JP7422113B2 - Information processing device, 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.

In recent years, with the rapid spread of the Internet, information distribution via the Internet has become popular. As an example of such information distribution, a technique is known in which a community on the Internet is proposed to a user according to the user's hobbies, etc., and interaction between users in the community is realized.

Japanese Patent Application Publication No. 2001-249877

However, the above-mentioned conventional techniques may not be able to enable users to obtain useful information.

For example, in the above-mentioned conventional technology, a community to which a plurality of users who have common hobbies belong is proposed to a certain user. However, even if you have common hobbies, once you get used to them, you may forget (or take for granted) the things you didn't understand when you started from scratch. Therefore, with the above-mentioned conventional technology, a user who starts from scratch may not be able to obtain useful information from the other party with whom he or she interacts, and may become frustrated.

This application has been made in view of the above, and aims to enable users to obtain useful information.

The information processing device according to the present application includes an estimating unit that estimates the skill level of the user regarding a predetermined object based on the user's action history, and a predetermined utilization and a determining unit that determines the other party with whom information is to be transmitted and received.

According to one aspect of the embodiment, it is possible to enable a user to obtain useful information.

FIG. 1 is a diagram showing an overview of information processing according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information providing apparatus according to an embodiment. FIG. 3 is a diagram showing an example of a user information database. FIG. 4 is a diagram showing an example of a history information database. FIG. 5 is a diagram showing an example of the hardware configuration.

DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. In addition, in the following embodiments, the same parts are given the same reference numerals, and redundant explanations will be omitted.

[1. Example of information providing device]
First, an example of a determination process executed by an information providing apparatus, which is an example of an information processing apparatus, will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of a determination process executed by an information providing apparatus according to an embodiment.

In the example shown in FIG. 1, as an example of a process executed by the information providing apparatus 10, when a request for distribution of information posted by users U02 to U05 is received from user U01, a determination process is executed. An example of an information providing process for determining another user who will send and receive information to and from user U01 and distributing information on the determined other user to user U01 has been described. Here, the embodiment is not limited to such a form, and the information providing apparatus 10 executes a determination process to be described later when exchanging messages between users, thereby determining a predetermined value. Other users who exchange information with the user may also be determined.

An example of the information providing device 10 shown in FIG. 1 will be described below. The information providing device 10 is a terminal device used by users U01 to U05 (hereinafter may be collectively referred to as "users U") via a predetermined network N such as the Internet (see FIG. 2, for example). 101 to 105 (hereinafter may be collectively referred to as "terminal devices 100"), and is realized by, for example, a server device, a cloud system, or the like. Note that the information providing device 10 may be able to communicate with any number of terminal devices 100 used by any number of users via the network N. Further, the information providing device 10 may be able to communicate with various external servers (not shown).

The terminal device 100 is a smart device such as a smartphone or a tablet used by the user U, and can communicate with any server device via a wireless communication network such as 3G (3rd Generation) or LTE (Long Term Evolution). This is a mobile terminal device that can Note that the terminal device 100 may be not only a smart device but also an information processing device such as a desktop PC or a notebook PC.

[2. Regarding an example of information provision processing]
Next, an example of the flow of the information providing process executed by the information providing device 10 will be described. For example, the information providing device 10 provides the user U with a service called SNS (Social Networking Service). For example, the information providing device 10 receives information including various types of content such as text, still images, moving images, audio, etc. from the user U as posted information. In such a case, the information providing device 10 retains the received posted information.

On the other hand, when the information providing device 10 receives a request for distribution of posted information from the user U, the information providing device 10 posts information posted by other users U who have a connection with the requesting user U on SNS among the posted information held. Extract posted information. More specifically, the information providing device 10 extracts posted information posted by another user who has skills related to the same subject (eg, programming, investment, etc.) as the requesting user U. For example, the information providing device 10 extracts posted information posted by other users who have skills related to the same subject as user U, based on the information of each user registered in advance. The information providing device 10 then distributes the extracted posted information to the user U who made the request.

As a result, the information providing device 10 can provide posted information posted by another user who has the same skill related to the same subject as the requesting user U. Therefore, the information providing device 10 can distribute information that is likely to be useful to the requesting user.

Here, a user who has skills regarding a predetermined object can be rephrased as a user who has an interest in the predetermined object. For example, if the predetermined subject is programming, it is estimated that a user who has only had an interest in programming for a short time (for example, one week) has little knowledge about programming. As described above, it is assumed that a user who has recently become interested in programming has little knowledge about programming, and therefore has a low skill level regarding programming. On the other hand, users who have been interested in programming for a long time (for example, 10 years) are estimated to have more knowledge about programming than users who have only recently been interested in programming. be done. As described above, a user who has been interested in programming for a long time has a wealth of knowledge regarding programming, and is therefore presumed to have a high skill level regarding programming. In this way, a user who has skills related to a predetermined subject can be said to be a user who has an interest in the predetermined subject.

In the present embodiment, the information providing device 10 acquires in advance target information indicating the object of interest (hereinafter also referred to as target) of each user, and uses the acquired target information and a user ID that allows each user to be identified. It is assumed that these are stored in advance in the user information database 31 (see FIG. 2) in association with each other. Furthermore, the information providing device 10 estimates that each user has a skill related to the object indicated by the object information associated with each user ID. For example, the information providing device 10 refers to the user information database 31 and estimates that the user U has programming skills when the target information associated with the user U is programming. Similarly, the information providing device 10 refers to the user information database 31 and estimates that the other user has programming skills when the target information associated with the other user is programming. That is, the information providing device 10 refers to the user information database 31 and identifies other users who are associated with the same target information as the target information associated with the user U, regarding the same target as the user U. Identify other skilled users.

Note that the information providing device 10 acquires target information indicating the target of the skill possessed by each user from the user through self-reporting by the user, and associates the acquired target information with a user ID that can identify each user. It may also be stored in the user information database 31 in advance.

[3. Regarding the conventional exchange of information between users]
Here, the information providing device 10 can exchange information between the users U through the information providing process described above. For example, the information providing device 10 distributes posted information regarding various questions posted by user U01 to user U02, and transmits posted information posted by user U02 as a response to the posted information posted by user U01. By distributing the information to the user U01, it is possible to exchange information between the user U01 and the user U02.

However, with the conventional technology, there have been cases where it has not been possible to enable users to obtain useful information. For example, in the conventional technology, the user U01 is provided with posts from other users who have skills related to the same subject as the user U01. However, even if users have skills related to the same subject, if there is a difference in skill level between users, it may not be possible to exchange useful information between users.

For example, assume that there are users U01 to U05 whose skill is "programming." In such a case, it is considered that the users U01 to U05 can have a dialogue regarding "programming", which is a common skill. For example, if user U01 is a beginner who does not have much knowledge about programming, and user U02 is an intermediate person who has some knowledge about programming, user U02 may respond to user U01's questions with empathy and knowledge. It is conceivable that the response would be to teach the teacher, etc.

However, for example, if user U01 is a beginner and user U05 is an advanced user, user U05 may post a response criticizing user U01 from above in response to user U01's question. There is a risk that it will happen. More specifically, since the content of user U01's question is a matter of course for user U05, there is a risk that user U05 may post something criticizing user U01 such as, "Find it yourself!". Furthermore, there is a risk that user U01 will post a critical post in response to such a post by user U05.

For example, if user U01 is an early user who has just started learning about programming, and user U02 is a user who has been learning about programming for about a year, There is a high possibility that the user U02 will respond with an accurate answer or advice to the user U01's question. However, if user U05 is a user who has been learning about programming for about 5 years, he may forget things he didn't understand when he first started learning about programming, and it may not be accurate. There is a risk of responding.

Furthermore, in addition to the programming example described above, for example, if there is a disparity in skill level regarding a subject, there is a risk that the exchange of useful information between users will be hindered. For example, if there are disparities in skill levels regarding subjects such as various learning activities and work abilities, there is a risk that the exchange of useful information between users will be inhibited.

[4. About the decision process]
In this way, even if the users U have skills related to the same subject, if there is a difference in skill level between the users U, it may not be possible to exchange useful information between the users U. Therefore, the information providing device 10 estimates the skill level of the user regarding a predetermined object based on the user's behavior history. Then, if the difference between the skill level estimated for a predetermined user and the skill level estimated for another user different from the predetermined user falls within a predetermined range, the information providing device 10 A user is determined as a party to whom information is to be sent and received with a predetermined user.

Thereby, the information providing device 10 can control the users such that the difference in skill level falls within an appropriate range to exchange information. That is, the information providing device 10 can allow the user to obtain useful information.

On the other hand, if the difference between the skill level estimated for a predetermined user and the skill level estimated for another user different from the predetermined user does not fall within a predetermined range, the information providing device 10 Exclude users from those who exchange information with the specified users.

Thereby, the information providing device 10 can control, for example, so that users with large differences in skill level do not exchange information with each other. That is, in the information providing device 10, for example, a user starting from scratch (a user with a low skill level) cannot obtain useful information because he/she exchanges information with a person with a high skill level, and as a result, becomes frustrated. can be prevented from occurring.

[5. Regarding an example of decision processing and information provision processing]
Returning to the description of FIG. 1, an example of the flow of the determination process and information provision process executed by the information providing apparatus 10 will be described. In the example shown in FIG. 1, it is assumed that the users U01 to U04 are users who have programming skills. Further, in the example shown in FIG. 1, posted information is provided when the difference in skill level between users is "4" or less.

For example, the information providing device 10 receives posted information including various contents such as questions, responses, complaints, and diaries from users U01 to U05 (steps S1 to S5). In such a case, the information providing device 10 retains the received posted information. The information providing device 10 also receives a request from the user U01 to request distribution of posted information (step S6). In such a case, the information providing device 10 estimates the skill level of the user U01 regarding programming based on the behavior history of the user U01 (step S7). Furthermore, the information providing device 10 estimates the skill level of each of the other users U02 to U05 based on the action history of each of the other users U02 to U05 (step S8). Then, the information providing device 10 selects, among the users U01 to U05, users whose skills are the same as those of the user U01 and whose skill level difference falls within a predetermined range, for sending and receiving information with the user U01. Determine as other users who do. Subsequently, the information providing device 10 selects posted information posted by another user who is determined to be the party with whom information is transmitted and received from the user U01 (step S9).

For example, as shown in (A) in FIG. 1, the information providing device 10 specifies the skill levels of the users U01 to U05 and the targets of the skills of the users U01 to U05. For example, in the example shown in (A) in FIG. 1, the information providing device 10 specifies the skill level "level 5" and the target "programming" of the user U01, and specifies the skill level "level 4" of the user U02 and the target "programming". "Programming" is specified, the skill level of user U03 is "level 10", the target "programming" is specified, the skill level of user U04 is "level 6", the target "programming" is specified, and the skill level of user U05 is Specify the level "Level 4" and the target "Investment".

In such a case, the information providing device 10 may post information posted by users U02 to U04 who have skills related to the same target "programming" as user U01, and if the difference from the skill level of user U01 is within a predetermined level. Select posted information posted by users within the range. For example, in the example shown in FIG. 1, the difference between the skill level "Level 5" of the user U01 and the skill level "Level 4" of the user U02 is less than or equal to the predetermined threshold "4". Furthermore, even if the question of user U01 is provided to user U02 whose skill level is lower than that of user U01, there is a small possibility that an appropriate answer will be obtained, but if the question of user U02 is provided to user U01 , you are more likely to get an appropriate answer. Therefore, as shown in (B) in FIG. 1, the information providing device 10 provides question information related to the question from among the posted information posted by the user U02 as information to be provided to the user U01. Select as.

Further, for example, in the example shown in FIG. 1, the difference between the skill level "Level 5" of the user U01 and the skill level "Level 10" of the user U03 exceeds the predetermined threshold "4". In such a case, it is unlikely that user U03 will provide an appropriate answer to user U01's question. Therefore, as shown in (B) in FIG. 1, the information providing device 10 excludes the posted information posted by the user U03 from being provided to the user U01.

For example, in the example shown in FIG. 1, the difference between the skill level "Level 5" of the user U01 and the skill level "Level 6" of the user U04 is less than or equal to the predetermined threshold "4". Further, if the question of the user U01 is provided to the user U04, who has a higher skill level than the user U01, there is a high possibility that an appropriate answer will be obtained. Therefore, as shown in (B) in FIG. 1, the information providing device 10, as information provided to the user U01, responds to the question information posted by the user U01 among the posted information posted by the user U04. Select response information related to the response to be provided.

As a result, as shown in (C) in FIG. 1, the information providing device 10 displays the question information C11 posted by the user U01 in the past, the response information C12 of the user U04 to the question information C11, and the response information C12 posted by the user U02. Content in which question information C13 and the like are arranged is generated, and the generated content is distributed to the terminal device 101 of the user U01. That is, the information providing device 10 distributes information selected according to the difference in skill level of the users U01 to U04 to the user U01 (step S10). As a result, the information providing device 10 can provide an empathetic response or an appropriate response to the user U01's question, a question that the user U01 can respond to with empathy, and so on. can be used to obtain useful information. In addition, the information providing device 10 prevents the user U01 from being unable to obtain useful information due to exchanging information with a partner whose skill level is too high (for example, the user U03), and resulting in frustration. It can be prevented.

[6. Configuration example of information providing device]
FIG. 2 is a diagram showing a configuration example of the information providing device 10 according to the embodiment. As shown in FIG. 2, the information providing device 10 includes a communication section 20, a storage section 30, and a control section 40.

(Communication department 20)
The communication unit 20 is realized by, for example, a NIC (Network Interface Card). The communication unit 20 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the terminal device 100.

(Storage unit 30)
The storage unit 30 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 30 also stores a user information database 31 and a history information database 32.

(User information database 31)
The user information database 31 stores various information regarding the user U of the service provided by the information providing device 10. For example, the user information database 31 stores various information such as user U's attributes. FIG. 3 is a diagram showing an example of the user information database 31. In the example shown in FIG. 3, the user information database 31 includes information such as "user ID (Identifier)", "age", "gender", "home", "work location", "skill level", and "target". Has items.

“User ID” indicates identification information for identifying user U. Moreover, "age" indicates the age of the user U identified by the user ID. Note that the "age" may be a specific age of the user U identified by the user ID, such as 35 years old. Furthermore, “gender” indicates the gender of the user U identified by the user ID.

Moreover, "home" indicates the location information of the home of the user U identified by the user ID. In the example shown in FIG. 3, "home" is illustrated as an abstract code such as "LC11", but it may also be latitude and longitude information. Furthermore, for example, "home" may be a region name or address.

Moreover, "work place" indicates the location information of the work place (school in the case of a student) of the user U identified by the user ID. In the example shown in FIG. 3, the "work location" is illustrated as an abstract code such as "LC12," but it may also be latitude and longitude information. Further, for example, the "work location" may be a region name or address.

Moreover, "skill level" indicates the skill level that the user U identified by the user ID has regarding the object. For example, the larger the number in "Level 0", the higher the skill level.

Moreover, "object" indicates the object of interest and skill that the user U identified by the user ID has. For example, "object" indicates an object in which the user U identified by the user ID is highly interested. For example, the "target" may be a search query (keyword) entered by the user U into a search engine. In the example shown in FIG. 3, one "target" is shown for each user U, but there may be a plurality of "targets".

For example, in the example shown in FIG. 3, the age of the user U identified by the user ID "U1" is "20s", and the gender is "male". Further, for example, the user U identified by the user ID "U1" indicates that his home is "LC11". Further, for example, the user U identified by the user ID "U1" indicates that the work location is "LC12". Further, for example, the user U identified by the user ID "U1" indicates that he has interests and skills related to "programming." Further, the user U identified by the user ID "U1" indicates that the skill level regarding programming is "level 5".

Here, in the example shown in FIG. 3, abstract values such as "U1", "LC11", and "LC12" are used for illustration, but "U1", "LC11", and "LC12" have specific values. It is assumed that information such as character strings and numerical values is stored. Below, abstract values may be illustrated in diagrams related to other information as well.

Note that the user information database 31 is not limited to the above, and may store various information depending on the purpose. For example, the user information database 31 may store various information regarding the terminal device 100 of the user U. In addition, the user information database 31 contains information such as demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral attributes), etc. of the user U. Information regarding attributes may also be stored. For example, the user information database 31 includes name, family structure, place of birth (locality), occupation, position, income, qualifications, type of residence (single-family house, condominium, etc.), presence or absence of a car, commuting/commuting time, commuting/commuting. Memorizes information such as routes, commuter pass sections (stations, lines, etc.), frequently used stations (other than the stations closest to your home or work), lessons (location, time zone, etc.), hobbies, interests, lifestyle, etc. You can.

(History information database 32)
The history information database 32 stores various information regarding history information (log data) indicating the behavior of the user U. FIG. 4 is a diagram showing an example of the history information database 32. In the example shown in FIG. 4, the history information database 32 includes items such as "user ID,""searchhistory,""browsinghistory,""purchasehistory," and "posting history."

“User ID” indicates identification information for identifying user U. Further, “search history” indicates a search history that is a history of search queries input by the user U. In addition, “browsing history” indicates a browsing history that is a history of contents that the user U has viewed. Further, “purchase history” indicates a purchase history that is a history of purchases by user U. Moreover, "posting history" indicates a posting history that is a history of postings by user U. Note that the "posting history" may include questions regarding user U's belongings.

For example, in the example shown in FIG. 4, the user U identified by the user ID "U1" searches according to "search history #1", views content according to "browsing history #1", This indicates that a predetermined product or the like was purchased at a predetermined store or the like according to "Purchase History #1" and posted according to "Posting History #1".

Here, in the example shown in FIG. 4, abstract values such as "U1", "search history #1", "browsing history #1", "purchase history #1", and "posting history #1" are used for illustration. However, information such as specific character strings and numerical values is stored in "U1", "Search history #1", "Browsing history #1", "Purchase history #1" and "Posting history #1". shall be

Note that the history information database 32 is not limited to the above, and may store various information depending on the purpose. For example, the history information database 32 stores message information regarding the history of messages exchanged in the past by user U with other users in message services such as LINE (registered trademark).

Further, the history information database 32 may store the user U's visit history to a physical store, visit history to a facility, or the like. Further, the history information database 32 may store the payment history of user U's electronic payment.

Returning to FIG. 2, the explanation will be continued. The control unit 40 is a controller, and uses, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array) to control the information providing device 10. This is achieved by executing various programs (corresponding to an example of an information processing program) stored in an internal storage device using a storage area such as a RAM as a work area. In the example shown in FIG. 2, the control unit 40 includes an acquisition unit 41, a generation unit 42, an estimation unit 43, a reception unit 44, a determination unit 45, and a distribution unit 46.

(Acquisition unit 41)
The acquisition unit 41 acquires various information regarding the user U of the service provided by the information providing device 10 from the terminal device 100, various servers, and the like. For example, the acquisition unit 41 acquires user information regarding the user, such as information indicating the user (user ID, etc.), location information of the user, and attribute information of the user. The acquisition unit 41 then registers the acquired user information in the user information database 31.

The acquisition unit 41 also acquires the user U's behavior history. For example, the acquisition unit 41 collects the behavior history of the user U from various external servers, such as an external server that provides services related to web search and an external server that provides services related to electronic commerce, and records the collected behavior history. It is registered in the information database 32.

(Generation unit 42)
The generation unit 42 generates a machine learning model that estimates the skill level from the behavior history. Specifically, the generation unit 42 refers to the history information database 32 and obtains the behavior history of a known user whose skill level is known for a period from when he or she started learning about a predetermined subject to the present. For example, the generation unit 42 may specify the search date and time when the known user first searched for a search query related to the predetermined target as the time when the known user started learning about the predetermined target. In addition, the generation unit 42 generates, as examples of behavior history, a known user's search history, a known user's purchase history, a known user's browsing history, a known user's posting history, and a known user's message exchange. Get history. Subsequently, upon acquiring the behavior history of the known user, the generation unit 42 estimates each piece of information regarding a predetermined object acquired by the known user through each behavior related to the acquired behavior history.

For example, the generation unit 42 estimates that the known user has acquired information regarding the search query at the search date and time through search behavior regarding the acquired search history. Furthermore, the generation unit 42 estimates that the known user has acquired information regarding the keyword included in the product name to be purchased at the purchase date and time through purchase behavior related to the acquired purchase history. Furthermore, the generation unit 42 estimates that the known user has acquired information regarding keywords included in the content viewed at the viewing date and time through the viewing behavior related to the acquired viewing history. In addition, through the posting behavior related to the acquired posting history, the generation unit 42 generates, for example, information posted by a known user regarding an answer at a date and time when posting information regarding an answer from another user to a question posted by the known user is received. Presumably you have obtained information about the included keywords. Furthermore, the generation unit 42 estimates that the known user has acquired information regarding the keyword included in the message on the date and time when the message was received through the exchange of messages regarding the acquired message exchange history. In this way, the generation unit 42 estimates each piece of information regarding the predetermined object acquired by the known user through each action related to the action history.

Further, when estimating each piece of information acquired by a known user, the generation unit 42 estimates that the known user has acquired each piece of information in the order of the estimated acquisition date and time of each piece of information. In this way, the generation unit 42 acquires information indicating the order in which the user acquired each piece of information regarding a predetermined object.

Subsequently, the generation unit 42 automatically generates information on a predetermined object acquired by the known user through each action related to the action history of the known user and information indicating the order in which the known user acquired each piece of information regarding the predetermined object. The machine learning model is trained to output the skill level of known users when input to the learning model. Here, each piece of information acquired by a known user and the information indicating the order in which each piece of information was acquired can be said to be a type of time-series data. Therefore, the generation unit 42 performs the above learning using a recurrent neural network (RNN) or LSTM (Long Short Term Memory), which is suitable for learning time series data, as an example of a machine learning model. Good too. For example, when the generation unit 42 inputs each piece of information regarding a predetermined object acquired by a known user into the RNN or LSTM in accordance with the order in which the known user acquired each piece of information regarding the predetermined object, the generation unit 42 determines the skill level of the known user. Train the RNN or LSTM to output .

As a result, the information providing device 10 can estimate the skill level of the user based on which information on a predetermined object the user acquired in what order, so the skill level of the user can be estimated appropriately. can do.

(Estimation unit 43)
The estimation unit 43 estimates the skill level of the user regarding a predetermined object based on the user's behavior history. Specifically, the estimating unit 43 estimates the skill level using the trained machine learning model generated by the generating unit 42.

More specifically, the estimation unit 43 refers to the history information database 32 and obtains the user's behavior history in the period from when the user started learning about a predetermined object to the present. For example, the estimation unit 43 may specify the search date and time when the user first searched for a search query related to the predetermined target as the time when the user started learning about the predetermined target. Furthermore, the estimation unit 43 acquires, as examples of the behavior history, the user's search history, the user's purchase history, the user's browsing history, the user's posting history, and the user's message exchange history. Subsequently, upon acquiring the user's behavior history, the estimation unit 43 estimates each piece of information regarding a predetermined object acquired by the user through each behavior related to the acquired behavior history.

For example, the estimating unit 43 estimates that the user has acquired information regarding the search query at the search date and time through search behavior regarding the acquired search history. Furthermore, the estimating unit 43 estimates that the user has acquired information regarding the keyword included in the product name to be purchased at the purchase date and time through purchase behavior related to the acquired purchase history. Furthermore, the estimating unit 43 estimates that the user has acquired information regarding keywords included in the article to be viewed at the viewing date and time through the viewing behavior related to the acquired viewing history. Furthermore, the estimating unit 43 estimates that, through the posting behavior regarding the acquired posting history, information regarding the keywords included in the posted information regarding the answer was acquired at the date and time when the posted information regarding the answer by the answerer to the user's question was received. . Furthermore, the estimating unit 43 estimates that the user has acquired information regarding the keyword included in the message at the date and time when the message was received through the exchange of messages regarding the acquired message exchange history. In this way, the estimating unit 43 estimates each piece of information regarding the predetermined object that the user has acquired through each action related to the action history.

Further, when estimating each piece of information acquired by the user, the estimating unit 43 estimates that the user has acquired each piece of information in the order of the estimated acquisition date and time of each piece of information. In this way, the estimation unit 43 acquires information indicating the order in which the user acquired each piece of information regarding a predetermined object.

When the estimation unit 43 acquires each piece of information regarding a predetermined object acquired by the user through each action related to the behavior history and the information indicating the order in which the user acquired each piece of information regarding the predetermined object, the estimation unit 43 calculates the predetermined information acquired by the user. By inputting each piece of information regarding the target into the trained machine learning model generated by the generation unit 42 according to the order in which the user acquired each piece of information, the skill level output from the machine learning model can be used to estimate the user's skill level. Get as result. Similarly, the estimating unit 43 estimates the skill level of each user regarding a predetermined object based on the behavior history of each user.

(Reception Department 44)
The receiving unit 44 receives a request from a predetermined user to request information distribution. For example, the receiving unit 44 receives a request from a predetermined user to request distribution of posted information.

(Decision unit 45)
When the reception unit 44 receives the request, the determination unit 45 determines the party with whom information is to be transmitted and received from a predetermined user based on the skill level estimated for each user by the estimation unit 43. Specifically, the determining unit 45 determines the party with whom information is to be transmitted and received from a predetermined user based on the difference in skill level estimated for each user by the estimating unit 43. For example, if the difference between the skill level estimated for a predetermined user and the skill level estimated for another user different from the predetermined user falls within a predetermined range, the determining unit 45 A user is determined as a party to send and receive information to and from a predetermined user.

Thereby, the information providing device 10 can control the users such that the difference in skill level falls within an appropriate range to exchange information. That is, the information providing device 10 can allow the user to obtain useful information.

On the other hand, if the difference between the skill level estimated for a predetermined user and the skill level estimated for another user different from the predetermined user does not fall within a predetermined range, the determining unit 45 Exclude a user from the parties that send and receive information to and from a specified user.

Thereby, the information providing device 10 can control, for example, so that users with large differences in skill level do not exchange information with each other. That is, in the information providing device 10, for example, a user starting from scratch (a user with a low skill level) cannot obtain useful information because he/she exchanges information with a person with a high skill level, and as a result, becomes frustrated. can be prevented.

(Distribution department 46)
The distribution unit 46 distributes, to a predetermined user, information regarding another user determined by the determination unit 45 as a partner with whom information is to be transmitted and received with the predetermined user. For example, the distribution unit 46 distributes, to a predetermined user, posted information of another user determined by the determination unit 45 as a partner with whom information is to be transmitted and received with the predetermined user.

[7. Modified example]
The information providing device 10 described above may be implemented in various different forms other than the above embodiment. Therefore, a modification of the embodiment will be described below.

[7-1. Skill level estimation process]
In the embodiment described above, a case has been described in which the estimation unit 43 estimates the skill level based on the behavior history from the time when the user started learning about a predetermined subject to the present. The method for estimating skill level is not limited to this.

Specifically, the estimation unit 43 may estimate the skill level based on the behavior history in the most recent predetermined period. For example, the estimation unit 43 may estimate the skill level based on the behavior history in the most recent past 6 months (or the most recent 3 months, the most recent 12 months, etc.).

As a result, the information providing device 10 can prevent the user's past learning methods and information from being mixed in by using the most recent behavior history, and therefore can appropriately estimate the user's skill level. Can be done.

[7-2. Process of determining the party to send and receive information〕
Further, in the embodiment described above, if the difference between the skill level estimated for a predetermined user and the skill level estimated for another user falls within a predetermined range, the determining unit 45 Although a case has been described in which a predetermined user is determined as a party with whom information is to be transmitted and received, the method by which the determining unit 45 determines a party with which information is to be transmitted and received is not limited to this.

[7-2-1. Users with similar skill levels]
For example, the estimating unit 43 estimates each of a plurality of skill levels possessed by a user regarding each of a plurality of objects, based on the user's behavior history. For example, the estimation unit 43 estimates the skill level of each user regarding each of a plurality of programming languages. The determining unit 45 determines when the difference between each of the plurality of skill levels estimated for the predetermined user and each of the plurality of skill levels estimated for another user different from the predetermined user falls within a predetermined range. determines another user as the party with whom information is to be sent and received with the predetermined user.

In this way, the information providing device 10 can match a user with a more suitable partner by matching users with a plurality of skill level differences within an appropriate range.

[7-2-2. Users whose skill level has increased at a similar rate]
The determining unit 45 also determines the degree of increase in the skill level estimated for a predetermined user over a predetermined period and the degree of increase in the skill level estimated for another user different from the predetermined user over a predetermined period. If the difference falls within a predetermined range, another user is determined as the party with whom information is to be sent and received with the predetermined user.

In this way, the information providing device 10 can match a user with a more suitable partner by matching users whose skill level has increased to a similar degree (that is, the range of improvement).

[7-2-3. Users whose skill level exceeds a predetermined threshold]
Further, if the skill level estimated for another user different from the predetermined user exceeds a predetermined threshold, the determining unit 45 determines the other user as the party with whom information is to be sent and received with the predetermined user. You may.

In this way, the information providing device 10 can match the user with a person who has a high skill level equivalent to, for example, an expert or expert who is desired as a role model.

[7-2-4. Other users〕
Further, the determining unit 45 may determine a user whose characteristics, such as Strengths Finder, are similar to the predetermined user as the party with whom information is to be sent and received with the predetermined user. Further, the determining unit 45 may determine a user who does not have time due to childcare or a user whose attribute information is similar to the predetermined user, such as an executive class, as the party with whom information is to be sent and received with the predetermined user. Further, the determining unit 45 may determine a user whose schedule management method, such as time devoted to studying and disposable time, is similar to the predetermined user as the party with whom information is to be sent and received. Further, the determining unit 45 may determine a user whose status, such as age, annual income, and working industry, is similar to the predetermined user as the party with whom information is to be sent and received.

Further, in the above embodiment, the processing that is being executed by the information providing device 10 may actually be executed by the terminal device 100. That is, the process may be completed standalone (by the terminal device 100 alone). In this case, it is assumed that the terminal device 100 has the functions of the information providing device 10 in the above embodiment.

[8. effect〕
As described above, the information processing device (information providing device 10) according to the present application includes the estimating section 43 and the determining section 45. The estimation unit 43 estimates the skill level of the user regarding a predetermined object based on the user's behavior history. The determining unit 45 determines a party with whom information is to be transmitted and received based on the skill level estimated for each user.

Thereby, the information processing device can match the user with a partner according to the skill level and enable the user to exchange information. Therefore, the information processing device can allow the user to obtain useful information.

Furthermore, the estimating unit 43 estimates the skill level based on each piece of information regarding the predetermined object that the user has acquired through each action related to the action history and information indicating the order in which the user has acquired each piece of information regarding the predetermined object. .

As a result, the information processing device can estimate the user's skill level based on which information about a predetermined object has been acquired in what order, so the information processing device can appropriately estimate the user's skill level. be able to.

Furthermore, the estimating unit 43 estimates the skill level based on the user's behavior history during the period from when he started learning about the predetermined object to the present.

As a result, the information processing device can appropriately estimate the user's skill level since it can take into account the user's learning process from the time the user started learning about a given subject to the present. be able to.

Furthermore, the estimation unit 43 estimates the skill level based on the behavior history in the most recent predetermined period.

As a result, the information processing device can, for example, prevent the user's past learning methods and information from being mixed up, and therefore can appropriately estimate the user's skill level.

Furthermore, the estimation unit 43 calculates the skill level based on the user's search history, the user's purchase history, the user's browsing history, the user's posting history, and the user's message exchange history as the behavior history. Estimate.

Thereby, the information processing device can appropriately estimate the skill level of the user based on information such as a search query acquired by the user in the process of learning about a predetermined object.

Further, the information processing device (information providing device 10) further includes a generation unit 42. The generation unit 42 generates a machine learning model that estimates the skill level from the behavior history. The estimation unit 43 estimates the skill level using the trained machine learning model.

Thereby, the information processing device can appropriately learn the characteristics of the user's behavior history by using the machine learning model, and therefore can appropriately estimate the user's skill level.

In addition, the generation unit 42 generates information regarding a predetermined object acquired by the known user through each action related to the action history of the known user whose skill level is known, and the order in which the known user acquires each information regarding the predetermined object. The machine learning model is trained to output the known skill level of the known user when information indicating the information is input to the machine learning model.

Thereby, the information processing device can cause the machine learning model to learn which information regarding a predetermined object has been acquired in what order by the user, so that the skill level of the user can be appropriately estimated.

Further, the determining unit 45 determines a party with which information is to be transmitted and received from a predetermined user based on the difference in skill level estimated for each user.

Thereby, the information processing device can, for example, avoid matching users with large differences in skill level. In other words, for example, a user starting from scratch (a user with a low skill level) cannot obtain useful information due to exchanging information with a person with a high skill level, and as a result, becomes frustrated. can be prevented from occurring. Further, the information processing device can match users whose skill level difference falls within an appropriate range. That is, the information processing device can allow the user to obtain useful information.

Further, if the difference between the skill level estimated for a predetermined user and the skill level estimated for another user different from the predetermined user falls within a predetermined range, the determining unit 45 A user is determined as a party to send and receive information to and from a predetermined user.

Thereby, the information processing device can control the users such that the difference in skill level falls within an appropriate range to exchange information. That is, the information processing device can allow the user to obtain useful information.

Further, if the difference between the skill level estimated for a predetermined user and the skill level estimated for another user different from the predetermined user does not fall within a predetermined range, the determining unit 45 Exclude a user from the parties that send and receive information to and from a specified user.

Thereby, the information processing device can control, for example, so that users with large skill levels do not exchange information with each other. In other words, for example, a user starting from scratch (a user with a low skill level) cannot obtain useful information due to exchanging information with a person with a high skill level, and as a result, becomes frustrated. can be prevented.

Furthermore, the estimation unit 43 estimates each of a plurality of skill levels possessed by the user regarding each of the plurality of objects, based on the user's behavior history. The determining unit 45 determines when the difference between each of the plurality of skill levels estimated for the predetermined user and each of the plurality of skill levels estimated for another user different from the predetermined user falls within a predetermined range. determines another user as the party with whom information is to be sent and received with the predetermined user.

In this way, the information processing device can match a user with a more suitable partner by matching users with a plurality of skill level differences within an appropriate range. Thereby, the information processing device can allow the user to obtain useful information.

The determining unit 45 also determines the degree of increase in the skill level estimated for a predetermined user over a predetermined period and the degree of increase in the skill level estimated for another user different from the predetermined user over a predetermined period. If the difference falls within a predetermined range, another user is determined as the party with whom information is to be sent and received with the predetermined user.

In this way, the information processing device can match a user with a more suitable partner by matching users with similar skill level increases (that is, the range of improvement). Thereby, the information processing device can allow the user to obtain useful information.

Further, if the skill level estimated for another user different from the predetermined user exceeds a predetermined threshold, the determining unit 45 determines the other user as the party with whom information is to be sent and received with the predetermined user. do.

In this way, the information processing device can match the user with a person who has a high skill level equivalent to, for example, a skilled person or expert whom the user wants to model. Thereby, the information processing device can allow the user to obtain useful information from a person with a high skill level.

[9. Hardware configuration]
Further, the terminal device 100 and the information providing device 10 according to the embodiments described above are realized by, for example, a computer 1000 having a configuration as shown in FIG. The information providing device 10 will be described below as an example. FIG. 5 is a diagram showing an example of the hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output I/F (Interface) 1060, an input I/F 1070, and a network I/F 1080 are connected to a bus. 1090.

The arithmetic unit 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and performs various processes. The arithmetic device 1030 is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the calculation device 1030 for various calculations. Further, the secondary storage device 1050 is a storage device in which data used by the calculation device 1030 for various calculations and various databases are registered, and includes a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid Disk Drive). This is realized using flash memory, etc. The secondary storage device 1050 may be a built-in storage or an external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), a NAS (Network Attached Storage), a file server, or the like.

The output I/F 1060 is an interface for transmitting information to be output to the output device 1010 that outputs various information such as a display, a projector, and a printer. (Digital Visual Interface) and HDMI (registered trademark) (High Definition Multimedia Interface). Further, the input I/F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, keypad, button, scanner, etc., and is realized by, for example, a USB or the like.

Further, the output I/F 1060 and the input I/F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, output device 1010 and input device 1020 may be wireless devices.

Moreover, the output device 1010 and the input device 1020 may be integrated like a touch panel. In this case, the output I/F 1060 and the input I/F 1070 may also be integrated as an input/output I/F.

Note that the input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

Network I/F 1080 receives data from other devices via network N and sends it to computing device 1030, and also sends data generated by computing device 1030 to other devices via network N.

Arithmetic device 1030 controls output device 1010 and input device 1020 via output I/F 1060 and input I/F 1070. For example, the arithmetic device 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040, and executes the loaded program.

For example, when the computer 1000 functions as the information providing device 10, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 40 by executing a program loaded onto the primary storage device 1040. Further, the arithmetic device 1030 of the computer 1000 may load a program obtained from another device via the network I/F 1080 onto the primary storage device 1040, and execute the loaded program. Furthermore, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I/F 1080, and may call and use program functions, data, etc. from other programs of other devices.

[10. others〕
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those that are in a so-called equivalent range. Furthermore, the aforementioned components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the constituent elements can be made without departing from the gist of the embodiments described above.

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

Furthermore, each component of each device shown in the drawings is functionally conceptual, and does not necessarily need to be physically configured as shown in the drawings. In other words, the specific form of distributing and integrating each device is not limited to what is shown in the diagram, and all or part of the devices can be functionally or physically distributed or integrated in arbitrary units depending on various loads and usage conditions. Can be integrated and configured.

For example, the information providing device 10 described above may be realized by a plurality of server computers, or depending on the function, it may be realized by calling an external platform etc. using an API (Application Programming Interface), network computing, etc. can be changed flexibly.

Furthermore, the above-described embodiments and modifications can be combined as appropriate within a range that does not conflict with the processing contents.

Further, the above-mentioned "section, module, unit" can be read as "means", "circuit", etc. For example, the estimating section can be replaced with estimating means or estimating circuit.

10 Information providing device 20 Communication unit 30 Storage unit 31 User information database 32 History information database 40 Control unit 41 Acquisition unit 42 Generation unit 43 Estimation unit 44 Reception unit 45 Determination unit 46 Distribution unit 100 Terminal device

Claims (15)

an estimation unit that estimates the skill level of the user regarding a predetermined object based on the user's behavior history;
a determining unit that determines a party to send and receive information to and from a predetermined user based on the skill level estimated for each user;
Equipped with
The estimation unit is
As the action history, the skill level is determined based on the user's search history, the user's purchase history, the user's browsing history, the user's posting history, and the user's message exchange history. estimate,
An information processing device characterized by: a generation unit that generates a machine learning model that estimates the skill level of the user regarding a predetermined object from the user's behavior history;
an estimation unit that estimates the skill level using the trained machine learning model;
a determining unit that determines a party to send and receive information to and from a predetermined user based on the skill level estimated for each user;
Equipped with
The generation unit is
Indicates each information regarding the predetermined object acquired by the known user through each action related to the action history of the known user whose skill level is known, and the order in which the known user acquired each information regarding the predetermined object. training the machine learning model to output the skill level that is known for the known user when information is input to the machine learning model;
An information processing device characterized by: The estimation unit is
Estimating the skill level based on each information regarding the predetermined object acquired by the user through each action related to the action history and information indicating the order in which the user acquired each information regarding the predetermined object;
The information processing device according to claim 1 or 2 , characterized in that: The estimation unit is
Estimating the skill level based on the behavior history in a period from when the user started learning about the predetermined subject to the present;
The information processing device according to any one of claims 1 to 3 . The estimation unit is
estimating the skill level based on the behavior history in the most recent predetermined period;
The information processing device according to any one of claims 1 to 4 , characterized in that: The determining unit is
determining a partner to send and receive information to and from the predetermined user based on the difference in skill level estimated for each user;
The information processing device according to any one of claims 1 to 5 . The determining unit is
If the difference between the skill level estimated for the predetermined user and the skill level estimated for another user different from the predetermined user falls within a predetermined range, the other user is Deciding who to send and receive information from the users of
The information processing device according to any one of claims 1 to 6 , characterized in that: The determining unit is
If the difference between the skill level estimated for the predetermined user and the skill level estimated for another user different from the predetermined user does not fall within a predetermined range, the other user is Exclude a specified user from those who send and receive information,
The information processing device according to any one of claims 1 to 7 , characterized in that: The estimation unit is
Estimating each of a plurality of skill levels of the user regarding each of a plurality of objects based on the user's behavior history,
The determining unit is
If the difference between each of the plurality of skill levels estimated for the predetermined user and each of the plurality of skill levels estimated for another user different from the predetermined user falls within a predetermined range, determining another user as a party to send and receive information to and from the predetermined user;
The information processing device according to any one of claims 1 to 8 , characterized in that: The determining unit is
The difference between the degree of increase in the skill level estimated for the predetermined user over the predetermined period and the degree of increase in the skill level estimated for the predetermined period for another user different from the predetermined user is a predetermined difference. If it falls within the range, determining the other user as the party to send and receive information with the predetermined user;
The information processing device according to any one of claims 1 to 9 . The determining unit is
If the skill level estimated for another user different from the predetermined user exceeds a predetermined threshold, determining the other user as a party to send and receive information with the predetermined user;
The information processing device according to any one of claims 1 to 10 . An information processing method performed by a computer, the method comprising:
an estimating step of estimating the skill level of the user regarding a predetermined object based on the user's behavior history;
a determining step of determining a party to send and receive information to and from a given user based on the estimated skill level of each user;
including;
The estimation step includes:
As the action history, the skill level is determined based on the user's search history, the user's purchase history, the user's browsing history, the user's posting history, and the user's message exchange history. estimate,
An information processing method characterized by: An information processing method performed by a computer, the method comprising:
a generation step of generating a machine learning model for estimating the skill level of the user regarding a predetermined object from the user's behavior history;
an estimation step of estimating the skill level using the trained machine learning model;
a determining step of determining a party to send and receive information to and from a given user based on the estimated skill level of each user;
including;
The production step includes:
Indicates each information regarding the predetermined object acquired by the known user through each action related to the action history of the known user whose skill level is known, and the order in which the known user acquired each information regarding the predetermined object. training the machine learning model to output the skill level that is known for the known user when information is input to the machine learning model;
An information processing method characterized by: an estimation procedure for estimating the skill level of the user regarding a predetermined object based on the user's behavior history;
a determination procedure for determining a party to send and receive information to and from a given user based on the estimated skill level of each user;
make the computer run
The estimation procedure is
As the action history, the skill level is determined based on the user's search history, the user's purchase history, the user's browsing history, the user's posting history, and the user's message exchange history. estimate,
Information processing program. a generation procedure for generating a machine learning model for estimating the skill level of the user regarding a predetermined object from the user's behavior history;
an estimation procedure for estimating the skill level using the trained machine learning model;
a determination procedure for determining a party to send and receive information to and from a given user based on the estimated skill level of each user;
make the computer run
The generation procedure is
Indicates each information regarding the predetermined object acquired by the known user through each action related to the action history of the known user whose skill level is known, and the order in which the known user acquired each information regarding the predetermined object. training the machine learning model to output the skill level that is known for the known user when information is input to the machine learning model;
Information processing program.

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