KR102660966B1 - System providing learning-related contetn - Google Patents

Abstract

A control method of an electronic device according to an embodiment of the present invention includes providing the selected video content to the user's terminal in response to a user's request for selecting at least one video content among a plurality of video content, the video content being provided If so, it may include selecting advertising content that matches at least one of the user's age and study subjects, and providing the selected advertising content to the user's terminal.

Description

A system that provides learning-related content { SYSTEM PROVIDING LEARNING-RELATED CONTETN }

The present invention relates to a technology for providing video content on a video service platform while also selecting and providing advertising content suitable for viewers of the video content.

Recently, the utilization of platforms that provide video services has increased, and more and more people are performing search functions on traditional portal sites through platforms that provide video services. Most platforms that provide these video services generate revenue through advertising, and as user usage of video platforms increases, the size of the advertising market on these video platforms is also increasing.

However, in the conventional video platform, advertisements related to the video content being played are provided in batches regardless of the viewer's tendencies or interests, which reduces the effectiveness of the advertisements.

Republic of Korea Patent Publication No. 10-2022-0151459 (Method and device for providing video-based advertising platform service)

The present invention can select and provide advertisements suitable for viewers of the video content in the process of servicing the video content.

The objects of the present disclosure are not limited to the purposes mentioned above, and other objects and advantages of the present disclosure that are not mentioned can be understood by the following description and will be more clearly understood by the examples of the present disclosure. Additionally, it will be readily apparent that the objects and advantages of the present disclosure can be realized by the means and combinations thereof indicated in the patent claims.

A control method of an electronic device according to an embodiment of the present invention includes providing the selected video content to the user's terminal in response to a user's request for selecting at least one video content among a plurality of video content, the video content being provided If so, it may include selecting advertising content that matches at least one of the user's age and study subjects, and providing the selected advertising content to the user's terminal.

At this time, the providing step includes specifying a label for the plurality of video contents, receiving a search request for the video content from the user, and providing the video content corresponding to the user's request with the name of the video content and It may include matching based on the label and presenting at least one matched video content.

Among them, the step of specifying the label includes extracting at least one image from among a plurality of images constituting the video content or extracting at least one text from among the text of the subtitles stored in connection with the video content. It may have features that are performed.

Additionally, the providing step may include the step of processing video content that requires an influx of viewers to create advertising content. In addition, the step of generating the advertising content may be characterized by performing at least one of changing the playback speed of the video content and dividing the video content into preset time units.

And the step of selecting advertising content according to an embodiment of the present invention is characterized by selecting advertising content matching the user's characteristics, where the user's characteristics include the user's age, the user's study subjects, and the user's previous history. It may include at least one of a list of watched videos, the user's intensive viewing time, and the user's interest category.

Additionally, selecting the advertising content may include selecting a frequency of providing the advertising content. The step of selecting the frequency of providing the advertising content may be characterized in that the user's intensive viewing time for the lecture video among the video content is calculated, and the frequency of providing the advertising content is reduced as the user's intensive viewing time increases. there is.

In addition, the step of selecting the advertising content calculates the user's expected learning level based on the user's intensive viewing time and the user's participation in the lecture video among the video content, and corresponds to the user's expected learning level. Thus, it can be characterized by matching advertising content that matches the learning level of the target.

The present invention selects and provides appropriate advertisements in consideration of the viewer's learning state of video content, thereby providing advertisements that meet the user's needs, thereby increasing the user's interest in the advertisement.

1 is a diagram illustrating the configuration of a system including an electronic device according to an embodiment of the present invention.
Figure 2 is a diagram showing the configuration of a server, an electronic device according to an embodiment of the present invention.
Figure 3 is a diagram showing the configuration of a content provider according to an embodiment of the present invention.
Figure 4 is a diagram showing the configuration of an advertisement selection unit according to an embodiment of the present invention.
Figure 5 is a flowchart showing the sequence of a content provision operation performed by an electronic device (server) according to an embodiment of the present invention.

The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. The present embodiments are merely provided to ensure that the disclosure of the present invention is complete and to provide a general understanding of the technical field to which the present invention pertains. It is provided to fully inform the skilled person of the scope of the present invention, and the present invention is only defined by the scope of the claims.

The terminology used herein is for describing embodiments and is not intended to limit the invention. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context. As used in the specification, “comprises” and/or “comprising” does not exclude the presence or addition of one or more other elements in addition to the mentioned elements. Like reference numerals refer to like elements throughout the specification, and “and/or” includes each and every combination of one or more of the referenced elements. Although “first”, “second”, etc. are used to describe various components, these components are of course not limited by these terms. These terms are merely used to distinguish one component from another. Therefore, it goes without saying that the first component mentioned below may also be a second component within the technical spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings commonly understood by those skilled in the art to which the present invention pertains. Additionally, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless clearly specifically defined.

As used in the specification, the term “unit” or “module” refers to a hardware component such as software, FPGA, or ASIC, and the “unit” or “module” performs certain roles. However, “part” or “module” is not limited to software or hardware. A “unit” or “module” may be configured to reside on an addressable storage medium and may be configured to run on one or more processors. Thus, as an example, a “part” or “module” refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, Includes procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functionality provided within components and “parts” or “modules” can be combined into smaller components and “parts” or “modules” or into additional components and “parts” or “modules”. Could be further separated.

Spatially relative terms such as “below”, “beneath”, “lower”, “above”, “upper”, etc. are used as a single term as shown in the drawing. It can be used to easily describe the correlation between a component and other components. Spatially relative terms should be understood as terms that include different directions of components during use or operation in addition to the directions shown in the drawings. For example, if a component shown in a drawing is flipped over, a component described as "below" or "beneath" another component will be placed "above" the other component. You can. Accordingly, the illustrative term “down” may include both downward and upward directions. Components can also be oriented in other directions, so spatially relative terms can be interpreted according to orientation.

Hereinafter, embodiments of the present invention will be described with reference to the attached drawings.

1 is a diagram illustrating the configuration of a system including an electronic device according to an embodiment of the present invention.

An electronic device according to an embodiment of the present invention may refer to the server 100 shown in FIG. 1. Additionally, the electronic device may refer to a user terminal 200 that is linked with the server 100 and performs an operation supported by the server 100.

As shown in FIG. 1, the system may be configured to include a server 100, a user terminal 200, and an advertisement providing terminal 300.

Additionally, the server 100 according to an embodiment of the present invention can communicate with a plurality of user terminals 200 and perform operations of receiving and transmitting video content to and from the user terminals 200. For example, the server 100 may acquire video content from one user terminal 200 and deliver the acquired video content to another user terminal 200. Additionally, according to various embodiments, the server 100 may support a communication environment in which video content is transmitted from a first user terminal to a second user terminal by matching a plurality of user terminals 200. Accordingly, the user terminal 200 connected to the server 100 can search for and select video content corresponding to the user's request, and receive the selected video content with the support of the server 100.

Additionally, according to various embodiments, when providing video content to the user terminal 200, the server 100 may also provide advertising content corresponding to user characteristics to the user terminal 200.

In order to perform such an advertisement provision operation, the server 100 may acquire advertisement content from the advertisement provision terminal 300, which is an external device, through communication with the advertisement provision terminal 300.

In addition, the server 100 can classify the advertising content obtained from the advertising providing terminal 300 according to items and select advertising content corresponding to the user's characteristics. Accordingly, when the server 100 receives a request for provision of video content from the user, it can not only provide the video content, but also provide advertising content pre-selected according to the user's characteristics.

A more detailed description of the server 100 will be described in more detail with reference to FIGS. 2 to 4.

Figure 2 is a diagram showing the configuration of a server, an electronic device according to an embodiment of the present invention.

As shown in FIG. 2, the server 100 according to an embodiment of the present invention may be configured to include a processor 110, a memory 120, and a communication unit 130. And the processor 110 may be configured to include a content providing unit 140 and an advertisement selection unit 150.

Before explaining the processor 110, the memory 120 and the communication unit 130 will be described.

The memory 120 may store the video content and the advertising content obtained through an external device such as the user terminal 200.

The communication unit 130 may transmit and receive the video content and the advertising content with an external device such as the user terminal 200.

Additionally, the processor 110 can perform content management operations such as classification of content acquired by the server 100 through communication with external devices, and select advertising content to be provided to users. As mentioned above, the processor 110 may be configured to include a content providing unit 140 and an advertisement selection unit 150.

For a more detailed description of the content provider 140, refer to FIG. 3.

Figure 3 is a diagram showing the configuration of a content provider according to an embodiment of the present invention.

As shown in FIG. 3, the content providing unit 140 will include a content attribute determination unit 141, a user information collection unit 142, a content processing unit 143, and a content transmission support unit 144. It is possible to perform operations to manage content, such as determining and classifying the properties of content acquired from an external device. Additionally, the content provider 140 may search for content corresponding to the user's request and provide it to the user.

Below, each configuration of the content providing unit 140 will be described.

First, the content attribute determination unit 141 can determine the attributes of the video content and advertising content. The attributes relate to, for example, related fields, topics, etc. of the content.

According to one embodiment, the video content may be interpreted as content related to learning, and in particular, the video content may mean a lecture video. However, the video content is not limited to this, and may include learning videos other than lectures obtained from a plurality of user terminals 200 (eg, a video of the user solving a problem uploaded by the user, etc.). Furthermore, the video content may include non-learning videos that are less relevant to learning (e.g., videos for personal study certification, humor videos, etc.).

When determining the properties of video content, the content property determination unit 141 may classify the types of video content mentioned above into lecture videos, non-lecture learning videos, non-learning videos, etc., and this classification information can be classified into labels. It can be specified as .

Additionally, the content property determination unit 141 can determine the properties of the advertising content and designate the corresponding property value as a label.

For example, the content attribute determination unit 141 may extract keywords corresponding to advertising content and label the advertising content with the extracted keywords. When extracting keywords for arbitrary advertising content, the content attribute determination unit 141 may perform an operation of converting the audio included in the advertising content into text (subtitles) by an STT (Speech to text) operation. there is. And the content attribute determination unit 141 may extract keyword words from the text (subtitle) information generated by the STT operation according to a preset standard. At this time, items corresponding to the criteria for extracting the keyword may include, for example, frequency of use, specificity (frequency of use higher than a standard value compared to the probability of being searched in subtitles of other videos), etc.

Furthermore, the content attribute determination unit 141 can extract keywords related to video content in a similar manner for not only advertising content but also video content and label the video content with the extracted keywords.

In addition, the content attribute determination unit 141 may directly receive keywords for the corresponding advertising content obtained from the advertising providing terminal 300 that provided the advertising content, and designate it as a label. For example, keywords for the advertising content may include items related to the purpose of the advertisement (e.g., subscription, sales, guidance, viewing, etc.), and the target of the advertisement (e.g., high school freshman, high school sophomore, local area). May include items regarding residents, reading room users, etc.) Additionally, the keyword may include items related to the main advertising object (eg, learning tool, academy, instructor, nutritional supplement, etc.) in the advertising content. And keywords for the advertising content are not limited to the items mentioned above.

As the content attribute determination unit 141 obtains keywords for advertising content, it can manage the keywords by designating them as labels corresponding to the content.

The user information collection unit 142 collects user-related information required to determine the user's characteristics, determines the user's characteristics through this, and classifies the user according to the determined characteristics.

The user information collection unit 142 may acquire information related to the user's basic personal information and classify the user into groups in response. For example, the user information collection unit 142 may classify users into the first high school group, the second high school group, and the third high school group based on the personal information details of the user registered by the user.

According to various embodiments, the user information collection unit 142 may classify users according to major learning subjects. According to this classification method, the user information collection unit 142 can classify the user as a high school second year group even if the user is actually a first year high school student and is mainly studying the second year of high school.

Alternatively, the user information collection unit 142 may classify users according to the career field the user is preparing for. For example, the user information collection unit 142 may classify users into a medical preparation group, a language and literature preparation group, a commerce preparation group, an engineering preparation group, etc.

After classifying users into groups in this way, the user information collection unit 142 stores the necessary information (e.g., minimum required learning (video lecture) schedule) related to preparing for the career field specified by the user in the memory 120. It can be set based on information (required or recommended learning schedules for each career field), and items that are judged to require additional learning in preparing for the relevant career field can be determined.

At this time, the user information collection unit 142 may determine whether the user needs additional learning based on the user's learning schedule compared to the minimum necessary learning schedule. For example, in a situation where learning about 10 sections of subject A (e.g., set to correspond to textbook units) is required to correspond to the user's career field, the user information collection unit 142 collects information from the actual user. The learning completion status can be confirmed to correspond to the five sections for Subject A. In this case, the user information collection unit 142 may determine the need for additional learning for the remaining five sections excluding the five sections for which the user has completed learning in subject A.

In this way, the user information collection unit 142 can classify users according to their career field and determine what the user needs to advance into that field.

According to various embodiments, the user information collection unit 142 may also obtain information about subjects related to the user's main viewing content or sections in which the subjects are classified according to preset conditions. Alternatively, the user information collection unit 142 may determine the user's list of watched videos, the user's intensive viewing time, and the user's interest category based on the user's search history and viewing history of video content.

In this way, the user's characteristic-related information obtained and determined through the user information collection unit 142 is later used to select advertising content matching the user by the characteristic-based selection unit 151 of the advertisement selection unit 150. It can be utilized.

The content processing unit 143 may generate advertising content by processing video content that is determined to require an influx of viewers.

According to one embodiment, advertising content provided from the server 100 of the present invention to the user terminal 200 may be acquired by the advertising providing terminal 300. However, it is not limited to this method, and the content processing unit 143 according to an embodiment of the present invention creates advertising content through video processing on its own for video content (e.g., lecture video) that is judged to require an influx of viewers. can be created.

At this time, the content processing unit 143 may perform at least one of changing the playback speed of the video content and dividing the video content into preset time units (eg, 1 minute). Furthermore, when the content processing unit 143 divides the video content (e.g., lecture video) into preset time units to generate short-form advertising content, the content processing unit 143 samples a plurality of thumbnail images from the video content at preset time intervals. , segmentation can be started based on the location where the scene change identified in the sampled thumbnail image begins.

The content transmission support unit 144 may transmit video content selected by the user to the user terminal 200.

In addition, the content transmission support unit 144 may transmit the advertising content selected by the advertisement selection unit 150 to the user terminal 200 at a frequency specified by the advertisement selection unit 150.

Among the configurations of the processor 110 shown in FIG. 2, when video content corresponding to the user's request is provided to the user, the advertisement selection unit 150 selects advertising content to be provided to the user along with the video content and selects it. You can perform the provided operations.

For a detailed description of the advertisement selection unit 150, refer to FIG. 4.

Figure 4 is a diagram showing the configuration of an advertisement selection unit according to an embodiment of the present invention.

As shown in FIG. 4, the advertisement selection unit 150 may include a characteristic-based selection unit 151, an effect-based selection unit 152, and a frequency selection unit 153.

The characteristic-based selection unit 151 may select advertising content to be provided to the user based on the characteristics of the user who requested video content.

Specifically, the characteristic-based selection unit 151 combines the user's characteristics with the user's age, the user's learning subject (or grade, learning stage), the list of videos the user has previously watched, and the user's intensive viewing time (of the video). time taken until playback stops), can be determined as at least one of the user's interest categories. At this time, the characteristic-based selection unit 151 may determine user characteristics based on information collected and determined by the user information collection unit 142 of the content providing unit 140.

And the characteristic-based selection unit 151 can provide advertising content corresponding to the user's characteristics. At this time, the characteristic-based selection unit 151 selects a group for the user's age or learning stage (e.g., 1st high school group, 2nd high school group, etc.) based on the user's age, the user's study subjects, etc. ) can be determined, and targeted advertising content can be matched corresponding to the determined group. For example, if the characteristic-based selection unit 151 determines that the user corresponds to the high school second year group, it can match and provide an advertisement for the high school second year workbook, which is advertising content targeted for the high school second group, to the user. there is. And at this time, the characteristic-based selection unit 151 may determine the target information of the advertising content based on the label assigned to the advertising content.

Additionally, the characteristic-based selection unit 151 can obtain the user's previously viewed video content history and obtain their label information. In addition, the characteristic-based selection unit 151 may determine the main area of interest for the user's learning (eg, reading comprehension, differentiation, etc.) through the frequency of labels of previously watched videos.

And the characteristic-based selection unit 151 can predict the user's interest area (or interest category) and match advertising content with a label corresponding to the user's interest area. The relationship between the user's area of interest and the label of the corresponding advertising content can be calculated using a preset formula. Alternatively, the correlation between the user's area of interest and the corresponding label may be calculated in response to statistical results based on the advertisement click rate of major viewers. For example, for users whose interest is determined to be reading, the label of advertising content for which the advertising click rate is calculated to be higher than the standard value may be set to correspond to the click rate with a matching relationship with the corresponding area of interest. In this way, the characteristic-based selection unit 151 can determine the relationship between the user's area of interest (category) and the label of the advertising content and match the advertising content accordingly.

Next, the effect-based selection unit 152 can predict the user's learning level (level) and select advertising content corresponding to the user's expected learning level.

According to one embodiment, the effect-based selection unit 152 may calculate the user's intensive viewing time when watching content separately classified as a lecture video among video content. At this time, the intensive viewing time can be obtained by calculating the average of the time elapsed from the time the user played a lecture video to the time it stopped. And at this time, the effect-based selection unit 152 can be controlled to check whether the user's gaze is detected while the lecture video is played on the user terminal 200 in order to determine the user's intensive viewing time, If the user's gaze is not detected, the user terminal 200 can be controlled to automatically stop playing the lecture video.

The effect-based selection unit 152 may calculate an estimate of the user's learning level based on the user's intensive viewing time and the user's participation level. At this time, the participation level is determined by whether the user consistently watched lecture videos corresponding to the same subject or section at preset intervals (e.g. one day) for more than a preset period (e.g. one week), and whether the user was asked questions after watching the lecture video. It can be calculated based on the frequency of writing, etc.

The effect-based selection unit 152 does not perform a separate test, but predicts the user's learning level based on factors (focused viewing time, participation) related to the user's habit of watching lectures.

And the effect-based selection unit 152 may match advertising content that corresponds to the calculated user's expected learning level or targets the same learning level. According to various embodiments, the advertising content may include information specifying the learning level of the main target viewer. The advertising content may include the learning level of the main target viewers, for example, an advertisement targeting a high-ranking audience, an advertisement targeting a middle-ranking audience, an advertisement targeting a low-ranking audience, etc.

Lastly, the frequency selection unit 153 can set the frequency of advertisements according to user characteristics. The frequency selection unit 153 may utilize the user's intensive viewing time for the lecture video among the video content, and reduce the frequency of providing the advertising content as the user's intensive viewing time increases. This frequency selection operation can encourage users who receive video lectures through the server 100 and learn through them to study more intensively in order to reduce the advertisements they receive.

Figure 5 is a flowchart showing the sequence of a content provision operation performed by an electronic device (server) according to an embodiment of the present invention.

As shown in FIG. 5, the server 100 according to an embodiment of the present invention may receive (501) a playback or transmission request for video content from the user's terminal.

In response, the server 100 may perform operation 502 to provide the requested video content to the user terminal.

Afterwards, as the video content is provided, the server 100 may perform operation 503 to select advertising content matching the user who requested the video content. At this time, when selecting advertising content matching a user, user characteristics related to the user's learning elements can be determined and advertising content corresponding thereto can be selected. For example, the server 100 determines the user's study subject based on the user's age (grade) or the user's main viewed lecture history, and advertises content based on at least one of the user's age and study subject. You can select . At this time, the advertising content may have information about the target target set in advance. For example, each of the above advertising contents may be pre-classified into advertisements targeting high school seniors, advertisements targeting high school seniors, etc. depending on the advertised product or advertising purpose.

And the server 100 may perform operation 504 to provide the selected advertising content to the user's terminal.

In short, the control method of an electronic device according to an embodiment of the present invention includes providing the selected video content to the user's terminal in response to a user's request for selecting at least one video content among a plurality of video content, the video content When provided, it may include selecting advertising content that matches at least one of the user's age and study subjects, and providing the selected advertising content to the user's terminal.

At this time, the providing step includes specifying a label for the plurality of video contents, receiving a search request for the video content from the user, and providing the video content corresponding to the user's request with the name of the video content and It may include matching based on the label and presenting at least one matched video content.

Among them, the step of specifying the label includes extracting at least one image from among a plurality of images constituting the video content or extracting at least one text from among the text of the subtitles stored in connection with the video content. It may have features that are performed.

Additionally, the providing step may include the step of processing video content that requires an influx of viewers to create advertising content. In addition, the step of generating the advertising content may be characterized by performing at least one of changing the playback speed of the video content and dividing the video content into preset time units.

And the step of selecting advertising content according to an embodiment of the present invention is characterized by selecting advertising content matching the user's characteristics, where the user's characteristics include the user's age, the user's study subjects, and the user's previous history. It may include at least one of a list of watched videos, the user's intensive viewing time, and the user's interest category.

Additionally, selecting the advertising content may include selecting a frequency of providing the advertising content. The step of selecting the frequency of providing the advertising content may be characterized in that the user's intensive viewing time for the lecture video among the video content is calculated, and the frequency of providing the advertising content is reduced as the user's intensive viewing time increases. there is.

In addition, the step of selecting the advertising content calculates the user's expected learning level based on the user's intensive viewing time and the user's participation in the lecture video among the video content, and corresponds to the user's expected learning level. Thus, it can be characterized by matching advertising content that matches the learning level of the target.

The server 100 according to an embodiment of the present invention may include a processor 110, a memory 120, a communication unit 130, etc.

Memory can store various programs and data necessary for the operation of electronic devices. Memory can be implemented as non-volatile memory, volatile memory, flash-memory, hard disk drive (HDD), or solid state drive (SSD).

The communication unit can perform communication with external devices. In particular, the communication unit may include various communication chips such as a Wi-Fi chip, a Bluetooth chip, a wireless communication chip, an NFC chip, and a low-power Bluetooth chip (BLE chip). At this time, the Wi-Fi chip, Bluetooth chip, and NFC chip communicate in the LAN method, WiFi method, Bluetooth method, and NFC method, respectively. When using a Wi-Fi chip or Bluetooth chip, various connection information such as SSID and session key are first transmitted and received, and various information can be transmitted and received after establishing a communication connection using this. A wireless communication chip refers to a chip that performs communication according to various communication standards such as IEEE, ZigBee, 3G (3rd Generation), 3GPP (3rd Generation Partnership Project), and LTE (Long Term Evolution).

The processor can control the overall operation of the user device using various programs stored in memory. The processor may be composed of RAM, ROM, graphics processing unit, main CPU, first to n interfaces, and bus. At this time, RAM, ROM, graphics processing unit, main CPU, first to n interfaces, etc. may be connected to each other through a bus.

RAM stores O/S and application programs. Specifically, when the electronic device is booted, the O/S is stored in RAM, and various application data selected by the user may be stored in RAM.

ROM stores a set of instructions for booting the system. When a turn-on command is input and power is supplied, the main CPU copies the O/S stored in the memory 200 to RAM according to the command stored in the ROM, executes the O/S, and boots the system. When booting is complete, the main CPU copies various application programs stored in memory to RAM and executes the application programs copied to RAM to perform various operations.

The main CPU accesses memory and performs operations including booting and execution using the OS stored in the memory. And, the main CPU performs various operations using various programs, content, data, etc. stored in memory.

The first to n interfaces are connected to the various components described above. One of the first to n interfaces may be a network interface connected to an external device through a network.

Meanwhile, furthermore, the processor can control the artificial intelligence model. In this case, of course, the control unit may include a graphics processor (eg, GPU) for controlling the artificial intelligence model.

The processor may include one or more cores (not shown), a graphics processing unit (not shown), and/or a connection passage (for example, a bus, etc.) for transmitting and receiving signals to and from other components.

A processor according to one embodiment performs the method described in connection with the present invention by executing one or more instructions stored in memory.

Meanwhile, the processor further includes RAM (Random Access Memory, not shown) and ROM (Read-Only Memory, not shown) that temporarily and/or permanently store signals (or data) processed inside the processor. It can be included. Additionally, the processor 130 may be implemented in the form of a system on chip (SoC) that includes at least one of a graphics processing unit, RAM, and ROM.

Programs (one or more instructions) for processing and controlling the processor can be stored in the memory. Programs stored in the storage unit may be divided into a plurality of modules according to their functions.

The steps of the method or algorithm described in connection with embodiments of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or a combination thereof. The software module may be RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, hard disk, removable disk, CD-ROM, or It may reside on any type of computer-readable recording medium well known in the art to which the present invention pertains.

The components of the present invention may be implemented as a program (or application) and stored in a medium in order to be executed in conjunction with a hardware computer. Components of the invention may be implemented as software programming or software elements, and similarly, embodiments may include various algorithms implemented as combinations of data structures, processes, routines or other programming constructs, such as C, C++, , may be implemented in a programming or scripting language such as Java, assembler, etc. Functional aspects may be implemented as algorithms running on one or more processors.

Although the present invention has been described in detail with reference to the above-described examples, those skilled in the art may make modifications, changes, and variations to the examples without departing from the scope of the present invention. In short, in order to achieve the effect intended by the present invention, it is not necessary to separately include all functional blocks shown in the drawings or to follow all the orders shown in the drawings, and even if not, the technical aspects of the present invention described in the claims may be used. Please note that it may fall within the range.

100: server
140: Content provision department
141: Content attribute judgment unit
142: User information collection unit
143: Content processing department
144: Content Delivery Support Department
150: Advertisement selection section
151: Characteristic-based selection unit
152: Effect-based selection section
153: frequency selection unit
200: user terminal
300: Advertisement provision terminal

Claims (1)

In a method of controlling an electronic device,
Providing the selected video content to the user's terminal in response to a user's request for selecting at least one video content from among a plurality of video content;
When the video content is provided, selecting advertising content matching at least one of the user's age and study subjects; and
Comprising: providing the selected advertising content to the user's terminal,
The steps to select above are
Comprising: selecting the frequency of provision of the advertising content,
The step of selecting the frequency of provision is
Calculate the user's intensive viewing time for the lecture video among the video contents,
As the user's intensive viewing time increases, the frequency of providing advertising content decreases,
The intensive viewing time corresponds to the average of the time taken from the time playback of the lecture video started to the time it was stopped,
The above selection steps are
Calculating the user's expected learning level based on the user's intensive viewing time and the user's participation in the lecture video among the video content,
Match advertising content that matches the target learning level in response to the user's expected learning level,
The participation level is,
Calculated based on at least one of whether the user has watched a lecture video corresponding to the same subject or the same section at a preset interval for more than a preset period of time, and the frequency with which the user writes a question after watching the lecture video. Characterized by
The control method of the electronic device is,
Extracting keywords for advertising content from at least one advertising providing terminal; and
It includes; specifying the extracted keywords as labels for a plurality of advertising contents,
Keywords for the advertising content are:
A system comprising at least one of a purpose of the advertising content, a target, and an item related to the advertising target.