JP6703571B2 - Information processing apparatus, information processing method, and information processing program - Google Patents

Description

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

Conventionally, for example, there is an information processing apparatus that estimates various characteristics of a user by providing various services to the user and analyzing the attributes of the user obtained by using the service. In this type of information processing apparatus, the service provided by itself may be optimized based on the estimated characteristics of the user.

JP, 2008-322252, A

However, the above-mentioned technology analyzes the characteristics of the user individually for each service and applies the analysis result to the optimization of its own service. Considering the use of the analysis results of other services, Was not done.

Further, if it is attempted to cooperate with another service, technical difficulties are involved in effectively applying the analysis result of the other service to the own service. In other words, it is difficult to obtain the analysis results of other services because the technical gap between the services is large.

The present application has been made in view of the above, and provides an information processing device, an information processing method, and an information processing program capable of acquiring an analysis result of another service without being aware of a gap between the services. With the goal.

The information processing device according to the present application includes an acquisition unit and a provision unit. The acquisition unit acquires, from different services, characteristic information including at least one of a model for estimating the characteristics of the user by using the attributes of the user and an estimation result regarding the characteristics estimated by using the attributes. To do. The providing unit provides the provided information based on the characteristic information acquired by the acquisition unit to another service.

According to the aspect of the embodiment, it is possible to obtain the analysis result of another service without being aware of the gap between the services.

FIG. 1 is a diagram illustrating an example of information processing according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the information processing system according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the information processing device according to the embodiment. FIG. 4 is a diagram showing an example of shared information. FIG. 5 is a diagram showing an example of service information. FIG. 6 is a diagram showing an example of model program information. FIG. 7 is a diagram showing an updating process by the updating unit. FIG. 8 is a flowchart showing a procedure of processing executed by the information processing apparatus according to the embodiment. FIG. 9 is a flowchart showing the procedure of the providing process executed by the information processing apparatus according to the embodiment. FIG. 10 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device according to the embodiment.

Hereinafter, modes (hereinafter, referred to as “embodiments”) for implementing an information processing device, an information processing method, and an information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited by this embodiment. Also, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicate description will be omitted.

First, an example of information processing performed by the information processing apparatus according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of information processing according to the embodiment. FIG. 1 shows an information processing system S including an information processing device 1 according to the embodiment. As shown in FIG. 1, the information processing system S according to the embodiment includes an information processing device 1, a service providing server 10 (10-1, 10-2, 10-3), and a user terminal 100.

The user terminal 100 is a terminal device owned by the user U. The user U uses the service Y (Y1, Y2, Y3) provided by each service providing server 10 by operating the user terminal 100 to access the service providing server 10 (steps S1-1, S1-2). , S1-3).

The service providing server 10 is a server device that provides various services Y to the user U. The service Y provided by the service providing server 10 is, for example, a service that delivers information via various applications installed in the user terminal 100. Such services include, for example, news service, auction service, weather forecast service, shopping service, financial transaction (stock trading, etc.) service, route search service, map provision service, travel service, restaurant introduction service, blog. There are services etc. Note that the service Y is not limited to a service in which information is distributed via an application, and may be, for example, a service in which the user U provides information by accessing a browser.

In FIG. 1, the service Y1 is a shopping service that provides a shopping site, the service Y2 is a map providing service that provides a map-related function, and the service Y provides a search site for searching various information. The search service will be described as an example.

Further, each service providing server 10 estimates the characteristics of the user U by analyzing the attributes of the user U who used the service Y. Specifically, each service providing server 10 uses at least one of a model for estimating the characteristics of the user U by using the attributes of the user U and an estimation result regarding the characteristics of the user U estimated by using the attributes of the user U. The characteristic information including is generated (steps S2-1, S2-2, S2-3).

The attribute mentioned here is a fixed attribute of the user U or a characteristic of the user U. For example, action information regarding the action of the user U when using the service Y such as a search log and a purchase history, and sex, It is a concept including demographic attributes such as age and address, and psychographic attributes such as life cycle, values, individuality, and motive for purchasing.

The characteristic of the user U is the property of the user U estimated by including various attributes of the user U, or the estimated attribute, and, for example, the interest of the user U, hobbies and preferences, behavior Includes patterns (search behavior, purchasing behavior, etc.).

Further, the above model in the characteristic information can input the attribute of the user U and output the characteristic of the user U as a score, for example. Further, the above-mentioned estimation result in the characteristic information is, for example, a score output by the model. The estimation result may be information that does not depend on the model, for example, information in which the attribute of the user U is simply quantified (for example, a score that increases or decreases according to the number of searches).

In the example shown in FIG. 1, the service Y1 as a shopping service generates a model of “I like fishing” and a score “2.3” which is an estimation result. In addition, the service Y1 generates a model of "like fishing" based on, for example, a purchase history of fishing products.

In addition, the service Y2 as the map providing server generates a “car lover” model and an estimation result score “3.5”. It should be noted that the service Y2 generates a "car lover" model based on, for example, a history of route searches to a car dealer, whether or not a car is owned, and the like.

Further, the service Y3 as a search service generates a model of “traveling” and a score “9.8” which is an estimation result. It should be noted that the service Y3 generates a "travel favorite" model based on, for example, a search history using search words related to travel. It should be noted that in FIG. 1, the higher the score, the more the user U has the characteristic that he or she has a strong interest or preference for the thing represented by the model.

Moreover, although the above-mentioned score has shown the case where it is a continuous value, it may be a discrete value, for example. Specifically, whether or not one likes fishing may be expressed by a score of a discrete value of "1" (like) or "0" (dislike). Alternatively, although the score is shown as an example of the estimation result, the estimation result is not limited to the score, and may be text information such as “like fishing”.

Here, conventionally, the feature information individually generated by a service is used only for optimizing its own service, and use of the feature information of other services has not been considered.

In addition, if it is attempted to cooperate with other services, in order to effectively apply the characteristic information of the other services to the own service, it is necessary to understand which service has what characteristic information. is necessary. However, conventionally, since it is difficult to accurately grasp the characteristic information of other services, it is difficult to use the characteristic information of other services.

Therefore, the information processing apparatus 1 according to the embodiment is configured so that the feature information generated by each service Y can be shared by other services Y. Specifically, the information processing apparatus 1 according to the embodiment acquires the above-described characteristic information from each of the different services Y (steps S3-1, S3-2, S3-3), and links the characteristic information for each user. The attached shared information is generated (step S4).

Note that the information processing apparatus 1 according to the embodiment is not limited to the case of acquiring the above-described model and the characteristic information including the score as the estimation result, and the characteristic information including only the model or the characteristic information including only the score. May be obtained.

Subsequently, the information processing apparatus 1, when requested by the service Y, provides the provided information based on the acquired characteristic information (steps S5-1, S5-2, S5-3). For example, there are the following two methods of providing additional information.

The first is a method in which the service providing server 10 specifies a specific user U and provides the characteristics (estimation result) of the specified user U based on the shared information. That is, the service Y can know the characteristics of the user U regarding the specific user U, which cannot be obtained by analyzing the service Y of itself. The second is a method in which the service providing server 10 specifies a specific characteristic and provides a list of users U having the specified characteristic based on shared information. As a result, the service Y can know the user U who has a characteristic that cannot be obtained by analyzing the service Y of itself.

That is, in the information processing method according to the embodiment, the characteristic information acquired from each of the different services Y is stored in association with each user. The other service Y comprehensively acquires the attribute associated with the user U or the information of the user U associated with the attribute by allowing the accumulated characteristic information to be acquired by the other service Y. You can

Therefore, in the information processing method according to the embodiment, since the other service Y can comprehensively acquire the information of the user U as the characteristic information, the characteristic information of the other service Y can be easily grasped and used. That is, according to the information processing method according to the embodiment, it is possible to acquire the characteristic information that is the analysis result of another service Y without being aware of the gap between the services Y.

Next, the configuration of the information processing system S according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of the information processing system S according to the embodiment. As shown in FIG. 2, the information processing system S according to the embodiment includes an information processing device 1, a plurality of service providing servers 10-1 to 10-n, and a plurality of user terminals 100-1 to 100-m. Including. The information processing device 1, the plurality of service providing servers 10-1 to 10-n, and the plurality of user terminals 100-1 to 100-m are connected via a network N. The network N is a communication network such as a LAN (Local Area Network), a WAN (Wide Area Network), a telephone network (a mobile telephone network, a fixed telephone network, etc.), a regional IP (Internet Protocol) network, and the Internet. The network N may include a wired network or a wireless network.

The user terminal 100 is a terminal device used by the user U, as described above. The user terminal 100 is, for example, a smart device (smartphone or tablet), a mobile phone, a personal computer, or the like. The user terminal 100 transmits a request for information to the service providing server 10 according to the operation of the user U.

The information processing device 1 is a server device that functions as a host server of the service providing server 10. The information processing apparatus 1 acquires characteristic information from each service providing server 10 to generate shared information, and also provides various information to the service providing server 10 using the generated shared information.

The service providing server 10 is a server device that provides the service Y to the user U as described above. The service providing server 10 analyzes the attribute of the user U who has used the service Y, and generates the characteristic information, for example. The service providing server 10 also requests the information processing device 1 for the additional information. The request for additional information is transmitted from the service providing server 10 when the administrator of the service Y operates the dedicated terminal connected to the service providing server 10, for example.

Further, in the information processing system S, the information processing device 1 and the plurality of service providing servers 10-1 to 10-n are configured to be owned by, for example, one business operator. That is, one business operator can provide a plurality of services Y. Further, one business operator collects the characteristic information generated by each service Y as shared information in the information processing device 1 and acquires and uses the provided information based on the shared information.

The information processing device 1 and the plurality of service providing servers 10-1 to 10-n may be configured to be owned by different companies. That is, the other service Y viewed from a certain service Y of a certain business operator may be the other service Y of the same business operator or the service Y of another business operator. Further, the plurality of service providing servers 10-1 to 10-n may be configured to be owned by different businesses. Further, in addition to the information processing system S described above, a server of a company that only uses the provided information may be connected.

2 illustrates the case where the information processing device 1 is configured separately from the service providing server 10 and has a function of generating and providing shared information, for example, one of the service providing servers 10 Some or all of the functions of the information processing device 1 may be replaced and performed.

Further, although FIG. 2 shows the case where the information processing device 1 has both functions of generating and providing shared information, for example, even if a plurality of information processing devices 1 share the above-mentioned functions. Good.

Next, the configuration of the information processing device 1 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a configuration example of the information processing device 1 according to the embodiment.

As shown in FIG. 3, the information processing device 1 includes a communication unit 2, a control unit 3, and a storage unit 4. The control unit 3 includes an acquisition unit 31, a determination unit 32, an update unit 33, a reception unit 34, an extraction unit 35, an estimation unit 36, and a provision unit 37.

The communication unit 2 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 2 is connected to the network N by wire or wirelessly, and transmits and receives information to and from at least the service providing server 10 via the network N.

The storage unit 4 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. As shown in FIG. 2, the storage unit 4 stores shared information 41, service information 42, and model program information 43.

The shared information 41 is information including the characteristic information acquired from the service providing server 10. FIG. 4 is a diagram showing an example of the shared information 41. As shown in FIG. 4, the shared information 41 is, for example, a table in which the column item is “UID” and the row item is “feature information”. In addition, a score, which is an output of the model in the characteristic information, is input to the data item of each set of the column item and the row item.

“UID” is identification information for identifying the user U. The “feature information” is information on a model and a score generated by each service providing server 10. In FIG. 4, a model name is input to each item of “feature information” (for example, “like fishing”).

As shown in FIG. 4, the shared information 41 is information including the scores of “UID” and “feature information”. In the example illustrated in FIG. 4, the user whose UID is “U1” indicates that the score of the model “like fishing” in the characteristic information is “2.3”.

A user whose UID is "U2" has a score of "not input" for the model "like fishing" in the characteristic information. This indicates that the score of the model “like fishing” in the characteristic information of the user “U2” has not been acquired from the service providing server 10.

For example, as the score, the score calculated by the service providing server 10 may be input as it is as the score of the shared information 41, or a score obtained by normalizing the score calculated by the service providing server 10 according to a predetermined standard may be used. You may input as shared information 41.

Further, in FIG. 4, the shared information 41 is shown as a score, but the shared information 41 is not limited to the score, and is divided into stages such as “○, Δ and ×” and “excellent, good and acceptable”. It may be the information provided.

Next, the service information 42 is information regarding the service Y provided by each service providing server 10. FIG. 5 is a diagram showing an example of the service information 42. As shown in FIG. 5, the service information 42 includes items such as “service ID”, “provided service”, and “number of registered models”.

The "service ID" is identification information that identifies the service Y (or the service providing server 10). The “provided service” is information indicating the content of the service Y. The “number of registered models” is information indicating the number of models of the characteristic information registered in the shared information 41.

Next, the model program information 43 is information including model program data in the feature information. FIG. 6 is a diagram showing an example of the model program information 43. The model program information 43 is information including model program data in the characteristic information acquired by the acquisition unit 31 described later. As shown in FIG. 6, the model program information 43 includes items such as “model ID”, “model name”, “service ID”, and “model data”.

The “model ID” is identification information that identifies the model in the characteristic information. The “model name” is identification information indicating the name of the characteristic information. The "service ID" is identification information that identifies the service Y (or the service providing server 10). The “model data” is model program data in the feature information.

The “model data” is, for example, a regression model in which the attribute of the user U is an explanatory variable. For example, “model data” is a regression model shown in the following formula. That is, it can be represented as a regression model of y=ω1·x1+ω2·x2+... +ωn·xn.

In the above formula, “x” is an explanatory variable corresponding to the attribute of the user U. “Y” is an objective variable corresponding to the score indicating the characteristics of the user U. Further, “ω” is a coefficient of “x” and indicates a predetermined weight value. Specifically, “ω1” is a weight value of “x1”, “ω2” is a weight value of “x2”, and “ωn” is a weight value of “xn”. As described above, the above formula is created by combining the explanatory variable “x” corresponding to the attribute of the user U and the variable including the predetermined weight value “ω” (for example, “ω1·x1 _” ). ..

The “model data” may be feature information generated using SVM (Support Vector Machine) or other machine learning method. Further, the characteristic information may be generated using a deep learning technique. For example, the service Y can generate feature information by appropriately using various deep learning techniques such as DNN (Deep Neural Network), RNN (Recurrent Neural Network), and CNN (Convolutional Neural Network).

The control unit 3 is a controller, and various programs stored in a storage device inside the information processing device 1 include a RAM as a work area, for example, by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. It is realized by being executed as. The control unit 3 is, for example, a controller, and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

The acquisition unit 31, the determination unit 32, the update unit 33, the reception unit 34, the extraction unit 35, the estimation unit 36, and the provision unit 37 are partially or wholly ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate). Array) or the like.

The control unit 3 registers the characteristic information acquired from the service providing server 10 and updates the model or estimation result of the registered characteristic information. Moreover, the control unit 3 provides various services Y based on the registered characteristic information.

The acquisition unit 31 uses different models of feature information including at least one of a model for estimating the characteristics of the user U using the attributes of the user U and an estimation result regarding the characteristics of the user U estimated using the attributes of the user U. Obtain from each Y. For example, the acquisition unit 31 acquires the characteristic information generated by the service Y in a format designated in advance. As a result, the format of the characteristic information can be made uniform among the services Y, so that the characteristic information having a unified standard can be acquired.

In addition, the acquisition unit 31 acquires, as the characteristic information, information including the above model and the initial value of the score output from the model. The initial value of the score may be calculated in advance by the service providing server 10, or may be calculated by the acquisition unit 31 acquiring the model data. When the acquisition unit 31 calculates the initial value, only the model data of the characteristic information is first acquired, and then the attribute of the user U is acquired from the service providing server 10 to calculate the score.

It should be noted that the acquisition unit 31 may have a check function of checking, when the characteristic information is acquired, whether or not the characteristic information is generated according to the specified format.

In addition, the acquisition unit 31 may acquire the attribute of the user U, which is the input of the model in the characteristic information, from the service Y different from the service Y from which the model is acquired. That is, the attribute of the user U may be acquired from the service Y of the acquisition source of the model registered as the shared information 41 and the score may be output, or the user U acquired from the service Y different from the service Y of the acquisition source. The score may be output using the attribute of. Thereby, for example, the models registered in the shared information 41 can be shared between the services Y of different businesses.

The determination unit 32 determines the priority order regarding updating for each model of feature information. The priority order determined by the determination unit 32 serves as a reference for the score update order performed by the update unit 33, which will be described later. The determination unit 32 determines the priority order based on, for example, current affairs information regarding current affairs.

The current affairs information is information such as news and information on social events. For example, the determination unit 32 extracts a specific keyword (for example, a news keyword) from the event that has occurred, and increases the priority of the characteristic information related to the keyword.

Note that the characteristic information related to a specific keyword is, for example, characteristic information including a specific keyword used in the news of the event, characteristic information related to the event, or similar to the genre of the event (keyword). It is the characteristic information and the like.

Further, the determining unit 32 determines the priority order based on, for example, the usage time of the characteristic information. The use time of the characteristic information is the time when the service Y performs the service activity using the characteristic information. For example, when the service Y uses the characteristic information to perform the service activity every Monday, the determination unit 32 increases the priority so that the characteristic information is surely updated on Sunday. Thereby, the service Y can perform the service activity based on the latest characteristic information.

The update unit 33 updates at least one of the model and the estimation result of the characteristic information acquired by the acquisition unit 31. For example, the updating unit 33 acquires the estimation result updated over time on the service Y side, and updates the estimation result of the feature information based on the acquired estimation result. As a result, even if the attribute of the user U changes daily, it is possible to always update the latest estimation result. The update unit 33 may acquire the attribute of the user U from the acquisition unit 31 over time and update the estimation result based on the acquired attribute. Further, for example, the update unit 33 acquires the attribute of the user U from the service Y over time, and updates the model of the characteristic information based on the acquired attribute of the user U. Here, updating of the model will be described with reference to FIG. 7.

FIG. 7 is a diagram showing an updating process by the updating unit 33. The upper part of FIG. 7 shows the process up to the initial registration of the model (the process at the first time), and the lower part of FIG. 7 shows the registered model process (the second and subsequent processes). As shown in the upper part of FIG. 7, first, the service providing server 10 acquires the attribute of the user U who has used the service Y (step S10).

Subsequently, the service providing server 10 generates a model by analyzing the acquired user attribute, and calculates the initial value of the score based on the model (step S11). Subsequently, the service providing server 10 outputs the characteristic information including the generated model data and the initial value of the score to the information processing device 1 (step S12).

The acquisition unit 31 of the information processing device 1 registers the acquired model data of the characteristic information in the model program information 43, and also registers the initial value of the score in the shared information 41 (step S13). This completes the processing of the characteristic information at the first time.

Next, when the processing of the characteristic information at the first time is completed, the information processing device 1 performs processing of updating the registered model data. As shown in the lower part of FIG. 7, first, the service providing server 10 acquires the attribute of the user U with time (step S20).

Subsequently, the service providing server 10 transmits the attributes of the user U acquired over time to the information processing device 1 (step S21). Subsequently, the updating unit 33 of the information processing device 1 updates the model data registered based on the acquired attributes of the user U (step S22). Specifically, the update unit 33 updates the objective variable, the explanatory variable, and the weight in the regression model using the acquired attributes of the user U.

That is, the updating unit 33 registers the model data of the characteristic information when the score is registered for the first time, and thereafter performs the model data updating process on behalf of the service providing server 10. As a result, even if the attribute of the user U changes daily, it is possible to always update to the latest model. The updating unit 33 is not limited to acquiring the attribute of the user U and updating the model data, but may acquire the model data updated over time by the service Y and perform the model data updating process. .

In addition, the timing of the updating process of the model data by the updating unit 33 may be arbitrary. For example, the update unit 33 may periodically acquire the attribute of the user U from the service providing server 10 and update the model. Alternatively, the update unit 33 may update the model when there is an update request from the service providing server 10.

The model update by the update unit 33 is performed based on the priority order determined by the determination unit 32, for example. That is, the update unit 33 updates the model in the update order based on the priority order determined by the determination unit 32.

Although the service providing server 10 calculates the initial value of the score in the upper part of FIG. 7, the information processing device 1 may calculate the initial value of the score, for example. In such a case, the service providing server 10 registers only the model data of the feature information in the information processing device 1 in advance, and then transmits the attribute of the user U to the information processing device 1.

Returning to FIG. 3, the receiving unit 34 will be described. The reception unit 34 receives various requests from the service providing server 10. For example, the reception unit 34 receives from the service Y a request for specifying a characteristic that specifies a specific characteristic. In the feature designation, the model ID, model name, etc. of the feature information included in the shared information 41 are designated. The designation by the feature designation may be one feature information or a plurality of feature information. Alternatively, the feature designation may be a designation including a plurality of feature information such as a field designation.

Further, the reception unit 34 receives a user designation request for designating a specific user U from the service Y. The user U designated by the user designation may be one or plural. Alternatively, the user designation may be a group designation including a plurality of users. In the case of group designation, the name of a particular group is designated by user designation.

Further, the reception unit 34 may include a period designation in the above request. For example, in the case of feature designation, the feature information registered in the period designated by the period designation may be the target of feature designation. In the case of user designation, the user U who used the service Y during the period designated by the period designation may be the user designated target.

The extraction unit 35 extracts the user U corresponding to the specific feature designated by the feature designation based on the feature information. For example, the extraction unit 35 extracts the user U whose score of the specified characteristic is equal to or more than a predetermined value.

The estimation unit 36 estimates the characteristic of the specific user U designated by the user designation based on the characteristic information. For example, the estimation unit 36 estimates that among the pieces of characteristic information of the designated user U, the characteristic information having a score of a predetermined value or more is the characteristic of the user U.

Note that the estimation unit 36, even if it is estimated that the user U does not have the feature of the feature information when the feature information of which the score is less than the predetermined value is included in the feature information of the designated user U. Good. That is, the estimation unit 36 estimates that the user U has the characteristic of "I like XX" when the score is equal to or higher than the predetermined value, and the user U "I dislike XX" when the score is less than the predetermined value. Presumed to have the characteristics of.

The providing unit 37 provides the provided information based on the characteristic information registered by the acquisition unit 31 to the other service Y. For example, the providing unit 37 provides the provided information based on the score to the other service Y. The providing unit 37 also generates the provision information based on the information acquired from the extraction unit 35 or the estimation unit 36, and provides the provision information to the service Y.

For example, the providing unit 37 generates the provision information including the list (one example of the list) of the user U extracted by the extraction unit 35 based on the feature specification and provides the provision information to the service Y. The list may be sorted in any order such as score order, user name (including user ID, etc.) alphabetical order, or alphabetical order.

Alternatively, the providing unit 37 may provide only a part of the users U among the users U extracted by the extracting unit 35 to the service Y as the providing information. Specifically, the providing unit 37 may provide the provision information in which only the user U having the highest score or the users U having the highest scores or the like are selected.

The providing unit 37 also provides the other service Y with the provision information including the information indicating the characteristics of the user U estimated by the estimation unit 36 based on the user designation. For example, the providing unit 37 provides the providing information including information in which the characteristics of the user U estimated by the estimating unit 36 are arranged in a list.

Further, the providing unit 37 may provide the providing information including only some of the features of the user U estimated by the estimating unit 36. For example, the providing unit 37 may provide the provided information in which only the features whose score is the highest-ranked feature information or only the features whose scores are the highest-ranked feature information are selected.

Next, a procedure of processing executed by the information processing device 1 according to the embodiment will be described with reference to FIG. FIG. 8 is a flowchart showing a procedure of processing executed by the information processing device 1 according to the embodiment.

As shown in FIG. 8, first, the acquisition unit 31 calculates the model for estimating the characteristics of the user U by using the attributes of the user U, and the estimation result regarding the characteristics of the user U estimated by using the attributes of the user U. Characteristic information including at least one is acquired (step S101).

Subsequently, the determining unit 32 determines the priority order for updating for each feature information (step S102). Subsequently, the updating unit 33 determines whether or not it is the update timing of the characteristic information (step S103). The update timing is determined, for example, based on the priority order determined by the determining unit 32.

If the update timing has come (Yes in step S103), the update unit 33 acquires the attribute of the user U from the service Y (step S104). The updating unit 33 may acquire the model data and the estimation result updated on the service side in step S104. Subsequently, the updating unit 33 updates the characteristic information based on the acquired attribute of the user U (step S105), and ends the process.

On the other hand, when it is not the update timing (No in step S103), the update unit 33 repeatedly executes step S103 until the update timing arrives.

Next, the procedure of the providing process executed by the information processing device 1 according to the embodiment will be described with reference to FIG. 9. FIG. 9 is a flowchart showing the procedure of the providing process executed by the information processing device 1 according to the embodiment.

As shown in FIG. 9, in the providing process, the accepting unit 34 first determines whether or not a feature specification request has been accepted from the service Y (step S201). When the accepting unit 34 accepts the feature designation (Yes in step S201), the extracting unit 35 extracts the user U having the particular feature designated by the feature designation (step S202).

Subsequently, the providing unit 37 provides the providing information including the list of the user U extracted by the extracting unit 35 to the service Y (step S203), and ends the process.

On the other hand, when the reception unit 34 does not receive the feature specification request (No in step S201), the reception unit 34 determines whether the user specification request has been received (step S204). The order of the processes of steps S201 and S204 may be exchanged.

When the accepting unit 34 accepts the request designated by the user (Yes in step S204), the estimation unit 36 estimates the characteristics of the user U designated by the user designation (step S205).

Subsequently, the providing unit 37 provides the service Y with the provision information including the information indicating the characteristics of the user U estimated by the estimation unit 36 (step S206), and ends the process.

On the other hand, when the accepting unit 34 does not accept the request designated by the user (step S204, No), the process proceeds to step S201.

Further, the information processing apparatus 1 according to the above-described embodiment is realized by, for example, a computer 1000 having a configuration shown in FIG. FIG. 10 is a hardware configuration diagram illustrating an example of a computer 1000 that realizes the functions of the information processing device 1 according to the embodiment. 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.

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

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

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 device via the input/output interface 1600. The CPU 1100 also outputs the generated data to the output device via the input/output interface 1600.

The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the program or data to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Etc.

For example, when the computer 1000 functions as the information processing device 1 according to the embodiment, the CPU 1100 of the computer 1000 realizes the function of the control unit 3 by executing the program loaded on the RAM 1200. Further, the HDD 1400 stores the data in the storage unit 4. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from another device via the network N.

As described above, the information processing device 1 according to the embodiment includes the acquisition unit 31 and the provision unit 37. The acquisition unit 31 uses different models of feature information including at least one of a model for estimating the characteristics of the user U using the attributes of the user U and an estimation result regarding the characteristics of the user U estimated using the attributes of the user U. Obtain from each Y. The providing unit 37 provides the provided information based on the characteristic information acquired by the acquisition unit 31 to the other service Y.

As a result, the analysis result of another service Y can be acquired without being aware of the gap between the services Y.

Further, in the information processing device 1 according to the above-described embodiment, the model of the characteristic information is that the characteristic of the user is output as a score by inputting the attribute of the user U. The providing unit 37 provides the provided information based on the score to the other service Y.

As a result, since the characteristics of the user U are scored, the characteristics of the standard that are unified among the other services Y can be shared, so that the analysis results of the other services Y can be used more effectively.

Further, in the information processing device 1 according to the above-described embodiment, the acquisition unit 31 acquires the attribute of the user U, which is the input of the model, from the service Y different from the service Y from which the model is acquired.

Thereby, for example, the models registered in the shared information 41 can be shared between the services Y of different businesses.

The information processing device 1 according to the above-described embodiment further includes the updating unit 33. The update unit 33 updates at least one of the model and the estimation result of the characteristic information acquired by the acquisition unit 31.

Thereby, even when the attribute of the user U changes with time, it is possible to always update the latest model and estimation result.

Further, the updating unit 33 according to the above-described embodiment acquires the attribute of the user U from the service Y over time, and updates the estimation result of the characteristic information based on the acquired attribute.

As a result, even if the attribute of the user U changes with time, the latest estimation result can always be updated.

Further, the updating unit 33 according to the above-described embodiment acquires the attribute of the user U from the service Y over time, and updates the model of the feature information based on the acquired attribute.

As a result, even when the attribute of the user U changes with time, it is possible to always update the latest model data.

Further, the updating unit 33 according to the above-described embodiment acquires the estimation result updated over time on the service Y side, and updates the estimation result of the feature information based on the acquired estimation result.

As a result, even if the attribute of the user U changes with time, the latest estimation result can always be updated.

In addition, the updating unit 33 according to the above-described embodiment acquires the model data updated over time on the service Y side, and updates the model data of the feature information based on the acquired model data.

As a result, even when the attribute of the user U changes with time, it is possible to always update the latest model data.

In addition, the information processing device 1 according to the above-described embodiment further includes the determination unit 32. The deciding unit 32 decides the priority order regarding updating for each feature information. The update unit 33 updates the feature information in the update order based on the priority order determined by the determination unit 32.

This allows, for example, a huge number of feature information updates to be prioritized, so that other services Y can use old feature information by updating in the order of high possibility of being used by another service Y. The sex can be lowered.

Further, in the information processing device 1 according to the above-described embodiment, the determination unit 32 determines the priority order based on the current affairs information regarding the current affairs.

As a result, the feature information can be updated in an update order according to the events in the world, that is, in an order in which the other services Y are likely to be used.

Further, in the information processing device 1 according to the above-described embodiment, the attribute of the user U includes action information regarding the action when the service Y of the user U is used.

Accordingly, the behavior of the user U in the service Y can be reflected in the characteristic information, so that the characteristic information with higher accuracy can be registered.

Further, the information processing device 1 according to the above-described embodiment includes the reception unit 34 and the extraction unit 35. The accepting unit 34 accepts a feature specification designating a particular feature from the service Y. The extraction unit 35 extracts the user U corresponding to the specific feature designated by the feature designation based on the feature information. The providing unit 37 provides the service Y with the providing information including the list of the users U extracted by the extracting unit 35.

As a result, for example, the user U having a specific feature that is not generated by the service Y of his/her own can be known, so that the quality of the service Y provided can be improved.

Further, the information processing device 1 according to the above-described embodiment includes the accepting unit 34 and the estimating unit 36. The reception unit 34 receives a user designation for designating a specific user U from the service Y. The estimation unit 36 estimates the characteristic of the specific user U designated by the user designation based on the characteristic information. The providing unit 37 provides the service Y with the providing information including the information indicating the characteristics estimated by the estimating unit 36.

As a result, the characteristics of the user U that cannot be generated by the service Y of the particular user U can be known, so that a higher quality service Y can be provided to the particular user U.

In addition, in the above-described embodiment, the information processing apparatus 1 may generate new feature information regarding the feature information included in the shared information 41, for example, by combining a plurality of feature information. Specifically, new feature information of “I like XX, I like XX” may be generated by adding the feature information of “I like XX” and the feature information of “I like XX”. Alternatively, new feature information “I like XX but dislike XX” may be generated by removing the feature information of “I like XX” from the feature information of “I like XX”. The generation timing of such new feature information may be generated by combining a plurality of feature designations accepted by the acceptance unit 34, or is related to the current event or event when the current event or event occurs. It may be generated by combining a plurality of feature information.

As described above, some of the embodiments of the present application have been described in detail based on the drawings, but these are examples, and various modifications based on the knowledge of those skilled in the art, including the modes described in the section of the disclosure of the invention, It is possible to implement the present invention in other forms with improvements.

Further, of the processes described in the above embodiment, all or part of the processes described as being automatically performed may be manually performed, or the processes described as being manually performed may be performed. All or part of the process can be automatically performed by a known method. In addition, the processing procedures, specific names, information including various data and parameters shown in the above-mentioned documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various kinds of information shown in each drawing are not limited to the illustrated information.

Further, each constituent element of each illustrated device is functionally conceptual, and does not necessarily have to be physically configured as illustrated. That is, the specific form of distribution/integration of each device is not limited to that shown in the figure, and all or a part of the device may be functionally or physically distributed/arranged in arbitrary units according to various loads or usage conditions. It can be integrated and configured.

Further, the respective processes described in the above-described embodiments can be appropriately combined within a range in which the processing contents do not contradict each other.

Also, the above-mentioned "section (module, unit)" can be read as "means" or "circuit". For example, the acquisition unit 31 can be read as a registration unit or a registration circuit.

DESCRIPTION OF SYMBOLS 1 Information processing device 2 Communication part 3 Control part 4 Storage part 10 Service providing server 31 Acquisition part 32 Determination part 33 Update part 34 Reception part 35 Extraction part 36 Estimating part 37 Providing part 41 Shared information 42 Service information 43 Model program information 100 User Terminal S information processing system

Claims (15)

A model that estimates the characteristics of the user using the attributes of the user, and an acquisition unit that acquires characteristic information including at least one of estimation results regarding the characteristics estimated using the attributes from different services,
An information processing apparatus, comprising: a providing unit that provides the additional information based on the characteristic information acquired by the acquisition unit to the other service. The model of the feature information is
By inputting the attributes of the user, the characteristics of the user are output as a score,
The providing unit is
The information processing apparatus according to claim 1, wherein the provided information based on the score is provided to the other service. The acquisition unit is
The information processing apparatus according to claim 1, wherein the attribute of the user that is an input of the model is acquired from a service different from the service from which the model is acquired. The information processing apparatus according to claim 1, further comprising an update unit that updates at least one of the model and the estimation result of the characteristic information acquired by the acquisition unit. The update unit is
The information processing apparatus according to claim 4, wherein the attribute of the user is acquired over time from the service, and the estimation result of the characteristic information is updated based on the acquired attribute. The update unit is
The information processing apparatus according to claim 4, wherein the attribute of the user is acquired over time from the service, and the model of the characteristic information is updated based on the acquired attribute. The update unit is
7. The estimation result updated over time on the service side is acquired, and the estimation result of the characteristic information is updated based on the acquired estimation result. The information processing device described in 1. The update unit is
The model updated in the service side over time is acquired, and the model of the feature information is updated based on the acquired model concerned. Information processing device. Further comprising a deciding unit for deciding a priority order for updating for each of the characteristic information,
The update unit is
The information processing apparatus according to any one of claims 4 to 8, wherein the feature information is updated in an update order based on the priority order determined by the determination unit. The determination unit is
The information processing apparatus according to claim 9, wherein the priority order is determined based on current affairs information regarding current affairs. The attributes of the user are
The information processing apparatus according to any one of claims 1 to 10, comprising behavior information regarding behavior of the user when using the service. A reception unit that receives a characteristic specification for specifying the specific characteristic from the service,
An extraction unit that extracts the user corresponding to the specific feature designated by the feature designation based on the feature information,
The providing unit is
The information processing apparatus according to claim 1, wherein the provided information including the list of the users extracted by the extraction unit is provided to the service. A reception unit that receives a user designation for designating the specific user from the service,
An estimation unit that estimates the characteristic of the specific user designated by the user designation based on the characteristic information,
The providing unit is
The information processing apparatus according to claim 1, wherein the provision information including the information indicating the characteristic estimated by the estimation unit is provided to the service. An information processing method executed by a computer,
A model for estimating the feature of the user using the attribute of the user, and an obtaining step of obtaining feature information including at least one of estimation results regarding the feature estimated using the attribute from different services,
And a providing step of providing the provided information based on the characteristic information acquired by the acquiring step to the other service. A model for estimating the characteristics of the user by using the attributes of the user, and an acquisition procedure for acquiring characteristic information including at least one of estimation results regarding the characteristics estimated by using the attributes from different services,
An information processing program, characterized by causing a computer to execute a providing procedure of providing providing information based on the characteristic information acquired by the acquisition procedure to another service.

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