KR102525315B1 - User recommendation method using production data and usage data and apparatus therefor - Google Patents

Abstract

In the present specification, in a method in which a recommendation device recommends assets and content to a user, learning data is received from a platform for using the content and an authoring tool for producing the content, and based on the learning data to build a learning model, and using the learning model, 1) a first model for analyzing the characteristics of the user, 2) a second model for recommending the content, and 3) for recommending the element A third model is generated, recommended content information is transmitted to the platform using the first model and the second model, and recommendation is made to the authoring tool using the first model and the third model. Element information can be passed.

Description

User recommendation method using production data and usage data and apparatus therefor

The present specification relates to a method for recommending data related to production to a user using data that can be obtained in content production and use.

With the development of Internet technology, various types of multimedia contents are rapidly growing based on high-performance network environments in 5G and 6G environments. As large-scale user participation platforms such as YouTube and TikTok are activated, the desire to create and distribute individual contents is growing, and various types of authoring tools are appearing as a result.

Through these authoring tools, users can consume a variety of content, and companies provide more convenient and intuitive services to users by using an algorithm that recommends content related to the content that the user is interested in through analyzing the activity data of these users. can do.

However, these general recommendation algorithms are limited only to the content consumed by users, and there is no recommendation algorithm that considers production data of content produced by users based on WEB3.0.

An object of the present specification is to perform learning of an artificial intelligence model by using consumption data and production data of a user, and to provide a service through the learned artificial intelligence model.

In addition, an object of the present specification is to provide a method for recommending various contents and assets (elements) to the user by using usage data consumed by the user and production data of contents produced by the user.

The technical problems to be achieved by this specification are not limited to the above-mentioned technical problems, and other technical problems not mentioned are clear to those skilled in the art from the detailed description of the specification below. will be understandable.

One aspect of the present specification is a method for recommending an asset and content to a user by a recommendation device, comprising: receiving learning data from a platform for using the content and an authoring tool for producing the content; Building a learning model based on the learning data; generating, by using the learning model, 1) a first model for analyzing the characteristics of the user, 2) a second model for recommending the content, and 3) a third model for recommending the asset; transmitting recommended content information to the platform using the first model and the second model; and transmitting recommended asset information to the authoring tool using the first model and the third model. can include

In addition, the learning data may include 1) user information related to the user using the platform, 2) user behavior information related to the user's behavior using the platform and the authoring tool, and 3) content information related to the content. can

In addition, the user information may be collected through a statistical collection of the user's terminal and a member sign-up procedure of the platform.

In addition, the user behavior information may be collected through statistical collection of the user's terminal, the platform, and the authoring tool.

In addition, the content information may be collected through a procedure for using the content of the platform and a procedure for producing and storing the content through the authoring tool.

In addition, the platform may transmit a list of recommended contents to the user based on the recommended contents information.

In addition, the authoring tool may transmit a recommendation list of the asset to the user based on the recommended asset information.

Another aspect of the present specification is a recommendation device for recommending assets and content to a user, comprising: a communication unit; memory containing artificial intelligence models; and a processor for functionally controlling the communication unit and the memory. The processor receives learning data from a platform for using the content and an authoring tool for producing the content, builds a learning model based on the learning data, and uses the learning model , 1) a first model for analyzing the characteristics of the user, 2) a second model for recommending the content, and 3) a third model for recommending the asset, the first model and the Recommended content information may be delivered to the platform using the second model, and recommended asset information may be delivered to the authoring tool using the first model and the third model.

According to an embodiment of the present specification, it is possible to perform learning of an artificial intelligence model by using consumption data and production data of a user, and provide a service through the learned artificial intelligence model.

In addition, according to an embodiment of the present specification, it is possible to provide a recommendation method for various contents and assets (elements) to the user by using usage data consumed by the user and production data of contents produced by the user.

Effects obtainable in the present specification are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below. .

1 is a block diagram for explaining an electronic device related to the present specification.
2 is an embodiment to which the present specification can be applied.
3 is an example of page generation to which this specification can be applied.
4 is an example of a controller 400 that can be applied to this specification.
5 is an example of a page list to which this specification can be applied.
6 is an example of elements to which this specification may be applied.
7 is an example of event detection of a convergence type manufacturing apparatus to which the present specification can be applied.
8 is an example of a result execution method to which the present specification can be applied.
9 is an example of element management to which this specification can be applied.
10 and 11 are examples of element upload to which this specification can be applied.
12 is a block diagram of an AI device according to an embodiment of the present specification.
13 is an example of a recommendation method pipeline to which the present specification can be applied.
14 is an example of visual coding to which the present specification can be applied.
15 is an embodiment of a recommendation device to which the present specification can be applied.
16 is an example of content display to which this specification can be applied.
17 is an example of content storage to which this specification can be applied.
18 is an example of recommended content information display to which this specification can be applied.
19 is an example of displaying recommendation element information to which the present specification can be applied.
The accompanying drawings, which are included as part of the detailed description to aid understanding of the present specification, provide examples of the present specification and describe technical features of the present specification together with the detailed description.

Hereinafter, the embodiments disclosed in this specification will be described in detail with reference to the accompanying drawings, but the same or similar components are given the same reference numerals regardless of reference numerals, and redundant description thereof will be omitted. The suffixes "module" and "unit" for components used in the following description are given or used together in consideration of ease of writing the specification, and do not have meanings or roles that are distinct from each other by themselves. In addition, in describing the embodiments disclosed in this specification, if it is determined that a detailed description of a related known technology may obscure the gist of the embodiment disclosed in this specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in this specification, the technical idea disclosed in this specification is not limited by the accompanying drawings, and all changes included in the spirit and technical scope of this specification , it should be understood to include equivalents or substitutes.

Terms including ordinal numbers, such as first and second, may be used to describe various components, but the components are not limited by the terms. These terms are only used for the purpose of distinguishing one component from another.

It is understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, but other elements may exist in the middle. It should be. On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it should be understood that no other element exists in the middle.

Singular expressions include plural expressions unless the context clearly dictates otherwise.

In this application, terms such as "comprise" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

1 is a block diagram for explaining an electronic device related to the present specification.

The electronic device 100 includes a wireless communication unit 110, an input unit 120, a sensing unit 140, an output unit 150, an interface unit 160, a memory 170, a control unit 180, and a power supply unit 190. ) and the like. The components shown in FIG. 1 are not essential to implement an electronic device, so an electronic device described in this specification may have more or fewer components than those listed above.

More specifically, among the components, the wireless communication unit 110 is between the electronic device 100 and the wireless communication system, between the electronic device 100 and other electronic devices 100, or between the electronic device 100 and an external server. It may include one or more modules enabling wireless communication between Also, the wireless communication unit 110 may include one or more modules that connect the electronic device 100 to one or more networks.

The wireless communication unit 110 may include at least one of a broadcast reception module 111, a mobile communication module 112, a wireless Internet module 113, a short-distance communication module 114, and a location information module 115. .

The input unit 120 includes a camera 121 or video input unit for inputting a video signal, a microphone 122 for inputting an audio signal, or a user input unit 123 for receiving information from a user, for example , a touch key, a push key (mechanical key, etc.). Voice data or image data collected by the input unit 120 may be analyzed and processed as a user's control command.

The sensing unit 140 may include one or more sensors for sensing at least one of information within the electronic device, environmental information surrounding the electronic device, and user information. For example, the sensing unit 140 may include a proximity sensor 141, an illumination sensor 142, a touch sensor, an acceleration sensor, a magnetic sensor, and gravity. Sensor (G-sensor), gyroscope sensor (gyroscope sensor), motion sensor (motion sensor), RGB sensor, infrared sensor (IR sensor), finger scan sensor, ultrasonic sensor , an optical sensor (eg, a camera (see 121)), a microphone (see 122), a battery gauge, an environmental sensor (eg, a barometer, a hygrometer, a thermometer, a radiation detection sensor, It may include at least one of a heat detection sensor, a gas detection sensor, etc.), a chemical sensor (eg, an electronic nose, a healthcare sensor, a biometric sensor, etc.). Meanwhile, the electronic device disclosed in this specification may combine and utilize information sensed by at least two or more of these sensors.

The output unit 150 is for generating an output related to sight, hearing, or touch, and includes at least one of a display unit 151, a sound output unit 152, a haptic module 153, and an optical output unit 154. can do. The display unit 151 may implement a touch screen by forming a mutual layer structure or integrally with the touch sensor. Such a touch screen may function as a user input unit 123 providing an input interface between the electronic device 100 and the user and provide an output interface between the electronic device 100 and the user.

The interface unit 160 serves as a passage for various types of external devices connected to the electronic device 100 . The interface unit 160 connects a device equipped with a wired/wireless headset port, an external charger port, a wired/wireless data port, a memory card port, and an identification module. It may include at least one of a port, an audio input/output (I/O) port, a video input/output (I/O) port, and an earphone port. In response to the external device being connected to the interface unit 160, the electronic device 100 may perform appropriate control related to the connected external device.

Also, the memory 170 stores data supporting various functions of the electronic device 100 . The memory 170 may store a plurality of application programs (application programs or applications) running in the electronic device 100 , data for operating the electronic device 100 , and commands. At least some of these application programs may be downloaded from an external server through wireless communication. In addition, at least some of these application programs may exist on the electronic device 100 from the time of shipment for basic functions of the electronic device 100 (eg, incoming and outgoing calls, outgoing functions, message receiving, and outgoing functions). Meanwhile, the application program may be stored in the memory 170, installed on the electronic device 100, and driven by the control unit 180 to perform an operation (or function) of the electronic device.

The controller 180 controls general operations of the electronic device 100 in addition to operations related to the application program. The control unit 180 may provide or process appropriate information or functions to the user by processing signals, data, information, etc. input or output through the components described above or by running an application program stored in the memory 170.

In addition, the controller 180 may control at least some of the components discussed in conjunction with FIG. 1 in order to drive an application program stored in the memory 170 . Furthermore, the controller 180 may combine and operate at least two or more of the components included in the electronic device 100 to drive the application program.

The power supply unit 190 receives external power and internal power under the control of the controller 180 and supplies power to each component included in the electronic device 100 . The power supply unit 190 includes a battery, and the battery may be a built-in battery or a replaceable battery.

At least some of the components may operate in cooperation with each other in order to implement an operation, control, or control method of an electronic device according to various embodiments described below. Also, the operation, control, or control method of the electronic device may be implemented on the electronic device by driving at least one application program stored in the memory 170 .

In this specification, the electronic device 100 may include a recommendation device, a terminal, a visual coding device, and a convergence type production device.

2 is an embodiment to which the present specification can be applied.

Referring to FIG. 2 , a user may communicate with a convergence type manufacturing device through a terminal. For example, the terminal can be connected to the convergence type production device through the WEB without a separate application, and the user can simultaneously produce 2D and 3D contents through the terminal.

The recommendation device includes the AI device 20 described below, is connected to the user's terminal and the convergence type production device, analyzes the user's propensity using meta data generated from the terminal and the convergence type production device, and analyzes the result of the analysis. Using , content and elements (Assets) suitable for the user can be recommended.

The convergence type production device receives a content creation command from the terminal through the WEB (S2010). For example, content may include 2D and/or 3D objects.

The convergence type production device creates a page to create content (S2020). For example, the page includes a page that can be expressed in a 2D or 3D form, and the convergence type production device may configure a screen by adding and arranging predefined elements (assets) or templates to each page. More specifically, an event may be registered in the added element, so that interaction with the content user may be added. Through this, users can create immersive and creative content.

3 is an example of page generation to which this specification can be applied.

Referring to FIG. 3 , a user may be provided with a page display screen 300 from a convergence type production device through a terminal. For example, one content may include one or more pages. In addition, the user can change the shape of the page in 2D or 3D through the layout selection window 310 that can appear on the page display screen 300, and creates a virtual space with special functions according to the content user's request, such as AR mode. can be added separately. The convergence type production device may register a separate controller 400 according to the shape of the page. Also, the user may change the size and ratio of the page through the layout selection window 310 .

Referring back to FIG. 2 , the convergence type manufacturing device registers the controller 400 based on the page (S2030). For example, the convergence type production device may register a controller 400 capable of controlling and interacting with elements according to the shape of a page.

4 is an example of a controller 400 that can be applied to this specification.

Referring to FIG. 4, when a user selects an element through a terminal, properties suitable for the element are displayed in the property window 410, the convergence type manufacturing device displays the registered controller 400, and the user selects the controller ( 400), attributes can be easily edited using a mouse or a touch. For example, a user can input accurate numerical values in the attribute window 410 to modify attribute values of elements in detail. The user can perform additional connected functions by adding a tab to the property window 410 . For example, additional connected functions may include the source of the element's creator or media playback information.

Referring back to FIG. 2 , the convergence type production device arranges elements on a page (S2040). For example, the convergence type production device may arrange predefined elements/templates and/or additionally uploaded elements according to page types.

5 is an example of a page list to which this specification can be applied.

Referring to FIG. 5, one content is composed of a bundle of several pages (screens), and a 2D or 3D screen can be selected according to a user's request.

For example, a page includes (1) page properties, (2) an event list, and (3) a resource list. More specifically, the event list includes information on events assigned to elements, and the resource list includes information on elements added to a page.

6 is an example of elements to which this specification may be applied.

Referring to FIG. 6 , the convergence type production apparatus may provide a predefined element/template according to a page type to a user through a terminal. Also, users can additionally upload and place elements.

Referring back to FIG. 2 , the convergence type manufacturing apparatus modifies the attribute value of the element (S2050).

For example, when the user selects an element arranged on the page display screen 300, the convergence type manufacturing device displays the property window 410 corresponding to the corresponding element, and the user registers the controller 400 based on the page. ), the property value can be modified through mouse, touch, numerical input, etc.

The convergence type manufacturing device registers an event corresponding to an element (S2060). For example, an event may contain a set of “actions” and “results”. More specifically, an action may define a condition under which an event occurs. For example, “action” is a condition for performing a function and may include various types of events or calls such as keyboard events, mouse/touch events, gesture events, area events, value events, and call events.

Also, results may include "feature" and "subject".

In more detail, “function” can define property changes and specific actions to be performed for the “object” that is the purpose of the function when an event is activated, and basic properties of elements such as position, size, rotation, transparency, view, It may include control functions for media elements such as hide, play, stop, and pause. In addition, a camera, GPS, accelerometer, etc. of a user terminal for utilizing information of an external environment may be included.

The convergence type production device registers an action, function, and/or object corresponding to the event (S2070). For example, the convergence type manufacturing device may register actions, functions, and/or objects based on attribute values of elements.

The convergence type manufacturing device executes the result when an event for an element is detected based on the registered action (S2080).

7 is an example of event detection of a convergence type manufacturing apparatus to which the present specification can be applied.

Referring to FIG. 7 , the convergence type manufacturing apparatus may check an event corresponding to an element, monitor the event, and detect the event. When an event is detected, the convergence type manufacturing device may check an attribute to execute a function corresponding to the event, and execute a result based on the function and attribute.

8 is an example of a result execution method to which the present specification can be applied.

Referring to FIG. 8, the convergence type manufacturing device can execute “result” simultaneously, and the lower “result” can be connected to the upper “result” and executed consecutively. In addition, the connection of the “result” is not limited and the upper “result” is connected. Continuing functions can be performed in the next step using the execution result of “result.” Unlike execution methods that are simply driven by one timeline, this result execution method provides the user with actual programming in relation to the operation of elements. It can provide the same environment as the technique, and can help you learn the programming environment naturally.

9 is an example of element management to which this specification can be applied.

Referring to FIG. 9 , since the 2D and 3D elements have different properties, it is difficult for the convergence type manufacturing device to control the elements in the same way. Therefore, the convergence type production device first wraps the 2D form elements and the 3D form elements through the object called "basic element", and expands to the "used element" used in the authoring tool of the convergence type production device based on the "basic element" and manages the elements so that they can be used. For example, the functionality of a "using element" may be configured to control and use the properties of a "primitive element". In more detail, in FIG. 9, images, videos, figures, and 3D models are exemplified as "using elements", but if the form is advantageous for controlling and displaying the characteristics of 2D elements and 3D elements, "using elements" may be used. can be displayed

10 and 11 are examples of element upload to which this specification can be applied.

Referring to FIGS. 10 and 11 , the convergence type manufacturing apparatus loads an uploaded element file through a loader and registers an object of the loaded element file as a “using element” that may correspond to the loader. The convergence type manufacturing device may place the uploaded element using the registered “used element”.

Referring to FIG. 10 , when the uploaded element file is an image file, the convergence type production device may load the image file through an image loader and register an object of the loaded image file as an image element. .

Referring to FIG. 11, when the uploaded element file is a 3D model file, the convergence type manufacturing device loads the 3D model file through a 3D loader, creates an object of the loaded 3D model file, and creates an animation to , In addition to animation, the created object can be registered as a 3D element.

For example, if the uploaded element file is a video file, the convergence type production device can create an HTMLVideoElement, add it to the screen, and then register the object as a "using element" to control it.

One content may include several pages, and each page may include a “resourceManager” that manages elements and an “eventManager” that manages operation events.

Elements placed on the page have a separate depth, so the convergence type production device can adjust the exposure order of elements on the screen by adjusting the depth according to the user's needs.

For example, in the convergence type production device, when an element is arranged, the corresponding element is registered in the resource manager of the corresponding page, and can be managed through changes, registration, deletion, etc. of properties and states. Resource manager not only manages the arranged elements, but also can call the connected function according to the change of the resource based on the resource list by generating an event for the change.

When an element is added, the convergence type production device adds the element to the management list in order to control the element through the controller registered in the page so that the controller can recognize it as a controllable element and manage it. Elements registered in the controller can be modified or controlled by the user's mouse, gesture, touch, or external controller.

In addition, the Redo/Undo function may be needed in the process of controlling the element by the user. To this end, the convergence type production device records changes in the state of the corresponding element by saving the changes in the controller in the history manager of the page, and calls the properties of the element from the list of changes stored in the history manager upon request. It can be configured to restore or re-update element state by updating current element properties. Memory problems can occur in the history manager because changes are saved for each element. Accordingly, in order to prevent this, the convergence type manufacturing device may limit the number of list of changes to be stored according to circumstances.

In addition, the convergence type production device can designate a user to share when producing content and perform the task simultaneously. For example, when content is initially created, the convergence type production device may create a unique channel corresponding to the content. The convergence type production device can designate a shared user who can use a unique channel and add the user to the same channel when the user accesses the corresponding content.

Users on the same channel can send and receive changes in real time and synchronize authoring data in real time. To this end, communication can be made in real time through websocket or webrtc.

However, when a new user accesses unsaved content, synchronization is performed with the previous version of the content, which may cause a version difference. To prevent this, when a new user accesses content for the first time after being added to a shared channel, initial synchronization may be performed by performing a general update on work changes through a specific user among existing working users. After such initial synchronization, the convergence type production device can solve the synchronization issue of unsaved content through a method of sharing data on changes in real time.

12 is a block diagram of an AI device according to an embodiment of the present specification.

The AI device 20 may include an electronic device including an AI module capable of performing AI processing or a server including the AI module. In addition, the AI device 20 may be included in at least a portion of the electronic device 100 shown in FIG. 1 to perform at least a portion of AI processing together.

The AI device 20 may include an AI processor 21, a memory 25 and/or a communication unit 27.

The AI device 20 is a computing device capable of learning a neural network, and may be implemented in various electronic devices such as a server, a desktop PC, a notebook PC, and a tablet PC.

The AI processor 21 may learn a neural network using a program stored in the memory 25 . For example, the AI processor 21 can generate a Tensorflow-utilized Recurrent Neural Networks (recurrent neural network) model on the memory 25, and uses data that can be collected from a user terminal and a convergence manufacturing device , these AI models can be trained.

For example, a trained AI model can generate sub-models with the following tasks:

1. Content Recommendation Model: Recommends customized content to users by using user characteristics model and data from analyzing content usage information and content creation information

2. Element Recommendation Model: Recommends customized assets to content creators using user characteristic models and asset metadata

3. User Characteristics Analysis Model: Analyzing the user's characteristics through analysis of the user's learning interest, participation, and immersion

13 is an example of a recommendation method pipeline to which the present specification can be applied.

Referring to FIG. 13 , an artificial intelligence model 1300 may be learned using data collected from a platform and a converged production device.

For example, the platform may be provided to a terminal through the WEB, and may be connected to a convergence type production device to provide a content production environment to the user. In addition, content created by other users can be displayed, and a search function for this can be provided. In addition, the platform may provide a user with a template that can be used in a content production environment, and may also provide a search function for this.

The learned artificial intelligence model may generate 1) a user characteristic analysis model, 2) a content recommendation model, and 3) an element recommendation model. The user characteristics output by the user characteristic analysis model may be used for learning of the artificial intelligence model 1300 .

For example, based on the characteristics of the user output from the user characteristic analysis model, the artificial intelligence model 1300 may display recommended content information to the user through the platform using the content recommendation model.

In addition, the artificial intelligence model 1300 may display element recommendation information to a user who wants to create content through a convergence type production device using an element recommendation model based on the user's characteristics output from the user characteristic analysis model. there is.

Data collected for learning may include 1) user information, 2) user behavior information, and 3) content information.

1. User Information

When a user accesses the platform for the first time, it may be collected through a terminal or through a membership registration procedure of the platform.

Table 1 below is an example of user information.

data collection channel data item statistics collection country area
City/Gun/Gu
language
browser
device
operating system
platform
resolution Join the platform User identification numberUser name
User ID
age
gender
Sign up date

2. User Behavioral Information It can be collected according to the user's behavior.

Table 2 below is an example of user behavior information.

data collection channel data item statistics collection Platform stay timeAverage participation time
Number of participating sessions (number of page moves)
Average participation time per session
revisit
Date of first visit
Content participation time platform Event code search word information for each button (keyword)
Content View History
Content Reviews
Content star rating
Like/dislike content
content bookmarks
How to enter the site Convergence type manufacturing device Select user unique number item
menu selection
Select Visual Coding Settings

3. Content Information

Table 3 below is an example of content information.

data collection channel data item data details platform Content usage information Unique content number Unique content user number
content retention time
Number of uses of content
Like the content
dislike content
Content Reviews
content bookmarks
Content star rating
Whether to move to the next content after experiencing the content
Content View History Convergence type manufacturing device Content creation information Unique number of element registrant
Classification of used elements
element meta information
element source file name
element category name
copyright holder
User behavior information used
Behavioral information of used elements
Number of uses by element category Content storage information Unique number of content registrant
subject
target grade
content name
Content Description
Content category
registration channel
Presence of infant content
Content expected play time

14 is an example of visual coding to which the present specification can be applied.

Referring to FIG. 14 , a user may communicate with a visual coding device through a terminal. For example, the convergence type manufacturing device may include a visual coding device.

In addition, the terminal can be connected to the visual coding device through the WEB without a separate application, and the user can create content through visual coding through the terminal.

The terminal generates a page for visual coding and arranges an asset on the page (S1410). For example, the terminal may display a list of elements and/or a template including the elements to the user. Users can select elements from the template to be placed on the page.

The terminal sets target elements to be visual coded based on the arranged elements (S1420). For example, a user may click and select a target element among elements arranged on a page.

The terminal sets user behavior related to interaction with the user (S1430). For example, a user action may be a condition for generating an event of a target element.

The terminal sets a result related to the target element based on the user's action (S1440). For example, the result may mean an operation performed in relation to a target element when the terminal receives an input corresponding to a user action from a user. The result may include a “function” for controlling the size, position, and state value of the target element, “operation” for calculating variables related to the target element, and a “function page” for indicating movement of the page.

The terminal displays the result of the target element based on the input of the user's action (S1450). For example, when a user clicks the target element once, the terminal may display a screen moving the target element for 1 second or moving to another page as a result.

15 is an embodiment of a recommendation device to which the present specification can be applied.

Referring to FIG. 15, the recommendation device is connected to the user terminal and the convergence type production device, learns through the collected data, and provides the predicted output value through the learned artificial intelligence model to the platform and the convergence type production device. . For example, the convergence type production device may include an authoring tool for content production.

The recommendation device receives learning data from the platform and convergence type production device (S1510). For example, the learning data includes user information related to a user using the platform, user behavior information related to the user's behavior using the platform and the convergence type production device, and content information related to content.

In more detail, in user information, information such as country, region, city/county/district, language, browser, device, operating system, platform, and resolution may be collected through statistics collection when a user accesses the platform through a terminal. there is. In addition, among user information, information such as a user identification number, user name, user ID, age, gender, date of joining may be collected through information provided by the user for membership registration on the platform.

In more detail, in user behavior information, information such as platform stay time, average participation time, number of participating sessions (number of page movements), average participation time per session, revisit, first visit date, content participation time, etc. It may be collected through statistics collection while using the platform. For example, information such as event codes for each button, search word information (keywords), and site entry method can be collected through the platform without a user logging in.

Users can log in, use content provided through the platform, create content through a converged production device connected to the platform, and create content through visual coding.

More specifically, in content information, content usage information may be collected through the platform based on user behavior.

16 is an example of content display to which this specification can be applied.

Referring to FIG. 16 , a user may use content through a page for displaying content of a platform, and the platform may collect content use information from a user's behavior through a page for displaying content.

Referring again to FIG. 15 , the user can produce content through the convergence type production device, and the convergence type production device can collect content production information and content storage information.

For example, a user may perform visual coding through the added element, and through this, used user behavior information and operation information of the used element may be collected. In addition, when the user saves the content that has been produced, the convergence type production device collects the unique number of the content registrant, subject, target grade, content name, content description, content category, registration channel, existence of infant content, expected play time of the content, etc. can do.

17 is an example of content storage to which this specification can be applied.

Referring to FIG. 17 , a user who wants to create and store content may input content storage information through a page for content storage provided from a convergence type production device.

Referring again to FIG. 15 , the recommendation device builds a learning model based on the learning data (S1520).

The recommendation device generates 1) a user characteristic analysis model, 2) a content recommendation model, and 3) an element recommendation model using the learning model (S1530).

The recommendation device transmits recommended content information to the platform using the user characteristic analysis model and the content recommendation model (S1540). For example, based on the characteristics of the user output from the user characteristic analysis model, the recommendation device may transmit recommended content information to the platform using the content recommendation model.

18 is an example of recommended content information display to which this specification can be applied.

Referring to FIG. 18 , the platform may display a panel 1800 for displaying recommended content information on the right side of a page for content display. For example, the recommended content information may include a list including screens and titles of recommended content.

Referring back to FIG. 15 , the recommendation device transmits recommended element information to the convergence type production device using the user characteristic analysis model and the element recommendation model (S1550).

19 is an example of displaying recommendation element information to which the present specification can be applied.

Referring to FIG. 19 , the convergence type manufacturing apparatus may display recommended element information to the user. For example, the convergence type production device displays recommended element information frequently used by users or recommended through an artificial intelligence model in the form of a list at the top of a list of elements provided to the user to create content by the user (1900 )can do.

Through this, in the present specification, the recommendation device may analyze the user's propensity using the user's content use statistics and meta data generated when the content is created, and recommend content and elements suitable for the user by utilizing the analysis result.

The above specification can be implemented as computer readable code on a medium on which a program is recorded. A computer-readable medium includes all types of recording devices in which data that can be read by a computer system is stored. Examples of computer-readable media include Hard Disk Drive (HDD), Solid State Disk (SSD), Silicon Disk Drive (SDD), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. , and also includes those implemented in the form of a carrier wave (eg, transmission over the Internet). Accordingly, the above detailed description should not be construed as limiting in all respects and should be considered illustrative. The scope of this specification should be determined by reasonable interpretation of the appended claims, and all changes within the equivalent scope of this specification are included in the scope of this specification.

In addition, although services and embodiments have been described above, this is only an example and does not limit the present specification, and those skilled in the art to which this specification belongs will not deviate from the essential characteristics of the present service and embodiments. It will be appreciated that various modifications and applications not exemplified above are possible. For example, each component specifically shown in the embodiments can be modified and implemented. And differences related to these modifications and applications should be construed as being included in the scope of the present specification as defined in the appended claims.

Claims (8)

A method in which a recommendation device recommends an asset and content to a user,
Receiving learning data from a platform for using the content and an authoring tool for producing the content;
Building a learning model based on the learning data;
generating, by using the learning model, 1) a first model for analyzing the characteristics of the user, 2) a second model for recommending the content, and 3) a third model for recommending the asset;
transmitting recommended content information to the platform using the first model and the second model; and
transmitting recommended asset information to the authoring tool using the first model and the third model;
Including, recommended method. According to claim 1,
The learning data is
1) user information related to users using the platform;
2) User behavior information related to the user's behavior using the platform and the authoring tool, and
3) A recommendation method including content information related to the content. According to claim 2,
The user information
The recommendation method, which is collected through the collection of statistics of the user's terminal and the membership sign-up process of the platform. According to claim 2,
The user behavior information is
The recommendation method, which is collected through statistics collection of the user's terminal, the platform, and the authoring tool. According to claim 2,
The content information
A recommendation method, which is collected through a procedure for using the content of the platform and a procedure for producing and storing the content through the authoring tool. According to claim 1,
the platform
Based on the recommended content information, a recommended list of the content is delivered to the user. According to claim 1,
The authoring tool is
A recommendation method of transmitting a recommendation list of the asset to the user based on the recommended asset information. A recommendation device for recommending assets and content to a user,
communications department;
memory containing artificial intelligence models; and
a processor for functionally controlling the communication unit and the memory; Including,
The processor
Receive learning data from a platform for using the content and an authoring tool for producing the content, build a learning model based on the learning data, and use the learning model to: 1) the user's characteristics A first model for analyzing , 2) a second model for recommending the content, and 3) a third model for recommending the asset are generated, and using the first model and the second model, A recommendation device that transmits recommended content information to the platform and transmits recommended asset information to the authoring tool using the first model and the third model.

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