KR20230174089A - Server, method and computer program for recommending content title and thumbnail - Google Patents

Abstract

The recommendation server is a channel that receives information on a plurality of content provision channels from the user terminal, analyzes content posted on the plurality of content provision channels, and extracts a first content list including a plurality of content that meets the first condition. a reader, and a plurality of contents including content titles and thumbnails for growing the user's content provision channel among the content presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel. 2 Includes title and thumbnail recommendations that extract the content list.

Description

Recommendation server, recommendation method, and computer program for recommending content titles and thumbnails {SERVER, METHOD AND COMPUTER PROGRAM FOR RECOMMENDING CONTENT TITLE AND THUMBNAIL}

The present invention relates to a recommendation server, recommendation method, and computer program that recommend content titles and thumbnails to grow a user's content provision channel.

Various types of content are produced and consumed through social network services (SNS). For example, users can view various types of content through ‘YouTube,’ and content creators can earn advertising revenue based on the number of subscriptions to the content. The market for social network services that provide content, such as 'YouTube', is growing every year.

However, content creators are having difficulty producing new content every time due to rapid changes in trends.

In order to grow users' content provision channels, we aim to provide a recommendation server, recommendation method, and computer program that recommends content titles and thumbnails.

However, the technical challenges that this embodiment aims to achieve are not limited to the technical challenges described above, and other technical challenges may exist.

As a means to achieve the above-described technical problem, an embodiment of the present invention receives information on a plurality of content provision channels from a user terminal, analyzes the content posted on the plurality of content provision channels, and satisfies the first condition. a channel reading unit for extracting a first content list including a plurality of matching contents, and growing the user's content provision channel among the contents presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel; A recommendation server that includes a title and thumbnail recommendation unit that extracts a second content list including a plurality of content including content titles and thumbnails to be recommended can be provided.

Another embodiment of the present invention includes receiving information on a plurality of content provision channels from a user terminal, analyzing content posted on the plurality of content provision channels, and including a plurality of content that satisfies a first condition. Extracting a content list, and a plurality of contents including content titles and thumbnails for growing the user's content provision channel among the content presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel. It is possible to provide a recommendation method that includes the step of extracting a second content list including.

In another embodiment of the present invention, when executed by a computing device, the computer program receives information on a plurality of content provision channels from the user terminal, analyzes the content posted on the plurality of content provision channels, and satisfies the first condition. A content title for extracting a first content list including a plurality of matching content, and growing the user's content provision channel among the content presented in the plurality of content provision channels based on the viewing tendency of the user's content provision channel. and a sequence of instructions for extracting a second content list including a plurality of content including thumbnails.

The above-described means for solving the problem are merely illustrative and should not be construed as limiting the present invention. In addition to the exemplary embodiments described above, there may be additional embodiments described in the drawings and detailed description of the invention.

According to one of the means for solving the problems of the present invention described above, it is possible to help grow a user's content provision channel by recommending content titles and thumbnails based on the user's viewing tendency of the content provision channel.

1 is a diagram schematically showing a recommendation system according to an embodiment of the present invention.
Figure 2 is a configuration diagram of a recommendation server according to an embodiment of the present invention.
3A and 3B are diagrams illustrating an example of a method for extracting a first content list according to an embodiment of the present invention.
Figure 4 is a diagram illustrating an example of a user channel registration screen according to an embodiment of the present invention.
Figure 5 is a diagram illustrating an example of a view count prediction screen according to an embodiment of the present invention.
Figure 6 is a diagram illustrating an example of a trend analysis screen according to an embodiment of the present invention.
Figure 7 is a flowchart of a recommendation method in which a recommendation server recommends content titles and thumbnails to grow a user's content provision channel according to an embodiment of the present invention.

Below, with reference to the attached drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. In order to clearly explain the present invention in the drawings, parts that are not related to the description are omitted, and similar parts are given similar reference numerals throughout the specification.

Throughout the specification, when a part is said to be "connected" to another part, this includes not only the case where it is "directly connected," but also the case where it is "electrically connected" with another element in between. . In addition, when a part is said to "include" a certain component, this does not mean excluding other components unless specifically stated to the contrary, but may further include other components, and one or more other features. It should be understood that it does not exclude in advance the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

In this specification, 'part' includes a unit realized by hardware, a unit realized by software, and a unit realized using both. Additionally, one unit may be realized using two or more pieces of hardware, and two or more units may be realized using one piece of hardware.

In this specification, some of the operations or functions described as being performed by a terminal or device may instead be performed on a server connected to the terminal or device. Likewise, some of the operations or functions described as being performed by the server may also be performed on a terminal or device connected to the server.

Hereinafter, an embodiment of the present invention will be described in detail with reference to the attached drawings.

1 is a diagram schematically showing a recommendation system according to an embodiment of the present invention.

Referring to FIG. 1, a recommendation system according to an embodiment of the present invention may include a user terminal 100 and a recommendation server 200. The user terminal 100 and recommendation server 200 shown in FIG. 1 exemplarily illustrate components that can be controlled by a recommendation system.

Each component of the recommendation system in Figure 1 may generally be connected through a network. For example, a network refers to a connection structure that allows information exchange between nodes such as terminals and servers, including a local area network (LAN), a wide area network (WAN), and the Internet. (WWW: World Wide Web), wired and wireless data communication network, telephone network, wired and wireless television communication network, etc. Examples of wireless data communication networks include 3G, 4G, 5G, 3GPP (3rd Generation Partnership Project), LTE (Long Term Evolution), WIMAX (World Interoperability for Microwave Access), Wi-Fi, Bluetooth communication, infrared communication, and ultrasound. This includes, but is not limited to, communication, Visible Light Communication (VLC), LiFi, etc.

The user terminal 100 may include, for example, a laptop or desktop PC as well as a mobile terminal capable of wired or wireless communication. A mobile terminal is a wireless communication device that guarantees portability and mobility, and includes not only smartphones, tablet PCs, and wearable devices, but also Bluetooth (BLE, Bluetooth Low Energy), NFC, RFID, ultrasonic, infrared, and Wi-Fi ( It may include various devices equipped with communication modules such as WiFi) and LiFi. However, the user terminal 100 is not limited to those illustrated above.

The user terminal 100 can access the recommendation server 200 and receive a recommendation service provided by the recommendation server 200. Here, the user may own a content provision channel. Additionally, the content provision channel may mean, for example, a personal channel on a platform such as 'YouTube'.

The recommendation server 200 may be a server that recommends content titles and thumbnails to grow the user's content provision channel.

The recommendation server 200 receives information on a plurality of content provision channels from the user terminal 100, analyzes content posted on the plurality of content provision channels, and provides first content including a plurality of content that meets the first condition. You can extract a list.

The recommendation server 200 is a second server that includes a plurality of content including content titles and thumbnails for growing the user's content provision channel among the content presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel. A content list can be extracted.

According to the recommendation system according to an embodiment of the present invention, it can help to rapidly grow the user's content provision channel by recommending content titles and thumbnails based on the user's viewing tendency of the content provision channel.

Figure 2 is a configuration diagram of a recommendation server according to an embodiment of the present invention.

Referring to FIG. 2, the recommendation server 200 according to an embodiment of the present invention includes a channel reading unit 210, a title and thumbnail recommendation unit 230, a view count prediction unit 250, and a trend analysis unit 270. It can be included. However, the recommendation server 200 in FIG. 2 is only one implementation example of the present invention, and various modifications are possible based on the components shown in FIG. 2.

Hereinafter, FIG. 2 will be described with reference to FIGS. 3 to 6.

The channel reading unit 210 receives information on a plurality of content provision channels from the user terminal 100, analyzes the content posted on the plurality of content provision channels, and generates a first message containing a plurality of content that meets the first condition. A content list can be extracted.

Here, the information on the content provision channel may be a URL (Uniform Resource Locator).

Additionally, the first condition may be a condition of having a higher number of views than the average number of views among content posted on a plurality of content providing channels. Hereinafter, the channel reading unit 210 will be described in detail using FIGS. 3A and 3B.

3A and 3B are diagrams illustrating an example of a method for extracting a first content list according to an embodiment of the present invention.

Referring to FIG. 3A, the channel reading unit 210 may provide a reading channel information registration/analysis screen 310 to the user terminal 100. For example, when the user terminal 100 requests registration of read channel information to read a plurality of content providing channels, the channel reading unit 210 displays the read channel information registration/analysis screen 310 to the user terminal 100. It can be provided as .

The channel reading unit 210 may receive information on a plurality of content providing channels from the user terminal 100. That is, the user inputs the URL address of the content providing channel that the user wants to read into the channel information input interface 311 through the user terminal 100 and clicks on the channel registration interface 313 to create a plurality of content providing channels to be read. can be registered.

Additionally, the channel reading unit 210 may receive an input period for the posting date of content posted on a plurality of content providing channels from the user terminal 100. For example, the channel reading unit 210 may receive input of a start date and an end date.

When the analysis start button 315 is selected from the user terminal 100 and a channel analysis request is received, the channel reader 210 can analyze content posted on a plurality of content providing channels registered for the corresponding period.

Referring to FIG. 3b, when receiving a channel analysis request from the user terminal 100, the channel reading unit 210 analyzes the content posted on a plurality of content providing channels and provides a plurality of content that meets the first condition. After extracting the first content list, a channel reading result screen 320 including the first content list can be provided to the user terminal 100.

The channel read result screen 320 may display a first content list with a higher number of views than the average number of views. For example, if the average number of channel views for all content posted on the first channel is 50, the channel reading unit 210 may output content with more than 50 views among all content posted on the first channel.

Additionally, the channel reading unit 210 may provide an interface that can sort the extracted first content list in latest or most popular order.

Returning to FIG. 2, the title and thumbnail recommendation unit 230 selects a content title and thumbnail for growing the user's content provision channel among the content presented in a plurality of content provision channels based on the user's viewing tendency of the content provision channel. A second content list containing a plurality of contents may be extracted.

In one embodiment, the title and thumbnail recommendation unit 230 receives information on the user's content provision channel from the user terminal 100 and watches the user's content provision channel based on the input information on the user's content provision channel. You can analyze your tendencies. Hereinafter, the title and thumbnail recommendation unit 230 will be described in detail using FIG. 4.

Figure 4 is a diagram illustrating an example of a user channel registration screen according to an embodiment of the present invention.

Referring to FIG. 4 , the title and thumbnail recommendation unit 230 may provide a user channel registration screen 400 to the user terminal 100 .

The title and thumbnail recommendation unit 230 receives information (e.g., URL) about the user's content provision channel from the user terminal 100 through the channel information input interface 401, and when the registration interface 413 is clicked, the user You can register content provision channels.

The title and thumbnail recommendation unit 230 may analyze the viewing tendency of the user's content provision channel based on information about the user's content provision channel. Here, the user's viewing tendency of the content providing channel may include at least one of gender ratio, age group, exposure amount, click-through rate, and viewing duration. The user's viewing tendency of the content providing channel may be directly input from the user terminal 100.

Returning to FIG. 2, the number of views prediction unit 250 uses the content title and thumbnail of each of the plurality of contents included in the second content list to predict the number of views and profit expected when posting the content on the user's content provision channel. It is predictable. Hereinafter, the view count prediction unit 250 will be described in detail using FIG. 5.

Figure 5 is a diagram illustrating an example of a view count prediction screen according to an embodiment of the present invention.

Referring to FIG. 5 , the view count prediction unit 250 may provide a view count prediction screen 500 to the user terminal 100 . Specifically, when the user terminal 100 selects one content from the second content list, the content title and thumbnail of the selected content are used to post the content on the user's content provision channel, including the expected number of views and profits. The number of views prediction screen 500 can be provided to the user terminal 100.

Here, in the first area 501, content selected from the user terminal 100 may be implemented as a player.

Additionally, the second area 503 may display information on the content providing channel where the selected content is posted. Here, the channel information may include the channel name, number of subscribers, number of content posted on the channel, cumulative number of views of all content posted on the channel, and open date of the channel.

The third area 505 may include the expected number of views, expected content profit, and expected number of views on my channel when posting the content to the user's content provision channel using the content title and thumbnail of the selected content.

Returning to FIG. 2 , the trend analysis unit 270 may provide a plurality of contents related to the keyword input from the user terminal 100 according to the second condition. Here, the second condition may be at least one of the number of views, publisher, posting date, and posting platform. Hereinafter, the trend analysis unit 270 will be described in detail using FIG. 6.

Figure 6 is a diagram illustrating an example of a trend analysis screen according to an embodiment of the present invention.

Referring to FIG. 6 , the trend analysis unit 270 may provide a trend analysis screen 600 to the user terminal 100 . Specifically, when the trend analysis unit 270 receives a keyword from the user terminal 100 through the keyword input interface 601, it displays a trend analysis screen 600 containing a plurality of contents 603 related to the input keyword. can be provided.

Here, the trend analysis unit 270 may provide a plurality of contents 603 according to at least one condition among the number of views, publisher, posting date, and posting platform. For example, the trend analysis unit 270 may display a plurality of contents 603 in order of highest number of views through the trend analysis screen 600 as shown in FIG. 5 . Additionally, the publishing platform may include various communities such as 'YouTube' and 'Naver'.

Figure 7 is a flowchart of a recommendation method in which a recommendation server recommends content titles and thumbnails to grow a user's content provision channel according to an embodiment of the present invention. The recommendation method for recommending content titles and thumbnails to grow the user's content provision channel in the recommendation server 200 shown in FIG. 7 includes steps processed in time series according to the embodiments shown in FIGS. 1 to 6. do. Therefore, even if the content is omitted below, it is also applied to the recommendation method in which the recommendation server 200 recommends content titles and thumbnails to grow the user's content provision channel according to the embodiment shown in FIGS. 1 to 6.

In step S710, the recommendation server 200 may receive information on a plurality of content provision channels from the user terminal 100.

In step S730, the recommendation server 200 may analyze content posted on a plurality of content providing channels and extract a first content list including a plurality of content that meets the first condition.

In step S750, the recommendation server 200 includes a plurality of contents including content titles and thumbnails for growing the user's content provision channel among the content presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel. The second content list can be extracted.

In the above description, steps S710 to S750 may be further divided into additional steps or combined into fewer steps, depending on the implementation of the present invention. Additionally, some steps may be omitted or the order between steps may be switched as needed.

The recommendation method of recommending content titles and thumbnails to grow the user's content provision channel in the recommendation server 200 described with reference to FIGS. 1 to 7 is a computer program stored on a medium executed by a computer or a computer program executable by a computer. It can also be implemented in the form of a recording medium containing instructions. In addition, the recommendation method of recommending content titles and thumbnails to grow the user's content provision channel in the recommendation server 200 described with reference to FIGS. 1 to 6 may also be in the form of a computer program stored in a medium executed by a computer. It can be implemented.

Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and non-volatile media, removable and non-removable media. Additionally, computer-readable media may include computer storage media. Computer storage media includes both volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data.

The description of the present invention described above is for illustrative purposes, and those skilled in the art will understand that the present invention can be easily modified into other specific forms without changing the technical idea or essential features of the present invention. will be. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive. For example, each component described as unitary may be implemented in a distributed manner, and similarly, components described as distributed may also be implemented in a combined form.

The scope of the present invention is indicated by the claims described below rather than the detailed description above, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention. do.

100: user terminal
200: Recommended server
210: Channel reading unit
230: Title and thumbnail recommendation section
250: View count prediction unit
270: Trend analysis department

Claims (13)

In the recommendation server that recommends content titles and thumbnails to grow the user's content provision channel,
a channel reading unit that receives information on a plurality of content provision channels from a user terminal, analyzes content posted on the plurality of content provision channels, and extracts a first content list including a plurality of content that meets a first condition; and
A second content list including a plurality of content including content titles and thumbnails for growing the user's content provision channel among the content presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel. Extracted title and thumbnail recommendations
A recommended server that includes.
According to claim 1,
A recommendation server wherein the information on the content provision channel is a URL (Uniform Resource Locator).
According to claim 1,
The first condition is a condition of having a higher number of views than the average number of views among the content posted on the plurality of content providing channels.
According to claim 1,
A view prediction unit that predicts the expected number of views and profits when posting content on the user's content provision channel using the content title and thumbnail of each of the plurality of content included in the second content list.
A recommended server that includes.
According to claim 1,
A trend analysis unit that provides a plurality of contents related to the keyword input from the user terminal according to a second condition.
A recommended server that further includes.
According to claim 5,
A recommendation server wherein the second condition is at least one of the number of views, publisher, posting date, and posting platform.
In the recommendation method of recommending content titles and thumbnails to grow the user's content provision channel,
Receiving information on a plurality of content provision channels from a user terminal;
extracting a first content list including a plurality of content satisfying a first condition by analyzing content posted on the plurality of content providing channels; and
A second content list including a plurality of content including content titles and thumbnails for growing the user's content provision channel among the content presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel. Extraction steps
A recommended method comprising:
According to claim 7,
A recommendation method wherein the information on the content provision channel is a URL (Uniform Resource Locator).
According to claim 8,
The first condition is a condition of having a higher number of views than the average number of views among the content posted on the plurality of content providing channels.
According to claim 7,
Predicting the expected number of views and profits when posting content on the user's content provision channel using the content title and thumbnail of each of the plurality of content included in the second content list
A recommended method further comprising:
According to claim 7,
Providing a plurality of contents related to a keyword input from the user terminal according to a second condition
A recommended method further comprising:
According to claim 11,
A recommendation method wherein the second condition is at least one of the number of views, publisher, posting date, and posting platform.
A computer program stored on a computer-readable recording medium comprising a sequence of instructions for recommending content titles and thumbnails to grow a user's content provision channel, comprising:
When the computer program is executed by a computing device,
Receive information on multiple content provision channels from the user terminal,
Analyzing the content posted on the plurality of content provision channels to extract a first content list including a plurality of content that meets the first condition,
A second content list including a plurality of content including content titles and thumbnails for growing the user's content provision channel among the content presented in the plurality of content provision channels based on the user's viewing tendency of the content provision channel. A computer program stored on a computer-readable recording medium containing a sequence of instructions for extracting.