evaluator. Furthermore, when an evaluator evaluates target information previously set as the correct answer as unfavorable, the selection unit 41 selects new target information based on the evaluation result excluding the evaluation result by the evaluator. Furthermore, when the time required for the evaluator to evaluate the target information satisfies a predetermined condition, the selection unit 41 selects new target information based on the evaluation result excluding the evaluation result by the evaluator. Furthermore, when a position on the screen of the terminal device used by the evaluator where the evaluator performed an operation related to the evaluation of the target information satisfies a predetermined condition, the selection unit 41 selects new target information based on the evaluation result excluding the evaluation result by the evaluator. Furthermore, when an evaluator performs an operation on a terminal device used by the evaluator to display a screen other than the screen for rating the target information, the selection unit 41 selects new target information based on the evaluation results excluding the evaluation results by the evaluator. Furthermore, when the evaluator's evaluation content for the target information satisfies a condition set based on information about the evaluator, the selection unit 41 selects new target information based on the evaluation results excluding the evaluation results by the evaluator. Furthermore, when the evaluator's evaluation content for the target information satisfies a condition set based on the purchase history of the target that the evaluator has rated, the selection unit 41 selects new target information based on the evaluation results excluding the evaluation results by the evaluator. Furthermore, when the evaluator's evaluation content for the target information satisfies a condition set based on the browsing history of the target that the evaluator has rated, the selection unit 41 selects new target information based on the evaluation results excluding the evaluation results by the evaluator.

[0211] As a result, the information processing device 10 according to the embodiment uses various methods to exclude evaluation results from evaluators who are presumed to be irresponsible at any time, and can appropriately select the target information to be presented to the evaluator based on the evaluation results from other honest evaluators.

[0212] Furthermore, in the information processing device 10 according to the embodiment, for example, the determination unit 46 determines whether or not to present the target information to the evaluator based on the evaluator's evaluation of the target information. Furthermore, the determination unit 46 determines whether or not to present the target information to the evaluator based on the evaluator's evaluation of the target information for which a correct answer has been set in advance. Furthermore, the determination unit 46 determines whether or not to present the target to the evaluator based on information about the evaluator and information about the target information. Furthermore, the determination unit 46 determines whether or not to present the target to the evaluator based on information about the evaluator and information about other evaluators who present the target information.

[0213] As a result, the information processing device 10 according to the embodiment can reinstate an excluded person as an evaluator if the excluded person meets certain conditions, thereby enabling an evaluator who was excluded for inappropriate reasons to be reinstated.

[0214] [8. Hardware Configuration] The information processing device 10 according to each of the above-described embodiments is realized, for example, by a computer 1000 configured as shown in Fig. 12. The information processing device 10 will be described below as an example. Fig. 12 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. The computer 1000 has a CPU 1100, a 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.

[0215] 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.

[0216] The HDD 1400 stores programs executed by the CPU 1100, data used by such programs, etc. The communication interface 1500 receives data from other devices via a communication network 500 (corresponding to the network N in the embodiment) and sends the data to the CPU 1100, and also transmits data generated by the CPU 1100 to other devices via the communication network 500.

[0217] 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.

[0218] 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.

[0219] For example, when the computer 1000 functions as the information processing device 10, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200 to realize the functions of the control unit 40. The HDD 1400 also stores various data in the storage device of the information processing device 10. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined communication network.

[0220] [9. Other] Although some of the embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be 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.

[0221] Furthermore, the information processing device 10 described above can flexibly change its configuration, for example, by calling an external platform or the like using an API (Application Programming Interface) or network computing, depending on the function.

[0222] Furthermore, the term "unit" in the claims can be read as "means" or "circuit," etc. For example, a selection unit can be read as a selection means or a selection circuit. [Explanation of symbols]

[0223] 10. Information processing equipment 20 Communications Department 30 Storage section 31 Target Information Database 32 Evaluator Information Database 33 User Information Database 40 Control Unit 41 Selection section 42 Reception Department 43 Estimation part 44 Providing Department 45 Setting section 46 Decision Section 47 Learning Department 100 user terminals 200 Evaluator terminal

Claims

1. a selection unit that selects, for each of the plurality of evaluators, a plurality of pieces of target information to be presented to the plurality of evaluators from among the target information indicating the evaluation targets; a receiving unit that receives, for each of the evaluators, an evaluation indicating which of the plurality of pieces of target information selected by the selecting unit is favorable; a determination unit that determines, for each evaluator, whether or not the evaluator is a specific evaluator who satisfies a predetermined condition, based on the evaluation result for each evaluator received by the reception unit; An information processing device having: The selection unit When the determination unit determines that none of the evaluators is the specified evaluator, select, for each of the evaluators, a plurality of pieces of target information to be newly presented to the multiple evaluators based on the evaluation results of all the evaluators received by the reception unit; when the determination unit determines that any of the evaluators is the specified evaluator, select, for each of the other evaluators, a plurality of pieces of target information to be newly presented to the other evaluators excluding the specified evaluator from the evaluation results of all the evaluators received by the reception unit; The reception unit A new evaluation indicating which of the new plurality of pieces of target information selected by the selection unit is favorable is received for each of the other evaluators.

1. An information processing device comprising:

2. The selection unit If any of the evaluators is determined to be the specific evaluator who evaluated the dummy information presented together with the target information or the dummy information presented in place of the target information as favorable, a plurality of pieces of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on the evaluation results obtained by excluding the evaluation results by the specific evaluator from the evaluation results of all the evaluators.

2. The information processing apparatus according to claim 1, wherein:

3. The selection unit When any of the evaluators is determined to be the specific evaluator who evaluated any of the same target information as favorable, a plurality of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on the evaluation results obtained by excluding the evaluation results by the specific evaluator from the evaluation results of all the evaluators.

2. The information processing apparatus according to claim 1, wherein:

4. The selection unit When it is determined that any of the evaluators is the specific evaluator who evaluated the target information previously set as the correct answer unfavorably, a plurality of pieces of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on an evaluation result obtained by excluding the evaluation result by the specific evaluator from the evaluation results of all the evaluators.

2. The information processing apparatus according to claim 1, wherein:

5. The selection unit When it is determined that any one of the evaluators is the specific evaluator based on the time required to evaluate the target information and satisfy the predetermined condition, a plurality of pieces of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on the evaluation results excluding the evaluation results by the specific evaluator from the plurality of evaluators.

2. The information processing apparatus according to claim 1, wherein:

6. The selection unit When it is determined that a position on the screen of a terminal device used by any of the evaluators where an operation related to evaluation of target information is performed is the specific evaluator that satisfies the predetermined condition, a plurality of pieces of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on evaluation results excluding the evaluation results by the specific evaluator from the plurality of evaluators.

2. The information processing apparatus according to claim 1, wherein:

7. The selection unit When it is determined that any of the evaluators is a specific evaluator who has performed an operation to display a screen different from the screen for evaluating the target information on the terminal device used by the evaluator, a plurality of pieces of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on the evaluation results excluding the evaluation results by the specific evaluator from the plurality of evaluators.

2. The information processing apparatus according to claim 1, wherein:

8. The selection unit When any of the evaluators is determined to be a specific evaluator whose evaluation content for the target information satisfies a condition set based on information about the evaluator, a plurality of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on evaluation results excluding the evaluation results by the specific evaluator from the plurality of evaluators.

2. The information processing apparatus according to claim 1, wherein:

9. The selection unit When it is determined that any of the evaluators is a specific evaluator whose evaluation content for the target information satisfies a condition set based on the purchase history of the evaluator's evaluation target, a plurality of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on evaluation results excluding the evaluation results by the specific evaluator from the plurality of evaluators.

2. The information processing apparatus according to claim 1, wherein:

10. The selection unit When it is determined that any of the evaluators is a specific evaluator whose evaluation content for the target information satisfies a condition set based on the browsing history of the evaluator's evaluation target, a plurality of target information to be newly presented to the other evaluators excluding the specific evaluator from the plurality of evaluators is selected for each of the other evaluators based on the evaluation results excluding the evaluation results by the specific evaluator from the plurality of evaluators.

2. The information processing apparatus according to claim 1, wherein:

11. a setting unit that sets an evaluator whose evaluation content for the target information satisfies the predetermined condition as a non-target evaluator who is not a target for presenting the target information; a determination unit that determines whether or not the non-target evaluator, who has been set by the setting unit as not being a target for presenting target information, is a target for presenting target information based on information about the non-target evaluator.

2. The information processing apparatus according to claim 1, further comprising:

12. The determination unit Based on the evaluation content of the non-target evaluator for the predetermined target information, it is determined whether or not the non-target evaluator is a target for presenting the target information.

12. The information processing apparatus according to claim 11,

13. The determination unit Based on the evaluation content of the non-target evaluator for the target information for which a correct answer has been set in advance, it is determined whether or not the non-target evaluator is to be a target for presenting the target information.

12. The information processing apparatus according to claim 11,

14. The determination unit Based on information about the non-target evaluator and information about the target information, it is determined whether or not the non-target evaluator is a target to present the target information.

12. The information processing apparatus according to claim 11,

15. The determination unit Based on information about the non-target evaluator and information about a predetermined evaluator other than the non-target evaluator who is a target to which the target information is to be presented, it is determined whether or not the non-target evaluator is a target to which the target information is to be presented.

12. The information processing apparatus according to claim 11,

16. 1. A computer-implemented information processing method, comprising: a selection step of selecting, for each of a plurality of evaluators, a plurality of pieces of target information to be presented to the evaluators from among the target information indicating the evaluation targets; a receiving step of receiving, for each of the evaluators, an evaluation indicating which of the plurality of pieces of target information selected by the selecting step is favorable; a determination step of determining, for each evaluator, whether or not the evaluator is a specific evaluator who satisfies a predetermined condition, based on the evaluation result for each evaluator received in the receiving step; Including, The selection step includes: When it is determined in the determination step that none of the evaluators is the specified evaluator, a plurality of pieces of target information to be newly presented to the plurality of evaluators is selected for each of the evaluators based on the evaluation results of all the evaluators received in the reception step; when it is determined in the determination step that any of the evaluators is the specified evaluator, a plurality of pieces of target information to be newly presented to the other evaluators excluding the specified evaluator from the plurality of evaluators is selected for each of the other evaluators based on the evaluation results obtained by excluding the evaluation results of the specific evaluator from the evaluation results of all the evaluators received in the reception step; The receiving step includes: A new evaluation indicating which of the new plurality of pieces of target information selected by the selection step is favorable is received for each of the other evaluators. An information processing method comprising:

17. a selection step of selecting, for each of a plurality of evaluators, a plurality of pieces of target information to be presented to the evaluators from among the target information indicating evaluation targets; a receiving step of receiving, for each of the evaluators, an evaluation indicating which of the plurality of pieces of target information selected by the selection step is favorable; a determination step of determining, for each evaluator, whether or not the evaluator is a specific evaluator who satisfies a predetermined condition, based on the evaluation result for each evaluator received by the reception step; on the computer, The selection procedure comprises: When it is determined by the determination procedure that none of the evaluators is the specified evaluator, a plurality of pieces of target information to be newly presented to the multiple evaluators is selected for each of the evaluators based on the evaluation results of all the evaluators received by the reception procedure; when it is determined by the determination procedure that any of the evaluators is the specified evaluator, a plurality of pieces of target information to be newly presented is selected for each of the other evaluators based on the evaluation results obtained by excluding the evaluation results by the specified evaluator from the evaluation results of all the evaluators received by the reception procedure, the plurality of pieces of target information to be newly presented to the other evaluators excluding the specified evaluator from the multiple evaluators; The reception procedure is as follows: A new evaluation indicating which of the new plurality of pieces of target information selected by the selection procedure is favorable is received for each of the other evaluators. An information processing program characterized by:

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