JP7112634B2 - Content delivery system, delivery device, delivery method, and program - Google Patents

Description

The present invention relates to technology for processing electronic content provided via a network.

With the recent development of information processing technology and the enhancement of networks, it has become possible to use messaging services such as SNS (Social Networking Service) to distribute various electronic contents such as advertisements, photos, and word of mouth. there is

JP 2016-143098 A

When messaging service users receive electronic content, such as advertisements, that they are not interested in, they may block the electronic content or stop using the messaging service.
On the other hand, business operators who post and distribute electronic content using messaging services (hereinafter referred to as content business operators) limit their electronic content to users who are likely to be interested in it. I have a desire to deliver.

SUMMARY OF THE INVENTION The present invention has been made in view of the circumstances described above, and one of the objects thereof is to provide a technology capable of efficiently distributing desired electronic content.

A content distribution system according to an aspect of the present disclosure is a system that distributes electronic content to users using a messaging service, and includes an acquisition unit that acquires access information representing past access history to electronic content by each user. a setting unit that accepts at least the setting of the number of distribution targets for electronic content newly posted by a content provider; an extracting unit that extracts users with many accesses as distribution target users; and a distribution unit that distributes newly posted electronic content to the extracted distribution target users using a messaging service. The gist is to have

Certain aspects of the present invention enable efficient delivery of desired messages.

It is a figure which shows an example of a structure of the content distribution system based on 1st Example. It is a figure which shows an example of the hardware constitutions of a delivery management apparatus, a delivery optimization apparatus, an SNS provision apparatus, and a user terminal. 4 is a diagram for explaining functions of a distribution management device and a distribution optimization device; FIG. FIG. 4 is a diagram exemplifying a distribution setting screen for electronic content displayed on the display of the distribution management device; 4 is a sequence diagram showing specific operations of a delivery management device and a delivery optimization device; FIG. FIG. 11 is a block diagram showing main functions of a content distribution system according to a third embodiment; FIG. FIG. 11 is a diagram illustrating the configuration of electronic content according to the third example; FIG. 12 is a diagram illustrating the configuration of electronic content according to the fourth example;

Preferred embodiments of the present invention will be described with reference to the accompanying drawings. It should be noted that, in each figure, the same reference numerals have the same or similar configurations.

A. This embodiment [first example]
<System configuration>
FIG. 1 is a diagram showing an example of the configuration of a content distribution system 100 according to the first embodiment.
The content delivery system 100 includes a delivery management device 10 , a delivery optimization device 20 , an SNS provision device 30 and a plurality of user terminals 40 . The distribution management device 10, the distribution optimization device 20, the SNS provision device 30, and the plurality of user terminals 40 can communicate with each other via the network N.

One or more portions of network N may be wired or wireless networks. Network N may be, by way of example and not limitation, an Ad Hoc Network, an Intranet, an Extranet, a Virtual Private Network (VPN), a Local Area Network (LAN), a wireless Wireless LAN (WLAN), Wide Area Network (WAN), Wireless WAN (WWAN), Metropolitan Area Network (MAN), Part of the Internet, Public Switched Telephone Network (Public Part of Switched Telephone Network (PSTN), mobile phone networks, ISDNs (Integrated Service Digital Networks), wireless LANs, LTE (Long Term Evolution), CDMA (Code Division Multiple Access), Bluetooth (registered trademark), satellite communication, etc., or a combination of two or more thereof.

The distribution management device 10 is implemented by, for example, a server computer, and distributes electronic content such as advertisements posted by content providers to desired users using a messaging service. In the following description, a user who distributes electronic content using a messaging service is called a "distribution target user".

The distribution optimization device 20 is realized by, for example, a server computer, and optimizes the distribution time of the electronic content posted by the content provider and the distribution target users of the electronic content (details will be described later).

The SNS providing device 30 is implemented by, for example, a server computer, and provides SNS including messaging services to each user. The SNS providing device 30 transmits/receives various electronic contents including messages, stamps, images, videos, advertisements, etc. to/from the user terminal 40 .

The user terminal 40 is a terminal possessed by each user, and includes, for example, a smart phone, a mobile phone, a personal computer, a handheld computer device, a wearable terminal, or the like. The user terminal 40 executes various services by operating applications, Internet browsers, etc. according to user operations.

<Hardware configuration>
FIG. 2 is a diagram showing an example of the hardware configuration of the distribution management device 10, the distribution optimization device 20, the SNS provision device 30, and the user terminal 40. As shown in FIG. The distribution management device 10, the distribution optimization device 20, the SNS provision device 30, and the user terminal 40 each include a CPU (Central Processing Unit) 1, a storage device 2 such as a memory, and a communication IF (Interface) for performing wired or wireless communication. 3. It has an input device 4 for receiving input operations and an output device 5 for outputting information. The input device 4 is, for example, a keyboard, mouse, touch panel, microphone, or the like. The output device 5 is, for example, a display (screen) and/or a speaker.

Hereinafter, functional configurations of the distribution management device 10 and the distribution optimization device 20 will be described in detail with reference to FIG.

<Functional block configuration>
(Distribution management device)
Distribution management device 10 includes distribution setting unit 11 , distribution unit 12 , user identification unit 13 , click information acquisition unit 14 , and storage unit 15 .
The distribution setting unit 11 , the distribution unit 12 , the user identification unit 13 and the click information acquisition unit 14 are implemented by the CPU 1 of the distribution management device 10 executing various programs stored in the storage device 2 . Note that the program can be stored in a storage medium such as a USB memory or a CD-ROM.
The storage unit 15 is realized by the storage device 2, and stores the user table TBL1, the click information table TBL2, and the like.

A distribution setting unit (setting unit) 11 receives various information related to the distribution of electronic content from the content provider CP. Specifically, the distribution setting unit 11 receives information such as the distribution time of the electronic content, the number of distribution target users, and the URL (Uniform Resource Locator) of the electronic content to be distributed (hereinafter collectively referred to as "distribution setting information"). . The distribution setting unit 11 transmits the received distribution setting information to the distribution optimization device 20 , and transmits the electronic content posted by the content provider CP to the distribution unit 12 .

The distribution unit 12 uses the messaging service to distribute the electronic content posted by the content provider CP to the specified distribution target users.

The user identification unit 13 assigns and manages identification information (ID) for identifying a user who uses the system 100, and identifies the clicked user when the URL of the electronic content is clicked.
. As a premise, each user is given an ID for using the messaging service (hereinafter referred to as "SNS ID"). The SNS ID of each user is registered in the user table TBL1.
Prior to using the system 100, each user sets up an account in the distribution management device 10 by making a so-called friend application or the like. When the account setting is performed, the user identification unit 13 gives each user an ID for using the distribution management device 10 (hereinafter referred to as “distribution ID”). The distribution ID assigned to each user is registered in the user table TBL1. In the user table TBL1, registered detailed information representing distribution ID, SNS ID, registration date and time, etc. is associated with each user and registered. Note that the timing at which the distribution ID is registered in the user table TBL1 is not limited to the above example. For example, when an unregistered user who does not use the distribution management device 10 clicks on the URL of the electronic content, the user identification unit 13 gives the unregistered user a distribution ID and registers the unregistered user in the user table TBL1. may

The user identification unit 13 identifies the user who clicked the URL of the electronic content by using the user table TBL1. For example, when the URL of the electronic content C1 is clicked by the user A shown in FIG. The user identification unit 13 searches the user table TBL1 using the SNS ID as a search key, thereby identifying the distribution ID registered in association with this SNS ID, and clicking the URL of the electronic content C1. Identify the user A who has

The click information acquisition unit (acquisition unit) 14 acquires click information of the URL of the electronic content by the user, and registers it in the click information table TBL2. The click information is access information representing a past access history to electronic content by the user. The click information includes the distribution ID of the user who clicked the URL of the electronic content, the date and time of the click indicating the access time to the electronic content, the access destination URL of the electronic content, and the like. The click information acquisition unit 14 acquires the click information of the URL of the electronic content described above by using the measurement page PM that is not displayed on the display of the user terminal 40 .

(delivery optimization device)
Delivery optimization device 20 includes learning unit 21 and delivery optimization setting unit 22 .
The learning unit 21 and the distribution optimization setting unit 22 are implemented by the CPU 1 of the distribution optimization device 20 executing various programs stored in the storage device 2 . Note that the program can be stored in a storage medium such as a USB memory or a CD-ROM.

The learning unit (extraction unit) 21 learns the past click information sequentially registered in the click information table TBL2, thereby extracting users who are likely to click the URL of the posted electronic content as distribution target users. do. For example, based on past click information, the learning unit 21 extracts, as distribution target users, users whose number of clicks on electronic content was equal to or greater than a threshold within a predetermined period. More specifically, based on the past click information, the learning unit 21 extracts users who have clicked electronic content 100 times or more in the past six months as distribution target users.

Based on the distribution setting information supplied from the distribution management device 10, the distribution optimization setting unit 22 requests the learning unit 21 to provide a list of distribution target users (that is, a distribution target user list). Specifically, the distribution optimization setting unit 22 specifies the number of distribution target users by referring to the distribution setting information. For example, when the number of distribution target users is 3000, the distribution optimization setting unit 22 requests the learning unit 21 to provide a distribution target user list for 3000 users. In response to the request, the learning unit 21 generates a distribution target user list in which 3000 distribution target users are described, and outputs the distribution target user list to the distribution optimization setting unit 22 . The distribution optimization setting unit 22 returns and sets the distribution target user list received from the learning unit 21 to the distribution management device 10 .

According to this configuration, users who are expected to have a high conversion rate (CVR) are extracted and listed as distribution target users based on past click histories regarding posted electronic content. Therefore, it is possible to distribute electronic contents more efficiently than in the past.

<Example of operations from distribution settings to distribution>
Next, while showing a specific example of a screen displayed on the distribution management device 10, a specific operation from distribution setting to distribution of electronic content will be described.

The content provider performs the work of posting the electronic content prior to setting the distribution. Specifically, a task of inputting electronic content resource information such as the title, layout, URL, and electronic data of the electronic content is performed. After completing the work of posting the electronic content, the content provider accesses the distribution management device 10 and displays an electronic content distribution setting screen on the distribution management device 10 .

FIG. 4 is a diagram exemplifying a distribution setting screen P1 for electronic content displayed on the display of the distribution management device 10. As shown in FIG.
The content provider inputs the distribution setting information such as the title of the electronic content, the distribution time of the electronic content, the number of distribution target users, and the URL of the electronic content, according to the instructions on the distribution setting screen P1. Note that instead of the number of distribution target users, an upper limit number of distribution or a range of the number of distribution target users may be set. For example, the upper limit of distribution may be set to "50000", or the range of the number of distribution target users may be set to "2000 to 4000".

FIG. 5 is a sequence diagram showing specific operations of the distribution management device 10 and the distribution optimization device 20. As shown in FIG.
The distribution setting unit 11 of the distribution management device 10 receives input of distribution setting information from the content provider (step S1), supplies the received distribution setting information to the distribution optimization device 20, and requests a distribution target user list. (step S2).

When the distribution setting information and the request for the distribution target user list are received, the distribution optimization setting unit 22 of the distribution optimization device 20 specifies the number of distribution target users included in the distribution setting information (step S3). Then, the distribution optimization setting unit 22 requests the learning unit 21 to provide a distribution target user list for the specified number of people. In response to the request, the learning unit 21 generates a distribution target user list for the specified number of users (step S4). More specifically, based on the past click information, the learning unit 21 rearranges in descending order the users whose number of electronic content clicks is equal to or greater than a threshold within a predetermined period, and extracts the users as distribution target users. Here, for example, if the number of distribution target users is 3000, the learning unit 21 generates a distribution target user list (descending order) in which the distribution IDs of the 3000 distribution target users are described. The learning unit 21 outputs the generated distribution target user list to the distribution optimization setting unit 22 .

Upon receiving the distribution target user list, the distribution optimization setting unit 22 transmits it to the distribution management device 10 (step S5). Upon receiving the distribution target user list, the distribution setting unit 11 of the distribution management device 10 identifies the distribution target users based on the distribution IDs in the received distribution target user list (step S6), and sends the electronic content to the distribution unit 12. Instruct to start distribution. Upon receiving such an instruction, the distribution unit 12 starts distributing the electronic content to the user terminals 40 of the distribution target users listed in the distribution target user list (step S7), and ends the process.

[Second embodiment]
In the first embodiment described above, a case has been described where distribution target users are optimized by extracting users who are expected to have a high CVR as distribution target users. On the other hand, in the second embodiment described below, in addition to optimization of distribution target users, optimization of distribution time is realized.
In addition, below, it demonstrates centering on a different point from 1st Example, and omits explanation about the part which is common in 1st Example.

The learning unit 21 of the distribution optimization device 20 not only identifies users who are expected to have a high CVR as distribution target users based on the distribution IDs included in the past click information, but also determines the click date and time included in the click information. By referring to , the time at which each distribution target user is likely to click is specified. As an example, one day is morning (6: 00-12: 00), noon (12: 00-18: 00), night (18: 00-23: 00), midnight (23: 00-6: 00) It is divided into four time periods (slots), and in which time slot is most likely to be clicked is grasped for each distribution target user. For example, for 1000 distribution target users, when it is found that the most clickable time zone is "midnight", the learning unit 21 of the distribution optimization device 20 generates a distribution target user list for 1000 users. At the same time, it transmits a message to the distribution management device 10 that the optimum distribution time is "midnight".

The distribution setting unit 11 of the distribution management device 10 receives from the distribution optimization device 20 a list of distribution target users for 1000 users and a message indicating that the optimum distribution time is "midnight". The distribution setting unit 11 specifies the distribution target users based on the distribution IDs in the distribution target user list received, and sends an instruction to the distribution unit 12 to distribute the electronic content at "midnight" based on the received message. . In this embodiment, since the time indicated in the optimum delivery time message is "late night", the electronic content is delivered to 1000 delivery target users who are likely to click "late night".

Thus, according to the above-described embodiment, in addition to optimizing the distribution target users, the distribution time is also optimized. Therefore, it is possible to distribute electronic content more efficiently than in the past.

In addition, in the above-described embodiment, the configuration of selecting one optimum delivery time was exemplified, but the gist is not limited to this. More than one optimal delivery time may be selected. For example, "midnight" and "midday" can be selected as optimal delivery times. Also, the distribution time may be divided according to the number of distribution target users. For example, if the number of distribution target users is set to 1000, 100, 200, 100 and 500 users will may be selected.

[Third embodiment]
In the above-described first embodiment, an example was given of optimizing distribution target users based on past click histories, but the present invention is not limited to this. The distribution target users may be optimized based on the past click history and the topic information of each article included in the posted electronic content. Here, the "topic information" is information representing the title of the article, such as "clothes mail order,""beautyequipment,""overseastravel,""hometraining," and "entertainment news."

FIG. 6 is a block diagram showing main functions of the content delivery system 100a according to the third embodiment. 6, parts corresponding to those of the content distribution system 100 shown in FIG. 3 are denoted by the same reference numerals, and detailed description thereof will be omitted.

3 and 6, the content distribution system 100a differs from the content distribution system 100 shown in FIG.
A content analysis device (analysis unit) 50 is realized by, for example, a server computer, and analyzes various electronic contents.

More specifically, when the content analysis device 50 receives the URL of each article forming the electronic content from the distribution setting unit 11 of the distribution management device 10, it accesses each article and analyzes the content of the article by natural language processing or the like. . The content analysis device 50 extracts the topic information of each article based on the analysis result, and calculates the score of the topic information. As an example, when the content analysis device 50 receives the URLs of four articles from the distribution setting unit 11, for example, it extracts a plurality of pieces of topic information for each of these four articles, and extracts the extracted topic information. Calculate the score of each and sort them in descending order of the score.

FIG. 7 is a diagram illustrating the configuration of electronic content EC according to the third embodiment.
In the example shown in FIG. 7, the electronic content EC includes four articles A1 to A4. Each of the articles A1 to A4 includes a title of the article, a URL indicating the location of the article, and a plurality (three in FIG. 7) of topic information with different scores. To give an example, the title of the article A1 is "clothing mail order", and the article A1 includes topic information such as "fast fashion", "spring coordination", and "spring sale" in descending order of score. be

The content analysis device 50 extracts topic information with the highest score for each article, and outputs it to the distribution setting unit 11 of the distribution management device 10 . For example, for the article A1 shown in FIG. 7, the topic information “fast fashion” with the highest score is extracted and output to the distribution setting unit 11 of the distribution management device 10. FIG.
When the distribution setting unit 11 receives the topic information with the highest score for each article, the distribution setting unit 11 includes the received topic information in the distribution setting information and transmits the distribution setting information to the distribution optimization device 20 .
Further, the distribution setting unit 11 transmits the electronic content posted by the content provider CP to the distribution unit 12, including the topic information of each article. As a result, the electronic content distributed from the distribution unit 12 includes the topic information of each article.

On the other hand, when a certain user clicks on the URL of any article included in the electronic content, the user specifying unit 13 uses the user table TBL1 to click on the article (hereinafter referred to as "specific article"). Identify users.
The click information acquisition unit 14 acquires the click information of the URL of the specific article by the user and registers it in the click information table TBL2. In this case, the click information of the URL of the specific article includes the distribution ID of the user, the date and time of the click, the access destination URL of the specific article, topic information of the specific article, and the like.

The learning unit 21 of the delivery optimization device 20 learns past click information sequentially registered in the click information table TBL2. Since the click information includes the topic information of the specific article, the learning unit 21 can find out the tendency of which user prefers to view (click) articles of what topics. .

The distribution optimization setting unit 22 specifies the number of distribution target users based on the distribution setting information supplied from the distribution management device 10, and requests the learning unit 21 to provide a distribution target user list for the specified number of users. As described above, the distribution setting information includes the topic information of each article included in the electronic content. The learning unit 21 is requested to extract the user as a distribution target user.

In response to such a request, the learning unit 21 extracts the specified number of users who are likely to be interested in the topic information of each article included in the electronic content, and generates a distribution target user list. The learning unit 21 then returns the generated distribution target user list to the distribution optimization setting unit 22 .

Upon receiving the distribution target user list, the distribution optimization setting unit 22 transmits it to the distribution management device 10 . It should be noted that subsequent operations can be described in the same manner as in the other embodiments described above, and therefore are omitted.

According to the above-described embodiment, users who are expected to have a high CVR are selected as distribution target users based on the topic information of each article included in the posted electronic content as well as the past click history regarding the posted electronic content. Extract and list. Therefore, it is possible to distribute electronic content more efficiently than in the past.

In the above example, the electronic content to be distributed includes four articles, but the number of articles included in the electronic content may be one or more. In the above example, topic information with the highest score is output to the distribution management device 10 for each article, but topic information with the second highest score may be output to the distribution management device 10, for example.

[Fourth embodiment]
In the third embodiment described above, distribution target users are optimized based not only on the past click history but also on the topic information of articles included in posted electronic content. Optimize your content.
Here, since the main functions of the content distribution system 100a according to the fourth embodiment are the same as those of the content distribution system 100a according to the third embodiment shown in FIG. 6, illustration and description are omitted.

FIG. 8 is a diagram illustrating the configuration of electronic content EC according to the fourth embodiment.
As shown in A of FIG. 8, the distributed electronic content EC includes six types of articles: "Clothing mail order", "Rough skin", "Recommended lips", "Home yoga", "Overseas travel", and "Comedy live". It is composed of A1 to A6.

Here, the learning unit 21 extracts users who are expected to have a high CVR as distribution target users based on past click histories and topic information of articles included in posted electronic content, and lists them as described above. This is the same as the third embodiment.
However, the learning unit 21 according to the fourth embodiment customizes electronic content including articles of topic information showing high interest for each distribution target user registered in the distribution target user list, which is different from that of the third embodiment. different from

In the learning unit 21, when a distribution target list is generated in the same manner as in the third embodiment, by referring to the click information table TBL2, articles of topic information likely to be of interest are extracted for each distribution target user, and extracted. Customize electronic content to include specific topical information.
For example, as shown in FIG. 8B, for user A, the electronic content EC is customized to include four articles: "clothes mail order", "skin irritation", "recommended lips", and "comedy live" (see FIG. 8B). 8 B), and for user B, the electronic content EC is customized to include four articles: "clothing mail order", "home yoga", "overseas travel", and "comedy live" (see FIG. 8 C). ), and so on.

After customizing the electronic content EC for each distribution target user in this manner, the learning unit 21 transmits the customized electronic content EC to the distribution management apparatus 10 together with the generated distribution target user list. The distribution unit 12 of the distribution management device 10 distributes the customized electronic content EC to each distribution target user registered in the distribution target user list.

According to the above-described embodiment, the electronic content is distributed after customizing the electronic content so as to include an article of topic information showing high interest for each distribution target user. Therefore, it is possible to distribute electronic content more efficiently than in the past.

B. Others In each of the above-described embodiments, the term "unit" does not simply mean physical means, but also includes the case where the functions of the "unit" are implemented by software. In addition, even if the function of one "section" or device is realized by two or more physical means or devices, the functions of two or more "sections" or devices are realized by one physical means or device. can be

100, 100a Content distribution system 10 Distribution management device 11 Distribution setting unit 12 Distribution unit 13 User identification unit 14 Click information acquisition unit 15 Storage unit 20 Distribution optimization device 21... Learning unit 22... Distribution optimization setting unit 30... SNS providing device 40... User terminal 50... Content analysis device TBL1... User table TBL2... Click information table TBL3... Score table

Claims (5)

A system for distributing electronic content composed of a plurality of articles to a user using a messaging service,
an acquisition unit that acquires access information representing access history to each article included in past electronic content by each user;
a setting unit that receives settings for at least the number of distribution targets for electronic content composed of a plurality of articles newly posted by a content provider using the messaging service ;
Based on the access information according to the set number of distribution target users, users who have accessed articles included in the past electronic content in large numbers are extracted as distribution target users, and the access information is extracted. an extracting unit that identifies an optimal distribution time at which the distribution target user is likely to click, based on the click information included in the
a distribution unit that distributes the newly posted electronic content composed of a plurality of articles to the extracted distribution target users, using the messaging service;
the access information includes topic information included in past articles accessed in the past by each of the users;
further comprising an analysis unit that identifies topic information for each of a plurality of new articles included in the newly posted electronic content by analyzing the newly posted electronic content;
The analysis unit extracts a plurality of pieces of topic information for each of the new articles, calculates a score for each of the extracted topic information, and selects topic information with the highest score as a topic for each of the new articles. identified as information,
The extracting unit extracts the topic information of the past article accessed in the past included in the access information and the new plurality of articles included in the newly posted electronic content according to the number of distribution target persons. extracting the distribution target users based on the topic information of the article,
The distribution unit distributes the newly posted electronic content composed of the plurality of new articles to the extracted distribution target users at the optimal distribution time using the messaging service. A content distribution system that distributes topic information for each of multiple articles . The extraction unit extracts based on the topic information of the past article accessed in the past included in the access information and the topic information of the new article included in the newly posted electronic content. A plurality of new articles of topic information likely to be of interest are extracted from the plurality of new articles included in the newly posted electronic content for each distribution target user, and the plurality of extracted new articles are extracted. customizing said newly posted electronic content to include relevant articles;
2. The content according to claim 1, wherein said distribution unit distributes said newly posted customized electronic content at said optimum distribution time using said messaging service for each of said extracted distribution target users. delivery system. A device for distributing electronic content composed of a plurality of articles to a user using a messaging service,
an acquisition unit that acquires access information representing access history to each article included in past electronic content by each user;
a setting unit that receives settings for at least the number of distribution targets for electronic content composed of a plurality of articles newly posted by a content provider using the messaging service ;
Based on the access information according to the set number of distribution target users, users who have accessed articles included in the past electronic content in large numbers are extracted as distribution target users, and the access information is extracted. an extracting unit that identifies an optimal distribution time at which the distribution target user is likely to click, based on the click information included in the
a distribution unit that distributes the newly posted electronic content composed of a plurality of articles to the extracted distribution target users , using the messaging service ;
the access information includes topic information included in past articles accessed in the past by each of the users;
further comprising an analysis unit that identifies topic information for each of a plurality of new articles included in the newly posted electronic content by analyzing the newly posted electronic content;
The analysis unit extracts a plurality of pieces of topic information for each of the new articles, calculates a score for each of the extracted topic information, and selects topic information with the highest score as a topic for each of the new articles. identified as information,
The extracting unit extracts the topic information of the past article accessed in the past included in the access information and the new plurality of articles included in the newly posted electronic content according to the number of distribution target persons. extracting the distribution target users based on the topic information of the article,
The distribution unit distributes the newly posted electronic content composed of the plurality of new articles to the extracted distribution target users at the optimal distribution time using the messaging service. A distribution device that distributes topic information for each of a plurality of articles . A method for distributing electronic content composed of a plurality of articles to a user using a messaging service, comprising:
an acquisition step of acquiring access information representing access history to each article included in past electronic content by each user;
a setting step of receiving settings for at least the number of distribution targets for electronic content composed of a plurality of articles newly posted by a content provider using the messaging service ;
Based on the access information according to the set number of distribution target users, users who have accessed articles included in the past electronic content in large numbers are extracted as distribution target users, and the access information is extracted. an extracting step of identifying an optimal distribution time at which the distribution target user is likely to click, based on the click information included in the
a distribution step of distributing the newly posted electronic content composed of a plurality of articles to the extracted distribution target users using the messaging service;
the access information includes topic information included in past articles accessed in the past by each of the users;
further comprising an analysis step of identifying topic information for each of a plurality of new articles included in the newly posted electronic content by analyzing the newly posted electronic content;
In the analyzing step, a plurality of pieces of topic information are extracted for each of the new articles, a score is calculated for each of the extracted topic information, and topic information with the highest score is selected for each of the new articles. identified as topical information,
In the extracting step, topic information of the past article accessed in the past included in the access information and the new topic information included in the newly posted electronic content are selected according to the number of distribution target persons. Extracting the distribution target users based on topic information of a plurality of articles,
In the distributing step, the newly posted electronic content composed of the plurality of new articles is sent to the extracted distribution target users at the optimal distribution time using the messaging service , A distribution method for distributing including topic information of each of the plurality of articles . a computer that delivers electronic content consisting of multiple articles to a user using a messaging service;
an acquisition step of acquiring access information representing access history to each article included in past electronic content by each user;
a setting step of receiving settings for at least the number of distribution targets for electronic content composed of a plurality of articles newly posted by a content provider using the messaging service ;
Based on the access information according to the set number of distribution target users, users who have accessed articles included in the past electronic content in large numbers are extracted as distribution target users, and the access information is extracted. an extracting step of identifying an optimal distribution time at which the distribution target user is likely to click, based on the click information included in the
executing a distribution step of distributing the newly posted electronic content composed of a plurality of articles to the extracted distribution target users using the messaging service;
the access information includes topic information included in past articles accessed in the past by each of the users;
further executing an analysis step of identifying topic information for each of a plurality of new articles included in the newly posted electronic content by analyzing the newly posted electronic content;
In the analyzing step, a plurality of pieces of topic information are extracted for each of the new articles, a score is calculated for each of the extracted topic information, and topic information with the highest score is selected for each of the new articles. identified as topical information,
In the extracting step, topic information of the past article accessed in the past included in the access information and the new topic information included in the newly posted electronic content are selected according to the number of distribution target persons. Extracting the distribution target users based on topic information of a plurality of articles,
In the distributing step, the newly posted electronic content composed of the plurality of new articles is sent to the extracted distribution target users at the optimal distribution time using the messaging service , A program for distributing including topic information of each of the plurality of articles .

Images