JP2023179929A - Information processing device, information processing method, and information processing program - Google Patents

Abstract

[Problem] To propose posting of comments on distributed content such as news to appropriate users. [Solution] An information processing device according to the present application includes an estimation unit that estimates the attributes of a user who proposes posting a comment on the distributed content based on information regarding the distributed content, and a user with the estimated attributes. , a distribution unit that distributes suggested content that suggests posting of comments on the distributed content, along with the distributed content and existing comments. [Selection diagram] Figure 1

Description

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

A technique for easily requesting a review is disclosed.

JP2022-072292A

However, the above-mentioned conventional technology requests other users belonging to the same group as the user to review content shared by the group. Therefore, it cannot be said that posting comments on distributed content such as news is proposed to appropriate users among an unspecified number of users.

The present application has been made in view of the above, and its purpose is to suggest appropriate users to post comments on distributed content such as news.

The information processing device according to the present application includes an estimating unit that estimates an attribute of a user who proposes posting a comment on the distributed content, based on information regarding the distributed content; The present invention is characterized by comprising a distribution unit that distributes suggested content that proposes posting of comments on the distributed content, along with the content and existing comments.

According to one aspect of the embodiment, posting of comments on distributed content such as news can be suggested to appropriate users.

FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information processing system according to an embodiment. FIG. 3 is a diagram illustrating a configuration example of a terminal device according to an embodiment. FIG. 4 is a diagram illustrating a configuration example of a server device according to an embodiment. FIG. 5 is a diagram showing an example of a user information database. FIG. 6 is a diagram showing an example of a history information database. FIG. 7 is a diagram showing an example of the proposal information database. FIG. 8 is a flowchart showing the processing procedure according to the embodiment. FIG. 9 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. Overview of information processing method]
First, with reference to FIG. 1, an overview of an information processing method performed by an information processing apparatus according to an embodiment will be described. FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. In addition, in FIG. 1, a case will be described as an example in which posting a comment on distributed content such as news is proposed to an appropriate user.

As shown in FIG. 1, the information processing system 1 includes a terminal device 10 and a server device 100. The terminal device 10 and the server device 100 are connected to be able to communicate with each other by wire or wirelessly via a network N (see FIG. 2). In this embodiment, the terminal device 10 cooperates with the server device 100.

The terminal device 10 is a smart device such as a smartphone or a tablet terminal used by a user U (user), and is connected to an arbitrary server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). This is a mobile terminal device that can communicate. Further, the terminal device 10 has a screen such as a liquid crystal display, which has a touch panel function, and displays data such as content through a tap operation, a slide operation, a scroll operation, etc. from the user U using a finger or a stylus. Accepts various operations on. Note that an operation performed on an area of the screen where content is displayed may be an operation on the content. Further, the terminal device 10 may be not only a smart device but also an information processing device such as a desktop PC (Personal Computer) or a notebook PC.

The server device 100 cooperates with the terminal device 10 of each user U, and provides API (Application Programming Interface) services for various applications (hereinafter referred to as apps) and various data to the terminal device 10 of each user U. It is an information processing device that provides information, and is realized using computers, cloud systems, etc.

Further, the server device 100 may be an information processing device that provides some kind of web service online to the terminal device 10 of each user U. For example, the server device 100 provides web services such as Internet connection, search service, SNS (Social Networking Service), electronic commerce (EC), electronic payment, online games, online banking, online trading, accommodation/ticket reservation, Services such as video/music distribution, news, maps, route searches, route guidance, route information, operation information, weather forecasts, etc. may be provided. In reality, the server device 100 may cooperate with various servers that provide the above-mentioned Web services, mediate the Web services, or may be in charge of processing the Web services.

Note that the server device 100 can acquire user information regarding the user U. For example, the server device 100 acquires information regarding user U's attributes such as user U's gender, age, and residential area. The server device 100 stores and manages identification information indicating the user U (user ID, etc.) as well as information regarding attributes of the user U.

Further, the server device 100 acquires various kinds of history information (log data) indicating the actions of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. For example, the server device 100 acquires a location history, which is a history of user U's location, date and time, from the terminal device 10. The server device 100 also acquires a search history, which is a history of search queries input by the user U, from a search server (search engine). Additionally, the server device 100 acquires a viewing history, which is a history of content viewed by the user U, from the content server. The server device 100 also acquires a purchase history (payment history) that is a history of product purchases and payment processing by the user U from the electronic commerce server and the payment processing server. Further, the server device 100 may acquire the listing history and the sales history, which are the listing history of the user U on the marketplace, from the electronic commerce server or the payment processing server. The server device 100 also acquires a posting history, which is a history of postings by the user U, from a posting server or SNS server that provides a word-of-mouth posting service. Note that the various servers described above may be the server device 100 itself. That is, the server device 100 may function as the various servers described above.

[1-1. Suggestions for posting comments〕
In this embodiment, the server device 100 estimates the attributes (segment, persona, etc.) of the user U who proposes posting a comment on the distributed content, based on information regarding the distributed content. Then, the server device 100 distributes the proposed content that suggests posting a comment to the user U having the estimated attribute, together with the distributed content.

For example, as shown in FIG. 1, the server device 100 directly or indirectly (via another server device, etc.) receives user information ( (attribute information, history information, etc.) (step S1).

Next, the server device 100 estimates highly relevant user attributes (user segments, user personas) from the titles and contents (distributor, theme, category) of distributed content such as news (step S2). ).

At this time, the server device 100 may use machine learning to estimate highly relevant user attributes from the title and content of distributed content such as news. For example, the server device 100 uses the title and content of distributed content such as news as input data, and generates an estimation model that outputs highly relevant user attributes. Note that a plurality of user attributes may be output.

Alternatively, in order to estimate user attributes that are highly relevant to the title and content of distributed content such as news, the server device 100 uses machine learning to input a set of the title and content of distributed content and user attributes as input data, An estimation model may be generated that outputs a score (or level) regarding the degree of association.

Alternatively, the server device 100 uses machine learning to generate an estimation model that uses a set of the title and content of the distributed content and a score related to relevance as input data, and outputs user attributes (or users with the user attributes). It's okay.

As for the machine learning method, deep learning, RNN (Recurrent Neural Network), LSTM (Long Short Term Memory), etc. may be used. Note that these are just examples, and the invention is not limited to these examples.

Next, the server device 100 determines the type (content) of comments that it wants users with highly relevant user attributes to post about the distributed content (step S3).

At this time, the server device 100 may use machine learning to estimate the type of comment that the user wants to post from the title and content of distributed content such as news, and user attributes. For example, the server device 100 uses as input data a set of the title and content of distributed content such as news and highly related user attributes, and generates an estimation model that outputs the type of comment desired to be posted. Note that a plurality of types of comments may be output.

Next, the server device 100 makes a proposal to suggest a user with a highly relevant user attribute to post a comment based on the highly relevant user attribute and the type of comment that the user with the user attribute wants the user to post. Content is generated (step S4).

Next, the server device 100 sends the distributed content, comments on the distributed content (such as existing comments posted by other users), and suggested content that suggests posting comments to users with highly relevant user attributes. (Step S5).

At this time, the server device 100 may distribute each comment on the distributed content so that the user attributes of the user who posted the comment (and the type of the comment) are displayed on the screen of the user's terminal device 10. .

Next, the server device 100 collects comments made in response to the distribution of the proposed content (comments according to the type of comment desired to be posted) from users with highly relevant user attributes who received the proposed content. Posts are accepted (step S6).

For example, if the title or content of distributed content such as news is related to "job hunting", the highly relevant user attributes are "job hunting student" (currently job hunting), "job hunting experience" ( (after receiving a job offer), "recruiting person" (interviewer), etc. In this case, it is also possible to classify by company, industry, or occupation. It is also possible to classify them into categories such as "new graduate hires," "second-year new graduate hires," and "mid-career hires." It is also possible to classify them by era, such as the "bubble period" and the "employment ice age." Depending on the position and attributes of each user, the content of comments may vary even for news items with the same theme.

[1-2. variation〕
The server device 100 uses a table of "keyword x attribute x what you want written". For example, the server device 100 changes the content of what the user wants to write based on the combination of articles and attributes, such as "job hunting x 3 years after employment x experience stories" or "job hunting x job hunting x interview information".

Additionally, the server device 100 determines the target user attributes and the type of comment that is desired to be posted, depending on the type (content) and keywords of comments (existing comments) already posted on the distributed content. It's okay. For example, the server device 100 wants comments such as "3 years after employment × experiences" and "currently employed × interview information", but if the latter is often posted among the existing comments, "3 years after employment × In order to increase the number of postings of ``experience stories,'' we will distribute suggested content that suggests posting ``experience stories'' to target users who have been employed for 3 years.

In addition, the server device 100 extracts a request such as "I want to know about the experiences of XX people" from among the existing comments, determines that the extracted request is the type of comment that the user wants to post, and Suggested content may be generated to encourage users of the attributes to post comments in accordance with their requests. At this time, the server device 100 may estimate a highly relevant user attribute (user segment, user persona) based on the extracted request, or determine the type (content) of the comment you want posted. You may decide.

Further, the server device 100 may encourage users with the target user attributes to post by asking them something like "How is it compared to when you were job hunting?"

Further, the server device 100 may distribute the proposed content only to users with corresponding attributes. In this case, the server device 100 does not distribute the proposed content to users other than highly relevant user attributes (users with other user attributes, etc.), and only distributes the distributed content and comments on the distributed content. You can do it like this. By excluding users with other attributes and distributing suggested content only to users with the corresponding attributes, it is possible to improve the accuracy of the content of comments posted according to user attributes.

Further, the server device 100 may distribute comment trees separately for each user attribute regarding distribution content. For example, when viewing a certain news, the server device 100 displays a comment tree for women and a comment tree for men separately. Additionally, the server device 100 can perform display control such as not displaying a comment tree for men when accessed by a woman.

[2. Configuration example of information processing system]
Next, the configuration of the information processing system 1 including the server device 100 according to the embodiment will be described using FIG. 2. FIG. 2 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 2, the information processing system 1 according to the embodiment includes a terminal device 10 and a server device 100. These various devices are connected via a network N so that they can communicate by wire or wirelessly. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

Furthermore, the number of devices included in the information processing system 1 shown in FIG. 2 is not limited to what is illustrated. For example, in FIG. 2, only one terminal device 10 is shown for simplification of illustration, but this is just an example and is not limited, and there may be two or more terminal devices.

The terminal device 10 is an information processing device used by the user U. For example, the terminal device 10 may be a smart device such as a smartphone or a tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a game console or AV device with a communication function, a car navigation system, a smart watch, or the like. These include wearable devices such as head-mounted displays, smart glasses, etc. Further, the terminal device 10 may be a house/building, a car, a home appliance, an electronic device, etc. compatible with IOT (Internet of Things).

The terminal device 10 also supports wireless communication networks such as LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation), Bluetooth (registered trademark), and wireless LAN (Local The server device 100 can be connected to the network N via short-range wireless communication such as an area network) and can communicate with the server device 100.

The server device 100 is, for example, a computer such as a PC or a blade server, or a mainframe or a workstation. Note that the server device 100 may be realized by cloud computing.

[3. Configuration example of terminal device]
Next, the configuration of the terminal device 10 will be explained using FIG. 3. FIG. 3 is a diagram showing a configuration example of the terminal device 10. As shown in FIG. As shown in FIG. 3, the terminal device 10 includes a communication section 11, a display section 12, an input section 13, a positioning section 14, a sensor section 20, a control section 30 (controller), and a storage section 40. Be prepared.

(Communication Department 11)
The communication unit 11 is connected to a network N (see FIG. 2) by wire or wirelessly, and transmits and receives information to and from the server device 100 via the network N. For example, the communication unit 11 is realized by a NIC (Network Interface Card), an antenna, or the like.

(Display section 12)
The display unit 12 is a display device that displays various information such as position information. For example, the display unit 12 is a liquid crystal display (LCD) or an organic electro-luminescent display (EL display). Further, the display unit 12 is a touch panel type display, but is not limited to this.

(Input section 13)
The input unit 13 is an input device that receives various operations from the user U. For example, the input unit 13 includes buttons for inputting characters, numbers, and the like. Note that the input unit 13 may be an input/output port (I/O port), a USB (Universal Serial Bus) port, or the like. Further, when the display section 12 is a touch panel display, a part of the display section 12 functions as the input section 13. Further, the input unit 13 may be a microphone or the like that receives voice input from the user U. The microphone may be wireless.

(Positioning unit 14)
The positioning unit 14 receives a signal (radio wave) sent from a GPS (Global Positioning System) satellite, and based on the received signal, determines position information (for example, latitude and longitude). That is, the positioning unit 14 positions the terminal device 10 . Note that GPS is just one example of GNSS (Global Navigation Satellite System).

Further, the positioning unit 14 can measure the position using various methods other than GPS. For example, the positioning unit 14 may use various communication functions of the terminal device 10 to measure the position as an auxiliary positioning means for position correction and the like, as described below.

(Wi-Fi positioning)
For example, the positioning unit 14 positions the terminal device 10 using the Wi-Fi (registered trademark) communication function of the terminal device 10 or the communication network provided by each communication company. Specifically, the positioning unit 14 performs Wi-Fi communication, etc., and determines the position of the terminal device 10 by measuring the distance to nearby base stations and access points.

(Beacon positioning)
Further, the positioning unit 14 may use the Bluetooth (registered trademark) function of the terminal device 10 to measure the position. For example, the positioning unit 14 measures the position of the terminal device 10 by connecting to a beacon transmitter connected by a Bluetooth (registered trademark) function.

(geomagnetic positioning)
Furthermore, the positioning unit 14 positions the terminal device 10 based on the geomagnetic pattern of the structure measured in advance and the geomagnetic sensor included in the terminal device 10 .

(RFID positioning)
Further, for example, if the terminal device 10 has an RFID (Radio Frequency Identification) tag function equivalent to a contactless IC card used at station ticket gates, stores, etc., or has a function to read an RFID tag. In this case, the location where the terminal device 10 used the terminal device 10 is recorded together with the information that the payment was made. The positioning unit 14 may measure the position of the terminal device 10 by acquiring such information. Further, the position may be determined by an optical sensor, an infrared sensor, or the like provided in the terminal device 10.

The positioning unit 14 may position the terminal device 10 using one or a combination of the above-mentioned positioning means, if necessary.

(sensor section 20)
The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. Note that the connection may be a wired connection or a wireless connection. For example, the sensors may be a detection device other than the terminal device 10, such as a wearable device or a wireless device. In the example shown in FIG. 3, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, an atmospheric pressure sensor 23, an air temperature sensor 24, a sound sensor 25, an optical sensor 26, a magnetic sensor 27, and an image sensor ( camera) 28.

Note that each of the sensors 21 to 28 described above is merely an example and is not limited to the above. That is, the sensor section 20 may be configured to include a portion of each of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of each of the sensors 21 to 28. .

The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects the physical movement of the terminal device 10, such as the moving direction, speed, and acceleration of the terminal device 10. The gyro sensor 22 detects physical movements of the terminal device 10 such as tilt in three axes directions based on the angular velocity of the terminal device 10 and the like. The atmospheric pressure sensor 23 detects the atmospheric pressure around the terminal device 10, for example.

Since the terminal device 10 is equipped with the above-mentioned acceleration sensor 21, gyro sensor 22, atmospheric pressure sensor 23, etc., it is possible to implement technologies such as pedestrian autonomous navigation (PDR) using these sensors 21 to 23, etc. It becomes possible to measure the position of the terminal device 10 using the . This makes it possible to obtain indoor position information that is difficult to obtain using positioning systems such as GPS.

For example, a pedometer using the acceleration sensor 21 can calculate the number of steps, walking speed, and distance walked. Furthermore, by using the gyro sensor 22, it is possible to know the direction of travel of the user U, the direction of the line of sight, and the inclination of the user's body. Further, from the atmospheric pressure detected by the atmospheric pressure sensor 23, it is also possible to know the altitude and the number of floors where the terminal device 10 of the user U is located.

The temperature sensor 24 detects, for example, the temperature around the terminal device 10. The sound sensor 25 detects, for example, sounds around the terminal device 10. The optical sensor 26 detects the illuminance around the terminal device 10 . The magnetic sensor 27 detects, for example, the earth's magnetism around the terminal device 10. The image sensor 28 captures an image of the surroundings of the terminal device 10.

The above-mentioned atmospheric pressure sensor 23, temperature sensor 24, sound sensor 25, optical sensor 26, and image sensor 28 each detect atmospheric pressure, temperature, sound, and illuminance, and capture images of the surroundings, so that the terminal device 10 It is possible to detect the surrounding environment and situation. Furthermore, it is possible to improve the accuracy of the location information of the terminal device 10 based on the environment and situation around the terminal device 10.

(Control unit 30)
The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input/output port, etc., and various circuits. Further, the control unit 30 may be configured with hardware such as an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control section 30 includes a transmitting section 31, a receiving section 32, and a processing section 33.

(Transmission unit 31)
The transmitting unit 31 receives, for example, various information input by the user U using the input unit 13, various information detected by the sensors 21 to 28 mounted on or connected to the terminal device 10, and information measured by the positioning unit 14. The location information of the terminal device 10 and the like can be transmitted to the server device 100 via the communication unit 11.

(Receiving unit 32)
The receiving unit 32 can receive various information provided from the server device 100 and requests for various information from the server device 100 via the communication unit 11 .

(Processing unit 33)
The processing unit 33 controls the entire terminal device 10, including the display unit 12 and the like. For example, the processing unit 33 can output various information transmitted by the transmitting unit 31 and various information received from the server device 100 by the receiving unit 32 to the display unit 12 for display.

(Storage unit 40)
The storage unit 40 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 an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an optical disk. Ru. The storage unit 40 stores various programs, various data, and the like.

[4. Configuration example of server device]
Next, the configuration of the server device 100 according to the embodiment will be described using FIG. 4. FIG. 4 is a diagram showing a configuration example of the server device 100 according to the embodiment. As shown in FIG. 4, the server device 100 includes a communication section 110, a storage section 120, and a control section 130.

(Communication Department 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). Further, the communication unit 110 is connected to the network N (see FIG. 2) by wire or wirelessly.

(Storage unit 120)
The storage unit 120 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 an HDD, an SSD, or an optical disk. As shown in FIG. 4, the storage unit 120 includes a user information database 121, a history information database 122, and a suggestion information database 123.

(User information database 121)
The user information database 121 stores user information regarding the user U. For example, the user information database 121 stores various information such as user U's attributes. FIG. 5 is a diagram showing an example of the user information database 121. In the example shown in FIG. 5, the user information database 121 has items such as "user ID (identifier),""age,""gender,""home,""worklocation," and "interest."

“User ID” indicates identification information for identifying user U. Note that the "user ID" may be user U's contact information (telephone number, email address, etc.), or may be identification information for identifying user U's terminal device 10.

Moreover, "age" indicates the age of the user U identified by the user ID. Note that the "age" may be information indicating the specific age of the user U (for example, 35 years old, etc.), or may be information indicating the age of the user U (for example, 30s, etc.) . Alternatively, the "age" may be information indicating the date of birth of the user U, or may be information indicating the generation of the user U (for example, born in the 1980s). 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. 5, "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. 5, the "work location" is illustrated as an abstract code such as "LC12", but it may also be latitude/longitude information or the like. Further, for example, the "work location" may be a region name or address.

Moreover, "interest" indicates the interest of the user U identified by the user ID. That is, "interest" indicates an object in which the user U identified by the user ID has a high interest. For example, "interest" may be a search query (keyword) that the user U inputs into a search engine. In the example shown in FIG. 5, one "interest" is shown for each user U, but there may be a plurality of "interests".

For example, in the example shown in FIG. 5, 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 is interested in "sports."

Here, in the example shown in FIG. 5, 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 121 is not limited to the above, and may store various information depending on the purpose. For example, the user information database 121 may store various information regarding the terminal device 10 of the user U. In addition, the user information database 121 includes information such as demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral attributes), etc. of user U. Information regarding attributes may also be stored. For example, the user information database 121 includes name, family composition, 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, etc. 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. It's okay.

(History information database 122)
The history information database 122 stores various information related to history information (log data) indicating the actions of the user U. FIG. 6 is a diagram showing an example of the history information database 122. In the example shown in FIG. 6, the history information database 122 includes items such as "user ID,""locationhistory,""searchhistory,""browsinghistory,""purchasehistory," and "posting history."

“User ID” indicates identification information for identifying user U. Further, “position history” indicates a position history that is a history of the user U's position and movement. 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. Moreover, "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. 6, user U identified by user ID "U1" moves as per "location history #1", searches as per "search history #1", and searches as per "view history #1". This indicates that the content is viewed according to "history #1", a predetermined product, etc. is purchased at a predetermined store etc. according to "purchase history #1", and the content is posted according to "post history #1".

Here, in the example shown in FIG. 6, abstracts such as "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" are used. Although the figures are illustrated using ``U1'', ``Location history #1'', ``Search history #1'', ``Browsing history #1'', ``Purchase history #1'' and ``Posting history #1'', It is assumed that information such as specific character strings and numerical values is stored.

Note that the history information database 122 is not limited to the above, and may store various information depending on the purpose. For example, the history information database 122 may store the user U's usage history of a predetermined service. Further, the history information database 122 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 122 may store the payment history of user U's payment using the terminal device 10 (electronic payment).

(Proposal information database 123)
The proposal information database 123 stores various information regarding distribution content and proposal content. FIG. 7 is a diagram showing an example of the proposal information database 123. In the example shown in FIG. 7, the suggestion information database 123 has items such as "distribution content", "attribute", "relevance", "comment type", and "proposed content".

"Distributed content" indicates identification information for identifying distributed content. Note that, in reality, it may be the title or content (distribution source, theme, or category) of the distributed content. Moreover, "attribute" indicates a user attribute (user segment, user persona, etc.) that is highly relevant to the distributed content. Note that there may be a plurality of user attributes. Moreover, "relevance" indicates the relevance between the distributed content and the user attribute. Note that the relevance may be a score (or a level) indicating the degree of relevance. Furthermore, the "comment type" indicates the type (content) of comments that users with highly relevant user attributes are desired to post about the distributed content. Further, "suggested content" indicates suggested content that suggests posting a comment to users with highly relevant user attributes.

For example, in the example shown in FIG. 7, the height of the relationship between the distribution content "Distribution #1" and the user attribute "Attribute #1" is "Relationship #1", and for the user with this user attribute, Comment type "Type #1" Indicates that the proposed content "Proposal #1" that proposes posting a comment is generated and distributed.

Here, in the example shown in FIG. 7, abstract values such as "delivery #1", "attribute #1", "relevance #1", "type #1", and "proposal #1" are used for illustration. However, "Distribution #1", "Attribute #1", "Relevance #1", "Type #1" and "Proposal #1" store information such as specific character strings and numerical values. shall be.

Note that the proposal information database 123 is not limited to the above, and may store various information depending on the purpose. For example, the proposal information database 123 may store identification information for identifying users with highly relevant user attributes. Further, the suggestion information database 123 may store information regarding existing comments on the distributed content. Further, the proposal information database 123 may store identification information for identifying the provider (distributor) of the distributed content. Further, the proposal information database 123 may store information regarding content trees.

(Control unit 130)
Returning to FIG. 4, the explanation will be continued. The control unit 130 is a controller, and controls the server device 100 using, 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). This is realized 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. 4, the control unit 130 includes an acquisition unit 131, an estimation unit 132, a determination unit 133, a generation unit 134, a distribution unit 135, and a reception unit 136.

(Acquisition unit 131)
The acquisition unit 131 acquires a search query input by the user U. For example, when the user U inputs a search query into a search engine or the like and performs a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110. That is, the acquisition unit 131 acquires, via the communication unit 110, a keyword input by the user U into a search window of a search engine, site, or application.

The acquisition unit 131 also acquires user U information regarding the user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information indicating the user U (user UID, etc.), location information of the user U, attribute information of the user U, etc. from the terminal device 10 of the user U. Further, the acquisition unit 131 may acquire identification information indicating the user U, attribute information of the user U, etc. at the time of user U's user registration. The acquisition unit 131 then registers the user U information in the user U information database 121 of the storage unit 120.

Further, the acquisition unit 131 acquires various types of history information (log data) indicating the behavior of the user U via the communication unit 110. For example, the acquisition unit 131 acquires various types of history information indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user UID or the like. The acquisition unit 131 then registers various types of history information in the history information database 122 of the storage unit 120.

(Estimation unit 132)
The estimating unit 132 estimates the attributes of the user U who proposes posting a comment on the distributed content, based on information regarding the distributed content (title, content, etc. of the distributed content). At this time, the estimating unit 132 estimates attributes that are highly relevant to information regarding the distributed content.

(Decision unit 133)
The determining unit 133 determines the type of comment that the user U with highly relevant attributes is desired to post about the distributed content.

(Generation unit 134)
The generation unit 134 generates suggested content that suggests posting a comment to a user U with a highly relevant attribute, based on the highly relevant attribute and the type of comment that the user U with the attribute wants the user U to post. generate.

The generation unit 134 also extracts requests for posting specific content from existing comments, and generates suggested content to encourage users U with the target attributes to post comments in accordance with the requests. do.

(Distribution Department 135)
The distribution unit 135 distributes to the user U having the estimated attribute, the distribution content and existing comments, as well as the proposed content that suggests posting a comment on the distribution content.

Furthermore, the distribution unit 135 does not distribute the proposed content to users U who have attributes other than the estimated attributes, but only distributes the distribution content and existing comments.

Furthermore, the distribution unit 135 distributes the comment tree separately for each attribute of the user U regarding the distribution content.

(Reception Department 136)
The reception unit 136 receives comments from users U who have received the distribution of the proposed content, regarding the distributed content that was performed in response to the distribution of the proposed content.

[5. Processing procedure]
Next, a processing procedure by the server device 100 according to the embodiment will be described using FIG. 8. FIG. 8 is a flowchart showing the processing procedure according to the embodiment. Note that the processing procedure shown below is repeatedly executed by the control unit 130 of the server device 100.

As shown in FIG. 8, the acquisition unit 131 of the server device 100 acquires user information (attribute information, history information, etc.) regarding the user U via the communication unit 110 (step S101).

Next, the estimating unit 132 of the server device 100 estimates highly relevant user attributes (can be user segments, user personas) from the title and content (can be distribution source, theme, category) of the distributed content (step S102).

Subsequently, the determining unit 133 of the server device 100 determines the type (content) of comments that users with highly relevant user attributes should post regarding the distributed content (step S103).

Next, the generation unit 134 of the server device 100 causes the user with the highly relevant user attribute to post a comment based on the highly relevant user attribute and the type of comment that the user with the user attribute wants the user to post. Proposed content that proposes the following is generated (step S104).

Subsequently, the distribution unit 135 of the server device 100 sends the distributed content and comments on the distributed content (existing comments posted by other users, etc.) to users with highly relevant user attributes via the communication unit 110. ), and also distributes suggested content suggesting posting of comments (step S105).

Subsequently, the reception unit 136 of the server device 100 receives comments (posted comments) made in response to the distribution of the proposed content from users with highly relevant user attributes who have received the distribution of the proposed content, via the communication unit 110. (step S106).

[6. Modified example]
The terminal device 10 and server device 100 described above may be implemented in various different forms other than the above embodiments. Therefore, a modification of the embodiment will be described below.

In the above embodiment, part or all of the processing executed by the server device 100 may actually be executed by the terminal device 10. For example, the process may be completed stand-alone (by the terminal device 10 alone). In this case, it is assumed that the terminal device 10 has the functions of the server device 100 in the above embodiment. Further, in the embodiment described above, since the terminal device 10 cooperates with the server device 100, it appears to the user U that the terminal device 10 is also executing the processing of the server device 100. That is, from another point of view, it can be said that the terminal device 10 includes the server device 100.

For example, the terminal device 10 may execute the process of the server device 100 in the above embodiment as the process on the installed application. That is, the process of the server device 100 in the above embodiment may be a process on an application installed on the terminal device 10. At this time, the terminal device 10 may generate the estimated model by on-device learning. Alternatively, the terminal device 10 may cooperate with the server device 100, provide data to the server device 100, and obtain the estimation model generated by the server device 100 through machine learning. Note that the server device 100 may generate an estimation model for each user attribute (segment, persona). Furthermore, the terminal device 10 may cooperate with the server device 100 to generate the estimation model through federated learning.

Furthermore, in the embodiments described above, news and the like are only examples of distributed content. In reality, the distributed content may be a website such as a bulletin board where comments (or some kind of writing) can be posted, as well as SNS, SMS (Short Message Service), a message application, etc. Further, the type (content) of the comment may be a review of a product or service, or may be a response to a questionnaire.

[7. effect〕
As described above, the information processing device (terminal device 10 and server device 100) according to the present application includes an estimation unit that estimates the attributes of the user U who proposes posting a comment on the distributed content based on information regarding the distributed content. 132, and a distribution unit 135 that distributes, to the user U having the estimated attribute, suggested content that proposes posting a comment on the distributed content, along with the distributed content and existing comments.

The estimating unit 132 estimates attributes that are highly relevant to information regarding distributed content.

The information processing device according to the present application further includes a determining unit 133 that determines the type of comment that the user U with highly relevant attributes is desired to post about the distributed content.

The information processing device according to the present application proposes posting of a comment to the user U of the highly relevant attribute based on the highly relevant attribute and the type of comment that the user U of the attribute wants the user U to post. It further includes a generation unit 134 that generates suggested content.

The generation unit 134 extracts a request for posting a specific content from existing comments, and generates suggested content for encouraging the user U of the target attribute to post a comment in accordance with the request.

The information processing device according to the present application further includes a reception unit 136 that accepts posting of comments on the distributed content performed in response to the distribution of the proposed content from the user U who has received the distribution of the proposed content.

The distribution unit 135 does not distribute the proposed content to users U who do not have the estimated attributes, but only distributes the distribution content and existing comments.

The distribution unit 135 divides and distributes comment trees for each attribute of the user U regarding the distribution content.

By using any one or a combination of the above-described processes, the information processing apparatus according to the present application can suggest posting of comments on distributed content such as news to appropriate users.

[8. Hardware configuration]
Further, the terminal device 10 and the server device 100 according to the embodiments described above are realized by, for example, a computer 1000 having a configuration as shown in FIG. The following will explain the server device 100 as an example. FIG. 9 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 (Universal Serial Bus) 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 server device 100, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 130 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.

[9. 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 server device 100 described above may be realized by a plurality of server computers, and 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 acquisition unit can be read as an acquisition means or an acquisition circuit.

1 Information processing system 10 Terminal device 100 Server device 110 Communication unit 120 Storage unit 121 User information database 122 History information database 123 Proposal information database 130 Control unit 131 Acquisition unit 132 Estimation unit 133 Determination unit 134 Generation unit 135 Distribution unit 136 Reception unit

Claims (10)

an estimation unit that estimates attributes of a user who proposes posting a comment on the distributed content based on information regarding the distributed content;
a distribution unit that distributes suggested content that proposes posting a comment on the distributed content, along with the distributed content and existing comments, to users with the estimated attributes;
An information processing device comprising: The information processing apparatus according to claim 1, wherein the estimating unit estimates an attribute that is highly relevant to information regarding the distributed content. a determining unit that determines the type of comment that users with highly relevant attributes are asked to post about the distributed content;
The information processing device according to claim 2, further comprising: a generating unit that generates the suggested content that proposes posting a comment to a user of a highly relevant attribute based on a highly relevant attribute and a type of comment that the user of the attribute wants the user to post;
The information processing device according to claim 3, further comprising: The generation unit extracts a request for posting a specific content from the existing comments, and generates the proposed content for encouraging users with the target attribute to post comments in accordance with the request. The information processing device according to claim 4, characterized in that: a reception unit that receives comments on the distributed content made in response to the distribution of the proposed content from users who have received the distribution of the proposed content;
The information processing device according to claim 1, further comprising: The information processing device according to claim 1, wherein the distribution unit does not distribute the proposed content to users with attributes other than the estimated attributes, and distributes only the distribution content and existing comments. . The information processing apparatus according to claim 1, wherein the distribution unit distributes the distribution content by dividing comment trees for each user attribute. An information processing method executed by an information processing device, the method comprising:
an estimation step of estimating the attributes of a user who proposes posting a comment on the distributed content based on information regarding the distributed content;
a distribution step of distributing suggested content that suggests posting a comment on the distributed content, along with the distributed content and existing comments, to users with the estimated attributes;
An information processing method characterized by comprising: an estimation step of estimating the attributes of a user who proposes posting a comment on the distributed content based on information regarding the distributed content;
A distribution procedure for distributing suggested content that proposes posting a comment on the distributed content, along with the distributed content and existing comments, to users with the estimated attributes;
An information processing program that causes a computer to execute.

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