WO2021112465A1

WO2021112465A1 - Design recommendation method through analysis of cloud works

Info

Publication number: WO2021112465A1
Application number: PCT/KR2020/016616
Authority: WO
Inventors: 안태환; 안성환
Original assignee: 주식회사 큐리어드
Priority date: 2019-12-04
Filing date: 2020-11-23
Publication date: 2021-06-10
Also published as: KR102111720B1

Abstract

An embodiment of the present invention may comprise: a work monitoring step in which a design recommendation server tracks and monitors a work production action, in real time, performed in a user terminal connected to a cloud network; a design type recommendation list providing step in which the design recommendation server sequentially provides a design type recommendation list according to a design type recommendation ranking for each design item on the basis of the working activity of a user connecting to the design recommendation server; a work production step in which the user terminal produces a work by selecting any one design type from the design type recommendation list sequentially provided for each design item by the user; a work registration step in which the design recommendation server registers and stores the work through the cloud network when the work production action performed in the user terminal is finished; and a registered work analysis step in which the design recommendation server generates the design type recommendation list for each design item by monitoring and analyzing the work finally registered due to the end of the work production action.

Description

Design recommendation method through cloud asset analysis

As a design recommendation method, the present invention analyzes the works of other users uploaded to the cloud and recommends various designs such as resolution, layout information, font information, shape information, image information, color information, chart information, and graph information. it's about

In general, the role of an authoring tool is to provide a production environment that can easily and easily help works such as contents and documents. Therefore, many document/design authoring tools provide image libraries or templates (layouts) with pre-configured layouts. Users create documents/designs by referencing images and other design elements from the provided library or directly applying them.

However, users spend a lot of time searching for or searching for design elements or templates (layouts), and it is not always easy to find content suitable for the document/design they want to create.

In addition, the design elements found through this search process may have complex copyright issues and may not fit the latest trends.

For this reason, there are actually many companies and homepages that provide various image sites, templates, and reference materials (portfolios) for designers/content creators in the Internet space. However, there are many cases where it is provided for a fee or the copyright is limited, the types of content are diverse (website, presentation materials, card news, printed materials, etc.), and it is difficult to distinguish them according to the resolution or purpose of use. have.

The technical task of the present invention is to recommend design elements/layouts derived from documents/designs of other users registered under the cloud environment when a user wants to design documents, contents, etc. It is to provide a means by which

An embodiment of the present invention includes a work monitoring process in which a design recommendation server tracks and monitors in real time an act of making a work performed in a user terminal connected to a cloud network; a design type recommendation list providing process in which the design recommendation server sequentially provides a design type recommendation list for each design item according to the design type recommendation ranking according to the authoring activity of a user who has accessed the design recommendation server; a work production process in which the user terminal selects a design type from a user from a design type recommendation list sequentially provided for each design item and produces a work; a work registration process in which the design recommendation server registers and stores the work through the cloud network when the work production action performed in the user terminal is terminated; and a registered work analysis process in which the design recommendation server generates a design type recommendation list for each design item by monitoring and analyzing the work to be finally registered due to the end of the work production act.

The registered work analysis process may include: a design extraction process in which the design recommendation server analyzes a work updated and registered through the cloud and extracts a design included in the work; a design type determination process in which the design recommendation server classifies the extracted designs by design items to determine a design type; a recommendation ranking determining process in which the design recommendation server evaluates each design type according to a preset evaluation index, and determines a design type recommendation ranking for each design item; and a design type recommendation list generation process in which the design recommendation server generates a design type recommendation list for each design item based on the design type recommendation ranking.

The design item includes at least one of a type, basic setting information, layout information, color information, image information, figure attribute information, and text attribute information, and the design type determining process includes the extracted design type, basic setting information, It is possible to determine which design item belongs to among the design items including layout information, color information, image information, figure property information, and text property information, and determine a design type within the identified design item.

Determining the design type may determine the design type of the design extracted by tying the design according to the design similarity within the design item through artificial intelligence (AI) analysis.

The recommendation ranking process may calculate a quantitative evaluation score according to the satisfaction of a predetermined quantitative evaluation index for each design type, and select a recommendation ranking of the design type according to the quantitative evaluation score.

The recommendation ranking process may calculate a user evaluation score according to the satisfaction of a preset user evaluation index for each design type, and select a recommendation ranking of the design type according to the user evaluation score.

The recommendation ranking process may include calculating a quantitative evaluation score according to the satisfaction of a predetermined quantitative evaluation index for each design type; calculating a user evaluation score according to the satisfaction of a preset user evaluation index for each design type; For each design type, the recommendation ranking of the design type may be selected by adding up the quantitative evaluation score and the user evaluation score.

The recommendation ranking process may include calculating a quantitative evaluation score according to the satisfaction of a predetermined quantitative evaluation index for each design type; calculating a user evaluation score according to the satisfaction of a preset user evaluation index for each design type; By applying different weights for each design type to the quantitative evaluation score and the user evaluation score, respectively, the weighted quantitative evaluation score and the user evaluation score may be added to select a recommendation ranking of the design type.

The sequentially providing for each design item in the design type recommendation list providing process may include: a design type recommendation process of providing a design type recommendation list in any one design item; a design type selection process in which a user selects any one design type from the design type recommendation list; a subsequent design type recommendation process of providing a design type recommendation list in a subsequent design item matching the design type selected by the user; a subsequent design type selection process in which a user selects any one design type from the design type recommendation list in the subsequent design item; and a process in which the subsequent design type recommendation process and the subsequent design type selection process are repeatedly performed until there is no subsequent design item to be recommended or there is a user's request for termination.

In the design type recommendation process and the subsequent design type recommendation process, a list of design items is arranged on the screen, and when any one design item is selected by the user, a design type recommendation list matching the selected design item can be displayed on the screen. have.

By disposing the design item list on the screen, only design items that meet a preset design item display condition may be included in the design item list.

The design item display condition may be characterized in that the design item selection ratio of users exceeds a preset selection threshold.

According to an embodiment of the present invention, by monitoring the act of making a work in real time in a cloud environment and recommending and providing a design that matches it, it is possible for a user to easily create a work according to the current trend.

In addition, according to an embodiment of the present invention, by sequentially providing a recommendation list for each design item, it is possible to efficiently recommend another design item most suitable for the design item selected by the user in the previous step.

In addition, according to an embodiment of the present invention, by determining a design type through artificial intelligence (AI) analysis of works registered in a cloud environment and generating a recommendation ranking using an evaluation index, accurate recommendation ranking calculation is possible.

1 is a block diagram illustrating a design recommendation system through cloud work analysis according to an embodiment of the present invention.

2 is a functional block diagram of a design recommendation system through cloud work analysis according to an embodiment of the present invention.

3 is a flowchart illustrating a design recommendation method through cloud work analysis according to an embodiment of the present invention.

4 is an exemplary diagram illustrating a state in which selections are made sequentially from a design type recommendation list according to an embodiment of the present invention.

5 is an exemplary diagram in which a layout suitable for a resolution selected by a user is recommended according to an embodiment of the present invention;

6 is an exemplary diagram in which a list of design items is displayed on a screen according to an embodiment of the present invention;

7 is an exemplary diagram of design items that may belong to a work according to an embodiment of the present invention.

8 is an exemplary diagram in which design typeization and recommendation ranking selection are made according to an embodiment of the present invention.

9 is an exemplary diagram of a quantitative evaluation index according to an embodiment of the present invention.

10 is an exemplary diagram of a user evaluation index according to an embodiment of the present invention.

Hereinafter, the advantages and features of the present invention, and a method of achieving them, will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in a variety of different forms, and is provided to fully inform those of ordinary skill in the art to the scope of the invention As such, the invention is only defined by the scope of the claims. In addition, in the description of the present invention, if it is determined that related known technologies may obscure the gist of the present invention, detailed description thereof will be omitted.

1 is a block diagram illustrating a design recommendation system through cloud work analysis according to an embodiment of the present invention, and FIG. 2 is a functional block diagram of a design recommendation system through cloud work analysis according to an embodiment of the present invention.

As used herein, the term "design" refers to components when creating works such as PPT files, word files, document files, and contents, and includes resolution, layout information, font information, shape information, image information, and color in the work. It is used as a concept that includes all elements of various works such as information, chart information, and graph information.

The present invention monitors the act of making a work in a cloud environment in real time and recommends and provides a design matching it.

To this end, in the cloud environment, documents prepared by various users are analyzed to classify design types, and the frequency of use is measured by establishing specific standards for various design elements included in documents. At this time, considerations may include the resolution (size) of the document, the number of types of design elements (text, images, figures, diagrams, images, music) included in the document, and coordinate values placed on each page of the document. .

In addition, it tracks the creation activity of users who create works such as content and documents in real time. The user can input document settings such as specifying resolution, place design elements on the page and input values, and can also change actions that change design element properties (color, shape, border, size, etc.) All these series of design activities will be tracked in the cloud.

And by comparing the design generated through analysis with the user's authoring activity, high-ranking designs are recommended in real time. For example, if the user sets the resolution, popular templates (layouts) are shown at the selected resolution so that the user can select them. do. It will be described in detail below.

The design recommendation system through cloud work analysis of the present invention may include a wired/wireless communication network 100 , a user terminal 200 , and a design recommendation server as shown in FIG. 1 .

The wired/wireless communication network 100 is a communication network that provides wired communication or wireless communication between the user terminal 200 and the design recommendation server. When such a wired/wireless communication network 100 is implemented as a wireless communication network, a wireless mobile communication network consisting of a base transceiver station (BTS), a mobile switching center (MSC), and a home location register (HLR) is provided. can be used for data communication. In addition, when the wired/wireless communication network 100 is implemented as a wired communication network, it may be implemented as a network communication network, and data communication may be performed according to an Internet protocol such as TCP/IP (Transmission Control Protocol/Internet Protocol).

The user terminal 200 is a terminal used by a user who produces works such as documents and contents, and in the drawings, a desktop PC (desktop PC) is described as an example, but not only a desktop PC but also a smart phone, A tablet PC (tablet PC), a slate PC (slate PC), a notebook computer (notebook computer) and the like may be applicable. Of course, the terminal to which the present invention is applicable is not limited to the above-described types, and it is natural that all terminals capable of communicating with an external device may be included.

The user terminal 200 performs an act of making a work through a web (WEB) in a cloud network. Accordingly, the user terminal 200 selects a design type from the user from the design type recommendation list sequentially provided for each design item from the design recommendation server to produce the work.

The conventional web (WEB) has been focused on providing a web page or website that shows specific information composed of text, picture, sound, or video to the user, but the recent web is gradually changing into an application form. . That is, the recent web is provided in the form of a computer application rather than a simple web page (or web site), so that the user terminal 200 can create a work on the web (WEB).

The design recommendation server monitors in real time an act of making a work performed in the user terminal 200 connected through the web on the cloud network, and recommends and provides a design matching the same. To this end, the design recommendation server has the same configuration as a general web server in terms of hardware to implement the above-described operation, and in terms of software, through various languages such as C, C++, Java, Visual Basic, Visual C, etc. It contains program modules that are implemented and perform various functions. In addition, it can be implemented using web server programs that are provided in various ways according to operating systems such as DOS, Windows, Linux, Unix, and Macintosh on general server hardware. have.

The dictionary definition of cloud is 'a service that stores data in a central computer connected to the Internet and can use data anytime and anywhere as long as it connects to the Internet'. The work result is updated in real time to the design recommendation server of the present invention through the cloud.

Therefore, as shown in FIG. 2 , the design recommendation server tracks and monitors in real time the act of making a work performed in the user terminal 200 connected to the cloud network, and the design type according to the authoring activity of the user connected to the design recommendation server A design type recommendation list according to the recommendation ranking is provided sequentially for each design item.

In addition, after registering and storing the work when the act of making a work in the user terminal 200 is finished through the cloud network, monitoring and analyzing the work to be finally registered due to the end of the act of making a work, a design type recommendation list for each design item will create

Here, in the work analysis and design type recommendation list generation, the design included in the work is extracted by analyzing the work to be updated and registered, and then the extracted design is classified by design item to determine the design type. Then, each determined design type is evaluated according to a preset evaluation index, a design type recommendation ranking is determined for each design item, and a design type recommendation list is generated for each design item based on the design type recommendation ranking. Hereinafter, it will be described in detail together with FIGS. 3 to 10 .

3 is a flowchart illustrating a design recommendation method through cloud work analysis according to an embodiment of the present invention, and FIG. 4 is an exemplary diagram illustrating a state in which a selection is made sequentially from a design type recommendation list according to an embodiment of the present invention 5 is an exemplary diagram in which a layout suitable for a resolution selected by a user is recommended according to an embodiment of the present invention, and FIG. 6 is an exemplary illustration in which a list of design items is displayed on the screen according to an embodiment of the present invention, FIG. 7 is an exemplary illustration of design items that may belong to a work according to an embodiment of the present invention, FIG. 8 is an exemplary illustration in which design typification and recommendation ranking selection are made according to an embodiment of the present invention, and FIG. 9 is an embodiment of the present invention An exemplary diagram of a quantitative evaluation index according to an example, and FIG. 10 is an exemplary diagram of a user evaluation index according to an embodiment of the present invention.

The design recommendation method through cloud work analysis of the present invention, as shown in FIG. 3, includes a work monitoring process (S310), a design type recommendation list providing process (S320), a work production process (S330), and a work registration process (S340) , it may include a registered work analysis process (S350).

The work monitoring process ( S310 ) is a process in which the design recommendation server tracks and monitors in real time an act of making a work performed in the user terminal 200 connected to the cloud network. A user who creates a work such as content or document may input a setting value of the work, such as specifying the resolution of the work, or place a design element on a page and input a value. In addition, behaviors that change the properties (color, shape, border, size, etc.) of design elements are changed, and all of these actions are monitored and tracked in the cloud in real time.

The design type recommendation list providing process ( S320 ) is a process in which the design recommendation server sequentially provides a design type recommendation list according to the design type recommendation ranking for each design item in accordance with the authoring activity of the user accessing the design recommendation server.

It is to recommend high-ranking designs in real time by comparing the design with the user's work-making behavior through analysis of works created by other users. For example, when a user selects a specific resolution, a list of popular templates (layouts) in the selected resolution is displayed so that the user can select from them.

Here, sequentially providing for each design item in the design type recommendation list providing process ( S320 ) includes a design type recommendation process ( S321 ) of providing a design type recommendation list in any one design item, and a design type recommendation list from a user in the design type recommendation list. A design type selection process (S322) in which any one design type is selected, a subsequent design type recommendation process (S323) of providing a design type recommendation list in a subsequent design item matching the design type selected by the user (S323), and a subsequent design item Subsequent design type selection process (S324) in which a user selects any one design type from the design type recommendation list in , and subsequent design items to be recommended by the subsequent design type recommendation process (S323) and the subsequent design type selection process (S324) There may be a process that is repeatedly performed until there is no end request (S325) of the user.

For example, as shown in FIG. 4 , when a user selects any one specific resolution in a state in which the resolution recommendation list is provided, a layout recommendation list arranged in the order of the most used layouts on the selected resolution is displayed. For example, as shown in FIG. 5 , when the user selects a resolution or designates a number, a right window appears and a layout suitable for the resolution selected by the user is recommended. In this case, the recommended layout is not a fixed result value, but the documents typed in square resolution in the user gallery are exposed in the order of the highest value by the evaluation index. Since there is a weight for the period in the evaluation index, a layout suitable for the recently produced trend is recommended first.

Similarly, when the user selects any one specific layout from the recommended layout recommendation list, a color recommendation list arranged in the order of the most used colors in the selected layout is displayed. When the user selects any one specific figure from the color recommendation list, a font recommendation list arranged in the order of the most used fonts in the selected color is displayed. The user selects a favorite typeface from the typeface recommendation list, and similarly, various design selections are repeated. In this way, it is possible to sequentially select design items such as resolution, layout, color, font, and the like.

On the other hand, in the design type recommendation process (S321) and the subsequent design type recommendation process (S323) described above, as shown in FIG. 6 , a list of design items is arranged on the screen, and any one design item is selected by the user. It may be implemented to display a design type recommendation list matching the selected design item on the screen. For example, when the user selects a figure in the left object panel, a rectangular figure is placed on the screen. Judging this behavior as “the intention to create a button,” the button style is recommended in the right panel. The button style can also be displayed by first exposing the results that fit the latest trend by extracting typified design elements from the user gallery.

Furthermore, arranging the design item list on the screen allows only design items that meet the preset design item display condition to be included in the design item list. Here, the design item display condition may be a condition in which a design item selection ratio of users exceeds a preset selection threshold. For example, only design items previously selected by 85% or more of users are provided with a design type recommendation list, and design items selected by less than 85% of existing users are not provided with a design type recommendation list.

This is because, if a design type recommendation list is provided for each design item for selection, it may have too many selection steps and cause user inconvenience. Therefore, it is recommended to provide a design type recommendation list only for design items used mainly by users. , and the rest of the design items are to provide a design type recommendation list only when the user wants it.

On the other hand, the work production process ( S330 ) is a process in which the user terminal 200 selects one design type from the user from the design type recommendation list sequentially provided for each design item, and produces the work. For example, if the user selects a specific resolution, a list of popular templates (layouts) in the selected resolution is displayed, and if any one template (layout) is selected by the user, the selected template (layout) is provided and the user You can create a work by inputting the text or picture you need in the template (layout).

In the work registration process (S340), the design recommendation server registers and stores the work through the cloud network when the work production action performed in the user terminal 200 is ended. The act of making a work and the result of the work that the user works on the user terminal 200 are updated in real time to the design recommendation server of the present invention through the cloud network.

The registered work analysis process ( S350 ) generates a design type recommendation list for each design item by monitoring and analyzing the work that is finally registered due to the design recommendation server and the end of the work production action. For example, it is to generate a design type recommendation list for each design item sorted in the order of the most used design types by analyzing the design trends that people currently use the most with respect to the works of people updated through the cloud. .

To this end, the registered work analysis process ( S350 ) may include a design extraction process ( S351 ), a design type determination process, a recommendation ranking process ( S353 ), and a design type recommendation list generation process ( S354 ).

The design extraction process ( S351 ) is a process in which the design recommendation server analyzes the work to be updated and registered through the cloud and extracts the design included in the work. The work registered in the cloud includes the elements shown in Figure 7, and through this, similarity and frequency of use can be measured. If the work is made of HTML, it may be possible to distinguish more clearly due to the characteristics of the programming language. The design items may correspond to type, basic setting information, layout information, color information, image information, figure property information, text property information, and the like, as shown in FIG. 7 .

The design type determination process is a process in which the design recommendation server classifies the extracted design by design item to determine the design type. That is, the design type determination process ( S352 ) identifies which design item the extracted design belongs to among design items including type, basic setting information, layout information, color information, image information, shape property information, and text property information, In other words, it is the process of determining the design type within the identified design items. That is, as shown in FIG. 8, each design item is categorized based on the registered work. Although it is simply classified into three in FIG. 8 , they may be classified according to each item of the evaluation index to be described later. Each typed list can be distinguished, for example, in a design in which red is used a lot, in a layout in which the title text is largely centered.

Determining such a design type enables implementation to determine the design type of the extracted design by tying the design according to the design similarity within the design item through artificial intelligence (AI) analysis.

A typographical model can be established for the classification of works, and the typographical model can also be directly learned through artificial intelligence (AI) analysis technology through the items of the analysis index;

Alternatively, the developer may make a hypothesis and input it during the system development stage. In recent artificial intelligence (AI) analysis technology, if the amount of data is sufficient, artificial intelligence (AI) can create a model by itself, but the amount of data may be insufficient and users' behavior can be sufficiently guessed, so it is expected to be tangible. It is to pre-enter values (layout, color, resolution, etc.) and to type data with similar values.

Hereinafter, examples of typology of registered works are described.

(1) Examples of typography in the case of layout and resolution

In the case of a layout that means a certain arrangement or arrangement of design elements, it has a certain pattern as shown in the figure on the right. The nature of the text is constant with the title, subheading, and main body, and it is arranged horizontally and vertically in two or three columns, including images. The pages of each document can be typed as shown in the figure on the right, and can be typed by analyzing the similarity of the layout. In the case of resolution, it can be divided into a long horizontal shape, a long vertical shape, and a square shape, and the possible layouts will vary depending on these resolution settings.

(2) Examples of typography in the case of color use and color arrangement

In most design elements used in works, color plays an important role. There is a tendency to use a certain color in the design of the work, and there are better color matching factors. The color can be used not only for the background color of the page, but also for text, shapes, SVG icons, etc. Although color exists in images and videos, it is difficult to trace in HTML, which can be supplemented through image recognition technology.

(3) Examples of typography for charts or graphs

In the case of charts or graphs, it is possible to type them into bar graphs, line graphs, circle shapes, donut shapes, etc. Even within a consistent type, additional design elements such as color arrangement or shape change, text arrangement, etc. are required a lot, and shapes and lines can be arranged in various ways in detail.

On the other hand, after the design type determination process (S352), a recommendation ranking process (S353) is performed. The recommendation ranking determining process ( S353 ) is a process in which the design recommendation server evaluates each design type according to a preset evaluation index, and determines the design type recommendation ranking for each design item.

After the recommendation ranking process ( S353 ), a design type recommendation list generation process ( S354 ) is performed. In the design type recommendation list generation process ( S354 ), the design recommendation server selects the design type recommendation list based on the design type recommendation ranking. It is the process of creating by design item.

Meanwhile, in determining the design type recommendation ranking in the recommendation ranking process ( S353 ), an efficient recommendation ranking selection criterion is needed in consideration of the types of various works. To this end, the recommendation ranking can be determined in four ways: quantitative evaluation, user evaluation, quantitative + user evaluation, and weight evaluation as follows.

The first method, quantitative evaluation, is a method of calculating a quantitative evaluation score according to the satisfaction of a preset quantitative evaluation index for each design type, and selecting a recommendation ranking of the design type according to the quantitative evaluation score. That is, it is evaluated by giving a score based on the quantitative evaluation index shown in FIG. 9, where the quantitative evaluation index is the project title, project description, tags, copyright, disclosure scope, number of pages, number of images, project XML capacity, etc. This may apply.

The second method, user evaluation, is a method of calculating a user evaluation score according to the satisfaction of a preset user evaluation index for each design type, and selecting a recommendation ranking of the design type according to the user evaluation score. That is, the evaluation is performed by giving a score based on the user evaluation index shown in FIG. 10, where the user evaluation index may correspond to the number of views, the number of interests, the number of shares, the number of reuses, the staff's pick, the weekly best, and the like.

The third method, quantitative + user evaluation, calculates a quantitative evaluation score according to the satisfaction of a preset quantitative evaluation index for each design type, and, in addition, a user evaluation score according to the satisfaction of a preset user evaluation index for each design type to calculate And, for each design type, the quantitative evaluation score and the user evaluation score are summed to select the design type recommendation ranking. Rather than using any one evaluation score, the recommendation ranking is selected as the sum total of the quantitative evaluation score and the user evaluation score.

The fourth method, weight evaluation, calculates a quantitative evaluation score according to the satisfaction of a preset quantitative evaluation index for each design type, and calculates a user evaluation score according to the satisfaction of a preset user evaluation index for each design type do. In addition, weights set differently for each design type are applied to the quantitative evaluation score and the user evaluation score, respectively, and the weighted quantitative evaluation score and the user evaluation score are summed to select a recommendation ranking for the design type. For this reason, it is necessary to increase the quantitative evaluation rate or increase the user evaluation rate depending on the design type. Taking this into consideration, different weights are applied to the quantitative evaluation score and the user evaluation score for each design type, and the quantitative evaluation score to which these weights are applied It is evaluated by summing the user evaluation score and the user evaluation score.

The embodiments in the above description of the present invention are presented by selecting and presenting the most preferred examples to help those skilled in the art understand from among various possible examples, and the technical spirit of the present invention is not necessarily limited or limited only by this embodiment. , various changes and modifications and equivalent other embodiments are possible without departing from the technical spirit of the present invention.

100: Wired and wireless communication network (cloud network)

200: user terminal

300: design recommendation server

Claims

a work monitoring process in which the design recommendation server tracks and monitors in real time an act of making a work performed in a user terminal connected to the cloud network;

a design type recommendation list providing process in which the design recommendation server sequentially provides a design type recommendation list for each design item according to the design type recommendation ranking according to the authoring activity of a user who has accessed the design recommendation server;

a work production process in which the user terminal selects a design type from a user from a design type recommendation list sequentially provided for each design item and produces a work;

a work registration process in which the design recommendation server registers and stores the work through the cloud network when the work production action performed in the user terminal is terminated;

a registered work analysis process in which the design recommendation server generates a design type recommendation list for each design item by monitoring and analyzing the work to be finally registered due to the end of the work production act;

Design recommendation method through cloud asset analysis, including.
The method according to claim 1, The registered work analysis process,

a design extraction process in which the design recommendation server analyzes the work to be updated and registered through the cloud and extracts a design included in the work;

a design type determination process in which the design recommendation server classifies the extracted designs by design items to determine a design type;

a recommendation ranking determining process in which the design recommendation server evaluates each design type according to a preset evaluation index, and determines a design type recommendation ranking for each design item;

a design type recommendation list generation process in which the design recommendation server generates a design type recommendation list for each design item based on the design type recommendation ranking;

Design recommendation method through cloud asset analysis, including.
3. The method according to claim 2,

The design item includes at least one of type, basic setting information, layout information, color information, image information, figure property information, and text property information,

The design type determination process includes identifying which design item belongs among the design items including the extracted design type, basic setting information, layout information, color information, image information, figure property information, and text property information, and the identified design Design recommendation method through cloud asset analysis to determine the design type within the item.
The method according to claim 3, determining the design type,

Design recommendation method through cloud work analysis that determines the design type of the extracted design by categorizing the design according to the design similarity within the design item through artificial intelligence (AI) analysis.
The method according to claim 2, The recommendation ranking process,

A design recommendation method through cloud work analysis for calculating a quantitative evaluation score according to the satisfaction of a preset quantitative evaluation index for each design type, and selecting a recommendation ranking for a design type according to the quantitative evaluation score.
The method according to claim 2, The recommendation ranking process,

A design recommendation method through cloud work analysis for calculating a user evaluation score according to the satisfaction of a preset user evaluation index for each design type, and selecting a recommendation ranking for a design type according to the user evaluation score.
The method according to claim 2, The recommendation ranking process,

a process of calculating a quantitative evaluation score according to the satisfaction of a preset quantitative evaluation index for each design type;

calculating a user evaluation score according to the satisfaction of a preset user evaluation index for each design type;

A design recommendation method through cloud work analysis that selects a design type recommendation ranking by adding up the quantitative evaluation score and user evaluation score for each design type.
The method according to claim 2, The recommendation ranking process,

a process of calculating a quantitative evaluation score according to the satisfaction of a preset quantitative evaluation index for each design type;

calculating a user evaluation score according to the satisfaction of a preset user evaluation index for each design type;

A design recommendation method through cloud work analysis in which weights set differently for each design type are applied to the quantitative evaluation score and the user evaluation score, respectively, and the weighted quantitative evaluation score and the user evaluation score are added to select a recommendation ranking for the design type.