JP2022057243A - Information processing device, information processing method and program - Google Patents

Abstract

To provide a user with information for determining whether to be close to other users in a sense of money.SOLUTION: According to an embodiment of the present invention, an information processing device 1 includes a classification part 122 for classifying a user into any of a plurality of types in association with each of a plurality of items corresponding to behaviors of the user, a calculation part 123 for calculating a feature quantity showing a trend of expenses of the user about each item on the basis of the type of the item in each of the plurality of items, and an output part 124 for outputting similar information corresponding to similarity between the feature quantity of a first user and the feature quantity of a second user to the first user.SELECTED DRAWING: Figure 2

Description

The present invention relates to an information processing apparatus, an information processing method and a program for outputting information regarding similarity between users.

Conventionally, there has been known a service of introducing another user as a candidate for a marriage partner or a lover to a user based on attributes such as hobbies and tastes of a plurality of users (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2020-95637

Even if the attributes such as hobbies and tastes are similar between the two users, the sense of money is not always close, so the standard of living and values do not match after the two users get married. There was a problem that it could be found.

Therefore, the present invention has been made in view of these points, and an object of the present invention is to provide a user with information for determining whether or not the sense of money is close to that of another user.

The information processing apparatus according to the first aspect of the present invention has a classification unit that classifies the user into one of a plurality of types in association with each of the plurality of items corresponding to the user's behavior, and each of the plurality of items. Corresponds to the similarity between the calculation unit that calculates the feature amount indicating the tendency of the user's expense regarding the item based on the type of the item, and the feature amount of the first user and the feature amount of the second user. It has an output unit that outputs similar information to the first user.

The output unit outputs information indicating one or a plurality of the second users having the feature amount within a predetermined range including the feature amount of the first user to the first user as the similar information. You may.

The output unit corresponds to the similarity between the feature amount of the first user calculated for each of the plurality of items and the feature amount of the second user calculated for the item. The similar information may be output.

The output unit includes the total value of the feature amount of the first user calculated for the plurality of items and the total value of the feature amount of the second user calculated for the plurality of items. The similarity information corresponding to the similarity of the above may be output.

The output unit may output the similarity information corresponding to the similarity specified by using the feature amount of one or a plurality of selection items selected from the plurality of items.

The output unit may select the one or a plurality of selection items from the plurality of items based on the input information by the first user.

The output unit may output the similarity information corresponding to the similarity specified by using the feature amount to which the weight associated with each of the plurality of items is applied.

The output unit may determine the weight associated with each of the plurality of items based on the input information by the first user.

The classification unit uses position information indicating the past position of the user, purchase history information indicating the product purchased by the user, usage content information indicating the content used by the user, and a questionnaire regarding the behavior of the user. The user may be classified into any of the plurality of types by using at least one of the questionnaire information indicating the answer given to the user.

The information processing method of the second aspect of the present invention includes a step of classifying the user into one of a plurality of types in association with each of a plurality of items corresponding to the user's actions executed by the processor, and the plurality of items. For each item, the step of calculating the feature amount indicating the tendency of the user to spend on the item based on the type of the item, and the similarity between the feature amount of the first user and the feature amount of the second user. It has a step of outputting the similar information corresponding to the above to the first user.

The program of the third aspect of the present invention relates to the processor to each of a plurality of items corresponding to the user's behavior, and classifies the user into one of the plurality of types, and in each of the plurality of items. A step of calculating a feature amount indicating a tendency of the user to spend on the item based on the type of the item, and a similarity corresponding to the similarity between the feature amount of the first user and the feature amount of the second user. The step of outputting the information to the first user and the step of outputting the information are executed.

According to the present invention, there is an effect that it is possible to provide a user with information for determining whether or not the sense of money is close to that of another user.

It is a figure which shows the outline of the information processing system which concerns on embodiment. It is a block diagram of the information processing system which concerns on embodiment. It is a schematic diagram for demonstrating the process which an information processing apparatus classifies a user. It is a schematic diagram for demonstrating the process which an information processing apparatus calculates a feature quantity. It is a front view of the user terminal displaying similar information. It is a figure which shows the flowchart of the information processing method executed by the information processing apparatus which concerns on embodiment.

[Overview of information processing system]
FIG. 1 is a diagram showing an outline of an information processing system according to the present embodiment. The information processing system includes an information processing device 1 and a plurality of user terminals 2. The information processing system may include other devices such as servers and terminals.

The information processing device 1 is a computer that outputs information on similarities between a plurality of users to a user terminal 2. The information processing device 1 is used, for example, to provide a matching service for matching a user with another user who is a candidate for a marriage partner or a lover. The user is, for example, a person registered in the matching service.

The user terminal 2 is an information terminal such as a smartphone, a tablet terminal, or a personal computer used by the user. The user terminal 2 displays the information output by the information processing device 1. The user terminal 2 has a display unit such as a liquid crystal display that displays information, and an operation unit such as a touch panel that accepts operations by the user. The user terminal 2 performs wireless communication or wired communication with the information processing device 1.

The outline of the processing executed by the information processing system according to the present embodiment will be described below. The information processing device 1 acquires behavioral information regarding the behavior of the user (1). The behavior information includes, for example, location information indicating the past position of the user, purchase history information indicating the product purchased by the user, usage content information indicating the content used by the user such as an application or a website, and behavior related to the user. Includes at least one of the questionnaire information indicating the answers given to the questionnaire.

The information processing device 1 specifies an action content such as what the user bought, what the user did, and where the user went, based on the acquired action information. The information processing apparatus 1 classifies the user into one of the plurality of types based on the specified action content in association with each of the plurality of items corresponding to the user's action (2). The information processing apparatus 1 classifies users for each item, for example, "frugal type" for the item of "lunch" and "rich type" for the item of "living style".

The information processing apparatus 1 calculates, for each of the plurality of items, a feature amount indicating the tendency of the user's expense related to the item based on the type of the item (3). The information processing apparatus 1 calculates a feature amount which is a numerical value indicating a tendency of the user's expense for each item, for example, 1 for the item of "lunch" and 3 for the item of "living style".

The information processing apparatus 1 determines the similarity between the feature amount calculated for the first user and the feature amount calculated for the second user, and provides similar information corresponding to the determined similarity to the first user. Output to the user terminal 2 used by (4).

In this way, the information processing apparatus 1 calculates the feature amount indicating the tendency of the user's expense by classifying the user in each of the plurality of items based on the action content of the user, and the feature amount is similar among the plurality of users. Output information about sex. As a result, the information processing apparatus 1 can provide the user with information for determining whether or not the sense of money is close to that of another user.

[Information processing system configuration]
FIG. 2 is a block diagram of an information processing system according to the present embodiment. In FIG. 2, the arrows indicate the main data flows, and there may be data flows other than those shown in FIG. In FIG. 2, each block shows not a hardware (device) unit configuration but a functional unit configuration. Therefore, the block shown in FIG. 2 may be mounted in a single device, or may be mounted separately in a plurality of devices. Data can be exchanged between blocks via any means such as a data bus, a network, and a portable storage medium.

The information processing device 1 has a storage unit 11 and a control unit 12. The information processing device 1 may be configured by connecting two or more physically separated devices by wire or wirelessly. Further, the information processing device 1 may be configured by a cloud, which is a collection of computer resources.

The storage unit 11 is a storage medium including a ROM (Read Only Memory), a RAM (Random Access Memory), a hard disk drive, and the like. The storage unit 11 stores in advance the program executed by the control unit 12. The storage unit 11 may be provided outside the information processing device 1, and in that case, data may be exchanged with the control unit 12 via a network.

The control unit 12 has an action specifying unit 121, a classification unit 122, a calculation unit 123, and an output unit 124. The control unit 12 is a processor such as a CPU (Central Processing Unit), and functions as an action specifying unit 121, a classification unit 122, a calculation unit 123, and an output unit 124 by executing a program stored in the storage unit 11. do. At least some of the functions of the control unit 12 may be performed by an electric circuit. Further, at least a part of the functions of the control unit 12 may be realized by the control unit 12 executing a program executed via the network.

Hereinafter, the processing executed by the information processing apparatus 1 will be described in detail. FIG. 3 is a schematic diagram for explaining a process in which the information processing apparatus 1 classifies users. The behavior specifying unit 121 acquires behavior information related to the behavior of each of the plurality of users. The behavior information is, for example, the position information indicating the past position of the user, the purchase history information indicating the product purchased by the user, the usage content information indicating the content used by the user, and the questionnaire regarding the behavior of the user. Includes at least one of the questionnaire information indicating the answer. The action specifying unit 121 acquires the action information from the user terminal 2, or acquires the action information from an external device different from the information processing device 1 and the user terminal 2.

The action specifying unit 121 specifies the action content of the user based on the acquired action information. The behavior specifying unit 121 specifies, for example, the place where the user lives and the place where the user stays, based on the location information. The behavior specifying unit 121 specifies, for example, that the user stays at a place in a predetermined range when the position information exists in the place during a predetermined period. The behavior specifying unit 121 identifies the product or service purchased by the user, for example, based on the purchase history information.

The behavior specifying unit 121 specifies, for example, the content posted by the user on the SNS (Social Networking Service) and the content browsed by the user based on the used content information. Further, the behavior specifying unit 121 is a product or service purchased by the user, a product or service desired by the user, a place where the user lives, and the user based on the content posted on the SNS by the user or the content viewed by the user. You may specify where you stayed. In addition, the behavior identification unit 121 determines the amount of expenses such as rent and food expenses of the user, the amount of income and savings of the user, and assets such as liabilities based on the information acquired from the contents such as the household account book service used by the user. It may be specified.

The behavior identification unit 121, for example, based on the response to the questionnaire indicated by the questionnaire information, the product or service purchased by the user, the place where the user lives, the place where the user stays, the amount of expenses such as the user's rent and food expenses, etc. , And identify assets such as user income and savings, and liabilities.

The behavior content of the user specified by the behavior specifying unit 121 is not limited to the specific information shown here, but may be a part of the above information, or may include other information regarding the user's behavior.

The classification unit 122 classifies the user into one of a plurality of types based on the action content specified by the action specifying unit 121 in association with each of the plurality of items corresponding to the user's behavior. The plurality of items are items corresponding to various actions such as meals, residence, travel hobbies, and purchases performed by the user. In the example of FIG. 3, the plurality of items are "lunch", "dinner", "drinking party", "how to spend the weekend", "living style", "long vacation", "savings", "clothes" and "clothes". It is a clock. The plurality of items are not limited to the specific items shown here.

The plurality of types are types corresponding to the degree of spending of the user. In the example of FIG. 3, the plurality of types are "frugal type", "intermediate type" and "rich type". In each item, the user is classified into "frugal type" when the degree of expense is low, "rich type" when the degree of expense is high, and "intermediate type" when the degree of expense is medium. The plurality of types are not limited to the specific types shown here.

An exemplary embodiment in which the classification unit 122 classifies the user into one of a plurality of types based on the action content will be described below. When classifying users based on location information, the classification unit 122 uses the user's stay location as the home or store based on the map information and the user's stay location specified by the behavior identification unit 121 based on the location information. , Park, leisure facility, domestic, overseas, etc. The classification unit 122 classifies the user into one of a plurality of types for each item based on the type of the determined staying place.

For example, the classification unit 122 presumes that the user brought a handmade lunch box when the place of stay is at home or office during the daytime for the item of "lunch", and puts the user in a "convenience store". Classify users into "intermediate type" by presuming that the user purchased a lunch box when the place of stay is a convenience store (hereinafter, convenience store) or supermarket (hereinafter, supermarket), and the place of stay is a restaurant. In some cases, it is presumed that the user has eaten out and the user is classified as "rich type".

For example, the classification unit 122 presumes that the user stays at home or returns to his / her parents' home when the long-term stay place is a specific place different from the user's home or home for the item of "long vacation". Users are classified as "frugal type", and users are classified as "intermediate type" by presuming that the user has traveled domestically when the long-term stay location is multiple locations in Japan, and the long-term stay location is overseas. In the case of a place, it is estimated that the user has traveled abroad and the user is classified as "rich type". In this case, the classification unit 122 may acquire the user's schedule information and specify the period of the long vacation.

The classification unit 122 may repeat the above-mentioned classification process for the information for a predetermined period, and determine the classification obtained most for one user as the classification of the user.

When classifying users based on purchase history information, the classification unit 122 uses a plurality of types of users for each item based on the products or services purchased by the user specified by the behavior identification unit 121 based on the purchase history information. Classify into one of.

For example, the classification unit 122 presumes that the user brought a handmade lunch box for the item of "lunch" when the user did not purchase food and drink during the daytime, and made it "frugal". Classify users, presume that the user purchased a lunch box if there is a purchase history at a convenience store or supermarket, classify the user into "intermediate type", and if there is a purchase history at a restaurant, the user eats out It is estimated that the user has been classified as "rich type".

For example, the classification unit 122 presumes that the user stays at home or returns to his / her parents' home when there is a purchase history at a specific place different from the user's home or home for the item of “long vacation”. Users are classified into "frugal type", and if there is a purchase history in multiple places in Japan, it is estimated that the user has traveled domestically, and users are classified into "intermediate type", and the purchase history in overseas places is In some cases, it is presumed that the user has traveled abroad and the user is classified as "rich type". In this case, the classification unit 122 may acquire the user's schedule information and specify the period of the long vacation.

The classification unit 122 may repeat the above-mentioned classification process for the information for a predetermined period, and determine the classification obtained most for one user as the classification of the user.

When classifying users based on the usage content information, the classification unit 122 is known for images or comments contained in the content posted to the SNS or the browsing content specified by the behavior specifying unit 121 based on the usage content information. By performing image recognition processing and parsing processing, the thing or place related to the posted content or browsing content is specified. The classification unit 122 classifies the user into one of a plurality of types for each item based on the thing or place specified from the posted content or the browsed content.

For example, the classification unit 122 brings a handmade bento by the user when the posted content includes an image or a comment about the handmade bento for the item of "lunch", or when the browsed content includes the site of the bento recipe. It is estimated that the user is classified as "frugal type". In addition, the classification unit 122 presumes that the user purchased the lunch box when the posted content includes images and comments related to the lunch box of the convenience store or supermarket, or when the browsing content includes a site introducing the lunch box of the convenience store or supermarket. Classify users into "intermediate type". In addition, the classification unit 122 presumes that the user has eaten out when the posted content includes an image or comment related to the food of the restaurant, or when the browsing content includes the site of the restaurant, and the user is set to "rich type". Classify.

The classification unit 122 includes, for example, an image or comment regarding a specific place where the posted content is different from the user's home or home for the item of "long vacation", or the browsing content is DIY (Do It Yourself) or home. Classify users as "frugal" by presuming that the user stayed at home or returned to their parents' home when the site related to the surrounding area is included. In addition, the classification unit 122 allows the user to travel domestically when the posted content includes images and comments related to domestic tourist destinations and domestic hotels, or when the browsed content includes sites related to domestic tourist destinations and domestic hotels. It is estimated that users are classified as "intermediate type". In addition, in the classification unit 122, the user travels abroad when the posted content includes images and comments related to overseas tourist destinations and overseas hotels, or when the browsed content includes sites related to overseas tourist destinations and overseas hotels. Estimate and classify users into "rich type". In this case, the classification unit 122 may acquire the user's schedule information and specify the period of the long vacation.

The classification unit 122 may repeat the above-mentioned classification process for the information for a predetermined period, and determine the classification obtained most for one user as the classification of the user.

When classifying users based on questionnaire information, the classification unit 122 classifies users into one of a plurality of types for each item based on the response to the questionnaire specified by the behavior identification unit 121 based on the questionnaire information. do.

It is assumed that the user responded to the questionnaire "What do you eat for lunch?" By either (1) handmade lunch box, (2) convenience store or supermarket lunch box, or (3) eating out. .. For example, the classification unit 122 classifies the user into a "frugal type" when the user's answer is a handmade lunch box for the item "lunch", and when the user's answer is a convenience store or supermarket lunch box, " Classify users into "intermediate type" and classify users into "rich type" when the user's answer is eating out.

It is assumed that the user responds to the questionnaire "How to spend a long vacation?" By either (1) home or homecoming, (2) domestic travel, or (3) overseas travel. For example, the classification unit 122 classifies the user into "frugal type" when the user's answer is home or homecoming for the item of "long vacation", and "intermediate" when the user's answer is domestic travel. Classify users into "types" and classify users into "rich types" when the user's answer is an overseas trip.

The classification unit 122 may repeat the above-mentioned classification process for the information for a predetermined period, and determine the classification obtained most for one user as the classification of the user.

The classification unit 122 is not limited to the specific classification process shown here, and the user may be classified for each of a plurality of items based on other behavior contents specified by the behavior identification unit 121 from the behavior information.

FIG. 4 is a schematic diagram for explaining a process in which the information processing apparatus 1 calculates a feature amount. The calculation unit 123 is a feature amount showing the tendency of the user's expense related to the item based on the type of the item in each of the plurality of items based on the result of the classification unit 122 classifying the user into one of the plurality of types. Is calculated.

For example, in each of a plurality of items, the calculation unit 123 sets the similarity to 1 when the type is "frugal type", 2 when the type is "intermediate type", and the type is "rich type". In the case, the similarity is calculated as 3. The feature amount is not limited to the specific value shown here. Further, the calculation unit 123 calculates the total value of the feature quantities calculated for the plurality of items.

The calculation unit 123 calculates the degree of similarity indicating the similarity between the feature amount of the first user and the feature amount of the second user. For example, the first user is a user who has performed an operation for viewing similar information on the user terminal 2, and the second user is a user different from the first user.

The degree of similarity is a value indicating the degree of similarity, and is, for example, an absolute value of the difference between the feature amount of the first user and the feature amount of the second user in the value for each item or the total value. In this case, the smaller the degree of similarity, the more similar the feature amount of the first user and the second user, and the larger the degree of similarity, the more similar the feature amount of the first user and the feature amount of the second user. It can be said that it has not been done. The degree of similarity is not limited to the specific value described here, and may be another value indicating the degree of similarity.

The calculation unit 123 calculates the degree of similarity between the feature amount of the first user calculated for each of the plurality of items and the feature amount of the second user calculated for the item. Further, the calculation unit 123 determines the degree of similarity between the total value of the features of the first user calculated for the plurality of items and the total value of the features of the second user calculated for the plurality of items. It may be calculated.

The output unit 124 uses the user terminal 2 in which the first user uses similar information corresponding to the similarity between the feature amount of the first user and the feature amount of the second user based on the similarity calculated by the calculation unit 123. Output to. The similar information is information for determining whether or not the first user has a similar sense of money to the second user.

The output unit 124 outputs, for example, information indicating one or a plurality of second users having a feature amount within a predetermined range including the feature amount of the first user as similar information. In this case, the output unit 124 is the sum of the feature amounts close to the total value of the feature amounts of the second user having the feature amount close to the feature amount of the first user in each of the plurality of items or the first user of the plurality of items. Extract the second user with the value. Then, the output unit 124 outputs the extracted information indicating one or a plurality of second users to the user terminal 2 used by the first user as similar information. That is, the output unit 124 matches one or a plurality of second users whose features are close to each other with respect to the first user.

Further, the output unit 124 does not directly use the numerical value of the feature amount, but based on the number of items whose types match between the first user and the second user among a plurality of items, the feature of the first user. A second user having a feature amount close to the amount may be extracted. For example, when the number of items whose types match between the first user and the second user is equal to or more than a predetermined value, the output unit 124 states that the first user and the second user have similar feature amounts. The determination is made, and the information indicating the second user is output to the user terminal 2 used by the first user as similar information.

The output unit 124 is not limited to the specific method shown here, and the proximity of the feature amount is set in the difference in the feature amount of each of the plurality of items, the difference in the total value of the feature amount of the plurality of items, and the plurality of items. Judgment is made using an arbitrary index such as the number of items whose feature amount difference is less than or equal to a predetermined value. As a result, the information processing apparatus 1 notifies the first user of the information of the second user whose feature amount is similar to that of the first user, and gives the first user a sense of money with the second user. Can provide information to determine if is close.

Further, the output unit 124 may output information indicating the degree of similarity of the feature amounts of each of the plurality of second users to the first user as the similarity information. In this case, the output unit 124 associates the user information such as the name and facial photograph of each of the plurality of second users with the similarity of the feature amount of the second user to the first user, and is used by the first user. Output to the user terminal 2 The output unit 124 may output a plurality of second users in order of the degree of similarity of the feature amounts. As a result, the information processing apparatus 1 notifies the first user of information indicating the similarity of the feature amount indicating the tendency of spending for each of the plurality of second users, and the first user feels like money with the second user. It can provide information to determine if it is close.

Further, the output unit 124 may specify the similarity by using the feature amount to which the weight associated with each of the plurality of items is applied. In this case, the output unit 124 acquires the input information to be used for determining the weight in the user terminal 2. The input information is, for example, a weight specified by the user for each item, or a user attribute (hobby, etc.) related to the user.

Based on the acquired input information, the output unit 124 determines the weight specified for each item by the user or the weight determined based on the user attribute as the weight associated with each of the plurality of items. For example, when the user's hobby is "travel", the output unit 124 determines a larger weight for items such as "how to spend the weekend" and "long vacation" than other items.

The output unit 124 applies the determined weights to each of the plurality of items, and then outputs similar information corresponding to the similarity between the feature amount of the first user and the feature amount of the second user. The output unit 124, for example, applies a weight to the feature amount of each of the plurality of items, and then selects a second user having a feature amount or a total value of the feature amount close to the feature amount or the total value of the feature amount of the first user. Extract. Further, the output unit 124 may output information indicating the similarity of the feature amounts of each of the plurality of second users to the first user as similar information after applying weights to the feature amounts of each of the plurality of items. good. As a result, the information processing apparatus 1 identifies the similarity between users by using the feature amount to which different weights are applied to each item according to the input information of the user, and the similar information reflecting the items to be emphasized for each user. Can be presented to the user.

Further, the output unit 124 may specify the similarity by using the feature amount of one or a plurality of selected items selected from a plurality of items instead of all of the plurality of items. In this case, the output unit 124 acquires the input information to be used for selecting the selection item in the user terminal 2. The input information is, for example, an item specified by the user or a user attribute (hobby, etc.) related to the user.

The output unit 124 selects an item specified by the user or an item related to the user attribute as a selection item based on the acquired input information. The items related to the user attribute are, for example, items such as "how to spend the weekend" and "long vacation" when the user's hobby is "travel".

The output unit 124 is a user terminal in which the first user uses similar information corresponding to the similarity (similarity) between the feature amount of the first user and the feature amount of the second user in the selected one or a plurality of selected items. Output to 2. Thereby, the information processing apparatus 1 can specify the similarity between users by using the items corresponding to the input information of the users, and can present the similar information reflecting the items to be emphasized for each user to the user.

FIG. 5 is a front view of the user terminal 2 displaying similar information. In the example of FIG. 5, the user terminal 2 used by the first user displays information indicating the three second users extracted by the output unit 124 as similar information. The information indicating the second user includes user information such as the name and face photograph of the second user and the degree of similarity of the feature amount of the second user to the first user. In the example of FIG. 5, the user terminal 2 is not the similarity itself calculated by the above-mentioned calculation unit 123, but an index obtained by converting the similarity according to a predetermined rule, for example, the higher the similarity, the larger the value. Shows the converted value.

The user terminal 2 is not limited to the second user extracted by the output unit 124, and may display information indicating the degree of similarity of the feature amounts of all the second users to the first user as similar information. The output unit 124 may output a plurality of second users in order of the degree of similarity of the feature amounts. As a result, the first user can refer to the similar information displayed on the user terminal 2 and determine whether or not the second user has a similar sense of money.

[Information processing method sequence]
FIG. 6 is a diagram showing a flowchart of an information processing method executed by the information processing apparatus 1 according to the present embodiment. The behavior specifying unit 121 acquires behavior information related to the behavior of each of the plurality of users (S11). The action specifying unit 121 specifies the action content of the user based on the acquired action information (S12).

The classification unit 122 classifies the user into one of the plurality of types based on the action content specified by the action specifying unit 121 in association with each of the plurality of items corresponding to the user's behavior (S13). The plurality of types are types corresponding to the degree of spending of the user, and are, for example, "frugal type", "intermediate type", and "rich type".

The calculation unit 123 is a feature amount showing the tendency of the user's expense related to the item based on the type of the item in each of the plurality of items based on the result of the classification unit 122 classifying the user into one of the plurality of types. Is calculated (S14). The calculation unit 123 calculates the degree of similarity indicating the similarity between the feature amount of the first user and the feature amount of the second user (S15).

The output unit 124 uses the user terminal 2 in which the first user uses similar information corresponding to the similarity between the feature amount of the first user and the feature amount of the second user based on the similarity calculated by the calculation unit 123. Is output to (S16).

[Effect of embodiment]
In the information processing system according to the present embodiment, as described above, the information processing apparatus 1 calculates the feature amount indicating the tendency of the user's expense by classifying the user into each of the plurality of items based on the action content of the user. , Outputs information about the similarity of features between multiple users. As a result, the information processing apparatus 1 can provide the user with information for determining whether or not the sense of money is close to that of another user.

Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes can be made within the scope of the gist. be. For example, all or part of the device can be functionally or physically distributed / integrated in any unit. Also included in the embodiments of the present invention are new embodiments resulting from any combination of the plurality of embodiments. The effect of the new embodiment produced by the combination has the effect of the original embodiment together.

The processor of the information processing apparatus 1 is the main body of each step (process) included in the information processing method shown in FIG. That is, the processor of the information processing apparatus 1 reads a program for executing the information processing method shown in FIG. 6 from the storage unit, executes the program, and controls each part of the information processing system, thereby showing in FIG. Execute the information processing method. Some of the steps included in the information processing method shown in FIG. 6 may be omitted, the order between the steps may be changed, or a plurality of steps may be performed in parallel.

1 Information processing device 12 Control unit 121 Behavior identification unit 122 Classification unit 123 Calculation unit 124 Output unit 2 User terminal

Claims (11)

A classification unit that classifies the user into one of a plurality of types in association with each of a plurality of items corresponding to the user's behavior.
In each of the plurality of items, a calculation unit for calculating a feature amount indicating a tendency of the user's expense regarding the item based on the type of the item, and a calculation unit.
An output unit that outputs similar information corresponding to the similarity between the feature amount of the first user and the feature amount of the second user to the first user, and
Information processing device. The output unit outputs information indicating one or a plurality of the second users having the feature amount within a predetermined range including the feature amount of the first user to the first user as the similar information. ,
The information processing apparatus according to claim 1. The output unit corresponds to the similarity between the feature amount of the first user calculated for each of the plurality of items and the feature amount of the second user calculated for the item. Output the similar information,
The information processing apparatus according to claim 1 or 2. The output unit includes the total value of the feature amount of the first user calculated for the plurality of items and the total value of the feature amount of the second user calculated for the plurality of items. Outputs the similarity information corresponding to the similarity of
The information processing apparatus according to claim 1 or 2. The output unit outputs the similarity information corresponding to the similarity specified by using the feature amount of one or a plurality of selection items selected from the plurality of items.
The information processing apparatus according to any one of claims 1 to 4. The output unit selects the one or a plurality of selection items from the plurality of items based on the input information by the first user.
The information processing apparatus according to claim 5. The output unit outputs the similarity information corresponding to the similarity specified by using the feature amount to which the weight associated with each of the plurality of items is applied.
The information processing apparatus according to any one of claims 1 to 6. The output unit determines the weight associated with each of the plurality of items based on the input information by the first user.
The information processing apparatus according to claim 7. The classification unit uses position information indicating the past position of the user, purchase history information indicating the product purchased by the user, usage content information indicating the content used by the user, and a questionnaire regarding the behavior of the user. The user is classified into one of the plurality of types by using at least one of the questionnaire information indicating the answer given to the user.
The information processing apparatus according to any one of claims 1 to 8. The processor runs,
A step of classifying the user into one of a plurality of types in association with each of the plurality of items corresponding to the user's behavior.
In each of the plurality of items, a step of calculating a feature amount indicating the tendency of the user to spend on the item based on the type of the item, and a step of calculating the feature amount.
A step of outputting similar information corresponding to the similarity between the feature amount of the first user and the feature amount of the second user to the first user, and
Information processing method. To the processor
A step of classifying the user into one of a plurality of types in association with each of the plurality of items corresponding to the user's behavior.
In each of the plurality of items, a step of calculating a feature amount indicating the tendency of the user to spend on the item based on the type of the item, and a step of calculating the feature amount.
A step of outputting similar information corresponding to the similarity between the feature amount of the first user and the feature amount of the second user to the first user, and
A program that runs.

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