KR102396110B1 - Method, Apparatus and System for Interlocking Between Heterogeneous Shopping Mall - Google Patents

Abstract

A method, apparatus, and system for interworking between heterogeneous shopping malls are disclosed. In the interworking method between heterogeneous shopping malls, a performance planning module for receiving a request to perform a specific task through a second shopping mall from a first shopping mall and automatically performing the task through a second shopping mall in response to the request is stored in the database It is checked whether or not there is, and if it is confirmed that the academic performance plan module exists in the database, the performance plan module can be performed.

Description

Interlocking method between heterogeneous shopping malls {Method, Apparatus and System for Interlocking Between Heterogeneous Shopping Mall}

The present invention relates to a method, apparatus and system for interworking between heterogeneous shopping malls, and more particularly, to a method, apparatus and system for interworking between heterogeneous shopping malls that can easily and automatically link operations between shopping malls based on different platforms. it's about

In recent years, the popularization of online communication such as the Internet has drastically changed the commerce environment more than ever. Now, to the extent that the word online or internet shopping itself is unfamiliar and the word internet or online feels like an unnecessary modifier, e-commerce through online is being activated. In addition, the expansion trend of the online e-commerce market is expected to further expand.

As online e-commerce companies, ie, shopping malls that sell products online, increase exponentially, shopping malls are working hard to link data with various platforms to strengthen their image and expand their business. For example, a shopping mall implemented based on a specific platform intends to link services of a heterogeneous shopping mall implemented based on a heterogeneous platform to its own shopping mall through interworking with the heterogeneous platform.

In general, interworking of heterogeneous platforms with shopping malls is based on collecting and processing an application programming interface (API). For example, a shopping mall identifies and collects APIs corresponding to a target platform for a specific service. If there is no corresponding API, the shopping mall must request to provide the API to the target shopping mall.

However, in this case, a considerable amount of time is required from requesting to provide API to receiving API. In addition, since the production of AIP is performed by a professional manpower, cost and time are consumed, and even if an API is collected from a target shopping mall or an API is provided, there is a difficulty in responding to and maintaining an issue when an issue occurs in the corresponding service. Therefore, there is an urgent need to develop a solution capable of easily performing interworking between heterogeneous shopping malls.

Patent Publication No. 2012-0020502

The present invention is to solve this problem, and provides a method, apparatus, and system for interworking between heterogeneous shopping malls that can easily and automatically perform service interworking between shopping malls based on different platforms based on X-Pass, which is absolute location information of elements. Its purpose is to provide

In order to achieve this object, in one aspect, the present invention provides a method of interworking between heterogeneous shopping malls. The interworking method between the heterogeneous shopping malls may include: receiving a request from a first shopping mall to perform a specific task through a second shopping mall, performed by a server interworking with a plurality of shopping malls; in response to the request, checking whether an execution plan module for automatically performing the task through the second shopping mall exists in the database; and when it is confirmed that the execution planning module exists in the database in the checking step, performing the execution planning module. The execution plan module includes at least one unit module, wherein the unit module includes a URL (Universal Resource Locator) of a web page of the second shopping mall associated with the unit task, information indicating the type of the unit task, and the unit task. It may include information indicating an action sequence and xpath information for performing the unit task.

The interworking method between the heterogeneous shopping malls further includes displaying an icon indicating whether or not a specific task is to be performed through the second shopping mall in the first shopping mall, and receiving the request according to the selection of the icon. can The icon may be associated with identification information indicating the second shopping mall.

The interworking method between the heterogeneous shopping malls may include: extracting Hypertext Mark-up Language (HTML) data from a web page of the second shopping mall when it is determined that the execution plan module does not exist in the checking step; collecting Xpass data corresponding to elements included in the web pages from the extracted HTML data; classifying the collected X-Pass data by associated X-Pass data based on the learned artificial intelligence model; modularizing the classified X-Pass data; The method may further include generating the task performing module based on the modularized X-Pass data.

The collected X-Pass data may include a Universal Resource Locator (URL) that is link information of the web page; keywords corresponding to elements; a tag type corresponding to the element; tag information corresponding to the element; and an X-pass value that is an absolute position value corresponding to the element.

The interworking method between the heterogeneous shopping malls may further include learning the artificial intelligence model, and the learning of the artificial intelligence model may include: extracting HTML data from a learning web page of a learning target shopping mall; collecting X-pass data corresponding to elements included in the learning webpage from HTML data extracted from the learning webpage; learning, by the artificial intelligence model, based on X-Pass data corresponding to elements included in the learning web page, so as to classify the X-Pass data according to characteristic information and keyword information corresponding to the X-Pass data; and storing the learned artificial intelligence model in a database.

The database interworking with the artificial intelligence model includes, for each element, a keyword corresponding to the element; a vector value corresponding to characteristic information and keyword information of the element; a similar keyword group corresponding to the element; a tag type corresponding to the element; an original creation date corresponding to the element; and a table including the most recent update date corresponding to the element may be managed.

The classifying may include: extracting characteristic information of the X-pass data based on link information of the X-pass data; determining a similar keyword group based on the keywords of the X-pass data; The method may include grouping the X-pass data for each associated X-pass data based on the characteristic information and the similar keyword group.

The task performing module may be configured to receive input data for the task from the first shopping mall, and automatically input the input data to a location requesting the input data on a web page of the second shopping mall when the task is performed. there is.

Meanwhile, in order to achieve the above object of the present invention, in another aspect, there is provided an interworking device between heterogeneous shopping malls. The interworking device between the heterogeneous shopping malls may include: a receiving unit receiving a request from a first shopping mall to request that a specific task be performed through a second shopping mall; and in response to the request, it is checked whether an execution planning module for automatically performing the task through the second shopping mall exists in the database, and when it is confirmed that the execution planning module exists in the database, the execution plan It may include an execution unit that executes the module.

The execution plan module includes at least one unit module, wherein the unit module includes a URL (Universal Resource Locator) of a web page of the second shopping mall associated with the unit task, information indicating the type of the unit task, and the unit task. It may include information indicating an action sequence and xpath information for performing the unit task.

The interworking device between heterogeneous shopping malls may further include a display unit for displaying an icon indicating whether a specific task is to be performed through the second shopping mall in the first shopping mall. The receiver may receive the request as the icon is selected. The icon may be associated with identification information indicating the second shopping mall.

The interworking device between the heterogeneous shopping malls may include: an extraction unit configured to extract HTML (Hypertext Mark-up Language) data from a web page of the second shopping mall when it is confirmed that the execution plan module does not exist; a collection unit for collecting X-pass data corresponding to elements included in the web pages from the extracted HTML data; a classification unit for classifying the collected X-Pass data by associated X-Pass data based on the learned artificial intelligence model; a modularization unit for modularizing the classified X-Pass data; and a task performing module generator configured to generate the task performing module based on the modularized X-Path data.

The collected X-Pass data may include a Universal Resource Locator (URL) that is link information of the web page; keywords corresponding to elements; a tag type corresponding to the element; tag information corresponding to the element; and an X-pass value that is an absolute position value corresponding to the element.

The interworking device between the heterogeneous shopping malls may further include a learning unit for learning an artificial intelligence model. The learning unit extracts HTML data from a learning web page of a learning target shopping mall, collects X-pass data corresponding to elements included in the learning web page from the HTML data extracted from the learning web page, and X-pass data The artificial intelligence model is trained based on the X-Path data corresponding to the elements included in the learning web page so as to classify the relevant X-Path data according to the characteristic information and keyword information corresponding to the Intelligence models can be stored in a database.

The database interworking with the artificial intelligence model includes, for each element, a keyword corresponding to the element; a vector value corresponding to characteristic information and keyword information of the element; a similar keyword group corresponding to the element; a tag type corresponding to the element; an original creation date corresponding to the element; and a table including the most recent update date corresponding to the element may be managed.

The classification unit may be configured to extract characteristic information of the X-pass data based on link information of the X-pass data, determine a similar keyword group based on a keyword of the X-pass data, and select the characteristic information and the similar keyword group. Based on the X-pass data, the X-pass data may be grouped according to the associated X-pass data.

The task performing module may be configured to receive input data for the task from the first shopping mall, and automatically input the input data to a location requesting the input data on a web page of the second shopping mall when the task is performed. there is.

Meanwhile, in order to achieve the above object of the present invention, in another aspect, the present invention provides an interworking system between heterogeneous shopping malls. The interworking system between the heterogeneous shopping malls includes: a first shopping mall; a second shopping mall; and a performance planning module that receives a request from the first shopping mall to perform a specific task through the second shopping mall, and in response to the request, automatically performs the task through the second shopping mall. and a server executing the execution planning module when it is confirmed that the execution planning module exists in the database.

The execution plan module includes at least one unit module, wherein the unit module includes a URL (Universal Resource Locator) of a web page of the second shopping mall associated with the unit task, information indicating the type of the unit task, and the unit task. It may include information indicating an action sequence and xpath information for performing the unit task.

The server may display an icon indicating whether or not to perform a specific task through the second shopping mall in the first shopping mall, and receive the request according to the selection of the icon. The icon may be associated with identification information indicating the second shopping mall.

When it is confirmed that the execution plan module does not exist, the server extracts HTML (Hypertext Mark-up Language) data from the web page of the second shopping mall, and includes it in the web pages from the extracted HTML data Collecting X-Pass data corresponding to the elements to be used, classifying the collected X-Pass data for each associated X-Pass data based on the learned AI model, modularizing the classified X-Pass data, and performing the modularization process The job may be created based on the Xpass data.

On the other hand, in order to achieve the above object of the present invention, in another aspect, the present invention comprises the steps of: receiving, in a computer, a request to perform a specific operation from a first shopping mall through a second shopping mall; in response to the request, checking whether an execution plan module for automatically performing the task through the second shopping mall exists in the database; and when it is confirmed that the execution planning module exists in the database in the checking step, performing the execution planning module - The execution planning module includes at least one unit module, wherein the unit module is associated with a unit task URL (Universal Resource Locator) of the web page of the second shopping mall, information indicating the type of the unit operation, information indicating the action sequence of the unit operation, and xpath information for performing the unit operation - A computer program stored in the medium is provided to execute the

As described above, according to the present invention, service interworking between shopping malls based on different platforms can be easily and automatically performed based on xpath, which is absolute location information of an element. Accordingly, a seller performing sales in a shopping mall can easily sell products in a completely different shopping mall based on a heterogeneous platform in addition to the shopping mall currently selling.

1 is a block diagram showing the configuration of a system for realizing a method for interworking between heterogeneous shopping malls according to a preferred embodiment of the present invention.
FIG. 2 is a block diagram for explaining the detailed configuration of the service server shown in FIG. 1 , and shows the configuration of an interworking device between heterogeneous shopping malls according to a preferred embodiment of the present invention.
3 to 4 are flowcharts illustrating an operation flow of an interworking device between heterogeneous shopping malls, and illustrate an interworking method between heterogeneous shopping malls according to a preferred embodiment of the present invention.
5 is an exemplary diagram illustrating an example of displaying a request icon on a product sale webpage of a first shopping mall.
6 is an exemplary diagram illustrating another example of displaying a request icon in the first shopping mall.
7 exemplarily shows a user interface used to extract HTML tags and text data.
8 exemplarily shows a user interface used to extract link data.
9 is an exemplary diagram illustrating Xpass data of elements collected by a service server.
10 is an exemplary diagram exemplarily illustrating a collection list of X-pass data of elements included in a web page.
11 is a flowchart illustrating a classification procedure performed by a classification unit of a service server.
12 shows data managed by interworking with an artificial intelligence model in a database in response to X-Pass data.
13 is a table exemplarily illustrating a list of data managed by FIG. 12 .
14 is a diagram illustrating data managed in a database in association with a modularization unit.
15 is an exemplary diagram illustrating a list of data managed by FIG. 14 .
16 is a diagram exemplarily showing information on a unit module included in a task execution module.
17 is a diagram illustrating a table associated with job performance information managed in association with the job performance module.
18 is a flowchart for explaining a procedure for learning an artificial intelligence model by a service server.
19 shows a user interface for inputting a set value for a platform that a user wants to collect and register.
20 exemplarily illustrates a user interface through which an operator can check related contents as needed in the process of collecting X-Pass according to the setting value registered on the page and then automatically processing collection and registration.

Since the present invention can have various changes and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the present invention to specific embodiments, and it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention.

Terms such as first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

When a component is referred to as being 'connected' or 'connected' to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in between. it should be On the other hand, when it is mentioned that a certain element is 'directly connected' or 'directly connected' to another element, it should be understood that the other element does not exist in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as 'comprise' or 'have' are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, and one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the accompanying drawings. In describing the present invention, in order to facilitate the overall understanding, the same reference numerals are used for the same components in the drawings, and duplicate descriptions of the same components are omitted.

1 is a block diagram showing the configuration of a system for realizing a method for interworking between heterogeneous shopping malls according to a preferred embodiment of the present invention.

As shown in FIG. 1 , the service server 100 may cooperate with a plurality of shopping malls, for example, a first shopping mall M1 and a second shopping mall M2. The shopping malls are built based on different heterogeneous platforms. Here, the shopping mall may include all types of online shopping malls that sell products through online. For example, the shopping mall may include an open market shopping mall such as Amazon, Auction, Interpark, etc., a large shopping mall such as a department store shopping mall, an outlet shopping mall, and a personal shopping mall operated with a unique domain. In addition, if a shopping mall sells products, various forms such as SNS, blog, online cafe or community may be included in the category.

The service server 100 interworks with the shopping malls of these different platforms, and enables the work performed in the first shopping mall M1 to be performed in the second shopping mall M2 so that the different types of shopping malls can be linked. .

For example, the service server 100 allows a seller who performs sales in the first shopping mall M1 to also sell products in the second shopping mall M2 of a platform completely different from the first shopping mall M1. The above operation may be various types of operations such as not only selling products but also changing user information, logging in, purchasing products, updating posts, and the like. In this embodiment, among these operations, an operation related to the sale of a product will be described as an example.

FIG. 2 is a block diagram for explaining the detailed configuration of the service server 100 shown in FIG. 1 , and shows the configuration of an interworking device between heterogeneous shopping malls according to a preferred embodiment of the present invention. 3 to 4 are flowcharts illustrating an operation flow of an interworking device between heterogeneous shopping malls, and illustrate an interworking method between heterogeneous shopping malls according to a preferred embodiment of the present invention.

As shown in FIG. 2 , the service server 100 includes a receiving unit 110 , a display unit 120 , a performing unit 130 , an extracting unit 140 , a collecting unit 150 , a classifying unit 160 , and a modularizing unit. 170 , a task performing module generating unit 180 , a learning unit 200 and a database 190 , and the like.

The service server 100 may be built based on at least one computer terminal. The computer terminal may be a server-class computer including a memory for storing a program, a processor for executing a program stored in the memory, an input unit for inputting information, an output unit for outputting information, and the like. The respective units may be interoperable and may be constructed based on at least one computer terminal.

Hereinafter, a preferred embodiment of the present invention will be described with reference to FIGS. 1 to 4 . In the description of the embodiment with reference to FIGS. 1 to 4 , it is assumed that the user is a seller of a product that sells a product through the first shopping mall M1, and the user sells the product sold at the first shopping mall M1 to the first shopping mall M1 ( It is assumed that there is also a desire to sell in the second shopping mall M2, which is operated based on a platform system completely different from that of M1).

In other words, it is assumed that the first shopping mall M1 is a shopping mall where the user is currently selling, and the second shopping mall M2 is a target shopping mall that is a shopping mall of a heterogeneous platform that the user wants to sell. That is, the second shopping mall M2 is a term that refers to a target shopping mall, and may actually be one shopping mall or a plurality of shopping malls.

First, the display unit 120 of the service server 100 may display an icon inquiring whether or not to perform a specific task in the first shopping mall M1 through the second shopping mall M2 (step: S1) . For example, in the description of the present embodiment, the specific operation may be to perform sales through the second shopping mall M2. The icon may be associated with identification information indicating the second shopping mall M2. Then, the user may select, for example, click or touch the displayed icon (step: S2).

5 is an exemplary diagram illustrating an example of displaying a request icon on a product sale webpage of the first shopping mall M1.

As shown in FIG. 5 , a guide phrase such as “Would you like to sell this product at the second shopping mall?” is displayed on one side of the product sales webpage of the first shopping mall M1, and such a message is displayed in an adjacent part of the guide phrase. A request icon IC1 for requesting is displayed. That is, the request icon IC1 is displayed in association with identification information indicating the second shopping mall M2, for example, the phrase.

When the user selects, for example, clicks or touches the icon IC1 , a request signal for requesting that the product sold in the first shopping mall M1 be sold in the second shopping mall M2 may be generated. The request signal may include identification information of the first shopping mall M1, identification information of the second shopping mall M2, and product identification information.

5 shows an example of displaying a request icon in the first shopping mall M1 by designating a target shopping mall to be sold in advance. Meanwhile, the display unit 120 may display a user interface so that the user can select the second shopping mall M2, which is the target shopping mall. 6 is an exemplary diagram illustrating another example of displaying a request icon in the first shopping mall M1.

As shown in FIG. 6 , the display unit 120 may display a user interface to select a second shopping mall M2, which is a target shopping mall, in the first shopping mall M1. For example, if the user selects the icon IC2 for selecting the second shopping mall M2 from the list, a list of the plurality of second shopping malls M2 is displayed, and the second shopping mall M2 desired by the user from the list is displayed. ) to be selected. When the second shopping mall M2 is selected, a request signal for requesting that products sold in the first shopping mall M1 be sold in the selected second shopping mall M2 may be generated.

For example, when the user selects the icon IC3 for directly inputting the second shopping mall M2 from the list, an input window is displayed for the user to input the identification information of the desired second shopping mall M2, , may receive identification information of the second shopping mall M2, for example, a Universal Resource Locator (URL), a name, and the like, from the user's input. When the identification information of the second shopping mall M2 is input, the display unit 120 requests a request to sell the product sold in the first shopping mall M1 in the second shopping mall M2 corresponding to the input identification information. may occur.

Meanwhile, there may be a plurality of products to be sold. In this case, the display unit 120 displays the product list or input window to be sold in the second shopping mall M2 in the first shopping mall M1, and the user selects or inputs products to be sold based on the displayed product list or input window. can

As shown in FIG. 3 , the receiving unit 110 of the service server 100 may receive a request from the first shopping mall M1 to perform a specific task through the second shopping mall M2 (step S). :S3). For example, the request may be a request to sell at least one product sold in the first shopping mall M1 through the second shopping mall M2. In this case, the request may include identification information of the first shopping mall M1, identification information of the second shopping mall M2, identification information of at least one product, and the like.

The performing unit 130 of the service server 100, in response to the received request, determines whether a task performing module for automatically performing the task through the second shopping mall M2 exists in the database 190 or not. can be confirmed (step: S4). As a result of the confirmation, if it is confirmed that the task performing module exists in the database 190, the task performing module may be performed (step: S5).

On the other hand, if it is confirmed that the task performing module does not exist in the database 190, procedures for creating the task performing module may be performed. As shown in FIG. 4 , first, the extraction unit 140 of the service server 100 receives HTML (Hypertext Mark-up Language) from the web page of the second shopping mall M2 for interworking with the first shopping mall M1. Data can be extracted (step: S11).

For example, the service server 100 may extract HTML data from a web page of the second shopping mall M2 for product sales. Here, the web page for product sale may be any web page necessary for the product sales procedure in the second shopping mall M2, such as log-in, product sale, stock check, payment, and order status check.

The collection unit 150 may collect xpath data corresponding to elements included in the web page from the extracted HTML data (step: S12). The X-pass data may include an X-pass that is absolute position information of a corresponding element. The X-pass may mean a unique path value for a specific element in the HTML document.

According to a preferred embodiment of the present invention, the service server 100 uses the Xpass scraping method as described above. X-pass scraping may mean automatically extracting and collecting X-passer information corresponding to a unique path value corresponding to an element. When an API provision request, which has been pointed out in the conventional problem described above, needs to be received or it is impossible to provide, by using the Xpass scraping method, not only the limitation of the accessible platform disappears, but also time and cost resources can be significantly reduced.

7 exemplarily shows a user interface used for extracting HTML tags and text data, and FIG. 8 exemplarily shows a user interface used for extracting link data.

9 is an exemplary diagram illustrating X-pass data of elements collected by the service server 100 . 10 is an exemplary diagram exemplarily illustrating a collection list of X-pass data of elements included in a web page. The X-pass data collected in this way is stored and managed in the database 190 .

As shown in FIG. 9 , the collected X-Pass data includes “URL” which is a URL (Universal Resource Locator) that is link information of the web page, “Title” which is a keyword corresponding to an element, and a tag type corresponding to the element. It may include "Tag_type", "Tag_info" which is tag information (or tag name) corresponding to the element, and "xpath" which is an X-path value that is an absolute position value corresponding to the element.

As shown in FIG. 10 , X-pass data corresponding to a plurality of elements collected from a web page of a link “Cafe24.com/prdctregister” may be collected. For example, the Xpass value of a sale status radio button that selects to sell on a webpage on the link "Cafe24.com/prdctregister" could be "//[@id="eDescriptionADDOptionM"], so the element's unique path The absolute position of an element can be known through the value of the axpath.

Next, the classification view of the service server 100 may classify the collected X-Pass data for each associated X-Pass data based on the learned artificial intelligence model (step: S13).

11 is a flowchart illustrating a classification procedure performed by the classification unit 160 of the service server 100 .

11 , the classification unit 160 may extract characteristic information of the X-pass data based on link information of the X-pass data based on an artificial intelligence model (step: S21 ) ). The classification unit 160 may determine a similar keyword group based on the keywords of the X-pass data based on the artificial intelligence model (step: S22). Next, the classifying unit 160 may group the X-Path data according to the associated X-Pass data based on the characteristic information and the similar keyword group based on the artificial intelligence model (step: S23).

12 shows data managed in conjunction with an artificial intelligence model in the database 190 in response to X-Pass data. 13 is a table exemplarily illustrating a list of data managed by FIG. 12 .

As shown in FIG. 12 , for each element, “Title” is a keyword corresponding to an element, “Vec_Result” is a result of a vector value corresponding to the characteristic information of the element and keyword information, and is a similar keyword group corresponding to the element. A table including "Synonym_Family", a tag type corresponding to the element "Tag_type", an initial creation date corresponding to the element "Created_date", and a recent update date corresponding to the element "Updated_date" is an artificial intelligence model It may be managed in the database 190 in association with the .

As shown in FIG. 13 , for the "login submission image" element, the keyword "login", a vector value, a group of similar keywords, such as "Login, Log in, login, ...", tag type "Submit image", initially created The date "2019-01-01", the latest update date "2019-01-28", etc. are managed, and list data of each element can be managed in the form of a table.

Then, the modularization unit 170 may modularize the classified X-Pass data (step: S14). Here, data of related elements with similar characteristics and keywords can be correlated. 14 is a diagram illustrating data managed in the database 190 in association with the modularization unit 170 . 15 is an exemplary diagram illustrating a list of data managed by FIG. 14 .

As shown in FIG. 14 , in the modularized data, a table including “Title” indicating a keyword of an element and “Tag_type” indicating a tag type of an element may be managed by the database 190 . As shown in FIG. 15 , the keyword “login” and the tag type “submit” may be managed for the first element of the list that is the login submission element.

Next, the task performing module generating unit 180 may generate a task performing module for performing a specific task in the second shopping mall M2 based on the modularized X-Pass data (step S15).

The task execution module may be, for example, a type of batch file that automatically performs a task requested from the first shopping mall M1 in the second shopping mall M2. The task performing module may include at least one unit module. For example, assuming that the requested operation is to sell a product in the second shopping mall M2, various operations such as logging in, product registration, product list collection, inventory check, sales reception, etc. Tasks must be performed, and the task performing module corresponding to the unit tasks for performing the task may be referred to as a unit module. The unit module may be a batch file for performing unit operations.

16 is a diagram exemplarily showing information on a unit module included in a task execution module. 17 is a diagram illustrating a table associated with job performance information managed in association with the job performance module.

As shown in FIG. 16 , the unit module includes "Target_URL" which is the URL of the target web page, "Plan_type" which is the action type information, "Action_tpye" which is the action type information, "Action_No" which is the action order information, and the action target X It may include "Target xpath" which is path information.

17 , in order to perform a task, the task performing module may manage information of a plurality of unit modules. For example, here, the action order of the unit module is determined according to the action order information.

Next, the performing unit 130 of the service server 100 may perform the task performing module (step: S16). Then, the task performing module may automatically perform the task requested by the user in the second shopping mall M2. For example, the task execution module logs the user into the second shopping mall M2 so that products sold in the first shopping mall M1 can be sold at the second shopping mall M2, and the user's second shopping mall M2 ) can perform a series of unit operations for product sales by registering the product.

The task performing module receives input data required for the task from the first shopping mall M1, and automatically inputs the input data to a position where the input data is requested on the web page of the second shopping mall M2 when the task is performed. can do.

For example, for login, user information (eg, ID, password) is received from the first shopping mall M1 and automatically entered into the user information input unit of the login web page of the second shopping mall M2, and then the login button is selected. After logging in, receiving product information from the first shopping mall M1, inputting the product information to a required location in the product registration unit of the second shopping mall M2, and selecting a registration button to register the product.

The input data from the first shopping mall M1 may be received by the task execution module by requesting it from the first shopping mall M1 in real time, or by receiving input data registered in advance from the first shopping mall M1, the database ( 190) and then used when performing work.

Therefore, according to a preferred embodiment of the present invention, it is possible to provide a service that enables easy interworking with a target shopping mall without checking and collecting APIs corresponding to platforms of heterogeneous target shopping malls or requesting provision. Time and human resources can be significantly reduced in terms of system development, deployment and maintenance.

Meanwhile, the learning unit 200 of the service server 100 may learn an artificial intelligence model. 18 is a flowchart illustrating a procedure for learning an artificial intelligence model by the service server 100 .

As shown in FIG. 18 , the learning unit 200 may extract HTML data from the learning web page of the learning target shopping mall (step S31). The learning unit 200 may collect X-Pass data corresponding to elements included in the learning web page from the HTML data extracted from the learning web page (step: S32).

Next, the learning unit 200 is configured to classify the X-pass data according to the associated X-pass data according to the characteristic information and keyword information corresponding to the X-pass data, so that the artificial intelligence model is X-pass corresponding to the elements included in the learning web page. It can learn based on the pass data (step: S33). The learning unit 200 may store the learned artificial intelligence model in the database 190 (step: S34).

The learning target shopping mall may be the second shopping mall M2 requested by the user of the first shopping mall M1, but may be a plurality of shopping malls in addition to the requested second shopping mall M2. That is, the learning target shopping mall may be a plurality of shopping malls, and as the number of learning target shopping malls increases, the accuracy of classification may also increase.

19 shows a user interface in which a user inputs a set value for a platform desired to be collected and registered. 20 exemplarily shows a user interface through which an operator can check related contents as needed, in which X-pass collection is performed according to the registered setting value through the user interface and subsequent collection and registration are automatically processed.

Although the present invention has been described by exemplifying preferred embodiments thereof, those skilled in the art can variously modify and change the present invention within the scope without departing from the technical matters and scope of the present invention described in the claims below. It will be understood that it can be implemented. Accordingly, modifications of future embodiments of the present invention will not depart from the teachings of the present invention.

M1: No. 1 Shopping Mall
M2: 2nd shopping mall
100 : service server
110: receiver
120: display
130: attendant
140: extraction unit
150: collection unit
160: classification unit
170: modularization unit
180: task execution module generation unit
190 : database
200: study department

Claims (23)

It is performed by a server linking with a plurality of shopping malls,
receiving a request from the first shopping mall to request that a specific operation be performed through a second shopping mall;
in response to the request, checking whether an execution plan module for automatically performing the task through the second shopping mall exists in the database; and
When it is confirmed that the execution planning module exists in the database in the checking step, performing the execution planning module,
The performance planning module includes at least one unit module,
The unit module includes a URL (Universal Resource Locator) of the web page of the second shopping mall associated with the unit operation, information indicating the type of the unit operation, information indicating the action sequence of the unit operation, and X for performing the unit operation contains path (xpath) information;
The operation is an operation of selling at least one product of the first shopping mall through the second shopping mall,
and displaying a request icon for requesting to sell the product through the second shopping mall on one side of the product sale web page of the first shopping mall.
The method of claim 1, further comprising: displaying an icon indicating whether a specific task is to be performed through the second shopping mall in the first shopping mall;
The interworking method between heterogeneous shopping malls, characterized in that receiving the request according to the selection of the icon.
The method of claim 2, wherein the icon is associated with identification information indicating the second shopping mall.
The method according to claim 1, wherein when it is confirmed that the execution plan module does not exist in the checking step,
extracting HTML (Hypertext Mark-up Language) data from the web page of the second shopping mall;
collecting Xpass data corresponding to elements included in the web pages from the extracted HTML data;
classifying the collected X-Pass data by associated X-Pass data based on the learned artificial intelligence model;
modularizing the classified X-Pass data;
The interworking method between heterogeneous shopping malls, further comprising the step of generating the execution plan module based on the modularized X-Pass data.
5. The method of claim 4, wherein the collected X-Pass data comprises:
URL (Universal Resource Locator) which is link information of the web page;
keywords corresponding to elements;
a tag type corresponding to the element;
tag information corresponding to the element; and
The interworking method between heterogeneous shopping malls, characterized in that it includes an X-pass value that is an absolute position value corresponding to the element.
According to claim 4, further comprising the step of learning the artificial intelligence model,
The step of learning the artificial intelligence model is,
extracting HTML data from a learning web page of a learning target shopping mall;
collecting X-pass data corresponding to elements included in the learning webpage from HTML data extracted from the learning webpage;
learning, by the artificial intelligence model, based on X-Pass data corresponding to elements included in the learning web page, so as to classify the X-Pass data according to characteristic information and keyword information corresponding to the X-Pass data; and
and storing the learned artificial intelligence model in a database.
5. The method of claim 4, wherein the database interworking with the artificial intelligence model is
For each element,
keywords corresponding to elements;
a vector value corresponding to characteristic information and keyword information of the element;
a similar keyword group corresponding to the element;
a tag type corresponding to the element;
an original creation date corresponding to the element; and
The interworking method between heterogeneous shopping malls, characterized in that the table including the latest update date corresponding to the element is managed.
The method of claim 4, wherein the classifying comprises:
extracting characteristic information of the Xpass data based on link information of the Xpass data;
determining a similar keyword group based on the keywords of the X-pass data;
and grouping the X-pass data for each associated X-pass data based on the characteristic information and the similar keyword group.
According to claim 1, wherein the performance planning module,
between heterogeneous shopping malls, characterized in that receiving input data for the task from the first shopping mall, and automatically inputting the input data to a location requesting the input data on a web page of the second shopping mall when the task is performed linkage method.
a receiving unit for receiving a request from the first shopping mall to request that a specific operation be performed through a second shopping mall; and
In response to the request, it is checked whether an execution planning module for automatically performing the task through the second shopping mall exists in the database, and when it is confirmed that the execution planning module exists in the database, the execution planning module Including an execution unit that performs
The performance planning module includes at least one unit module,
The unit module includes a URL (Universal Resource Locator) of the web page of the second shopping mall associated with the unit operation, information indicating the type of the unit operation, information indicating the action sequence of the unit operation, and X for performing the unit operation contains path (xpath) information;
The operation is an operation of selling at least one product of the first shopping mall through the second shopping mall,
and a request icon for requesting to sell the product through the second shopping mall is displayed on one side of a product sale web page of the first shopping mall.
11. The method of claim 10, further comprising: a display unit for displaying an icon indicating whether a specific task is to be performed through the second shopping mall in the first shopping mall;
and the receiving unit receives the request according to the selection of the icon.
The companion device of claim 11 , wherein the icon is associated with identification information indicating the second shopping mall.
The method of claim 10, wherein when it is confirmed that the performance planning module does not exist,
an extraction unit for extracting HTML (Hypertext Mark-up Language) data from the web page of the second shopping mall;
a collection unit for collecting X-pass data corresponding to elements included in the web pages from the extracted HTML data;
a classification unit for classifying the collected X-Pass data by associated X-Pass data based on the learned artificial intelligence model;
a modularization unit for modularizing the classified X-Pass data; and
The interworking device between heterogeneous shopping malls, further comprising a module generator generating the execution plan module based on the modularized X-Pass data.
14. The method of claim 13, wherein the collected X-Pass data comprises:
URL (Universal Resource Locator) which is link information of the web page;
keywords corresponding to elements;
a tag type corresponding to the element;
tag information corresponding to the element; and
and an X-pass value that is an absolute position value corresponding to the element.
The method of claim 13, further comprising a learning unit for learning the artificial intelligence model,
The learning unit,
Extracting HTML data from a learning web page of a learning target shopping mall, collecting X-pass data corresponding to elements included in the learning web page from the HTML data extracted from the learning web page, and corresponding to the X-pass data In order to classify the related X-Path data according to information and keyword information, the artificial intelligence model is trained based on X-Path data corresponding to elements included in the learning web page, and the learned artificial intelligence model is stored in a database. A linkage device between heterogeneous shopping malls, characterized in that it is stored in the .
14. The method of claim 13, wherein the database interworking with the artificial intelligence model is
For each element,
keywords corresponding to elements;
a vector value corresponding to characteristic information and keyword information of the element;
a similar keyword group corresponding to the element;
a tag type corresponding to the element;
an original creation date corresponding to the element; and
The interworking device between heterogeneous shopping malls, characterized in that the table including the latest update date corresponding to the element is managed.
The method of claim 13, wherein the classification unit,
Extracting characteristic information of the Xpass data based on link information of the Xpass data, determining a similar keyword group based on a keyword of the Xpass data, and determining the X-pass data based on the characteristic information and the similar keyword group A companion device between heterogeneous shopping malls, characterized in that the pass data are grouped according to the associated X-pass data.
The method of claim 10, wherein the performance planning module,
between heterogeneous shopping malls, characterized in that receiving input data for the task from the first shopping mall, and automatically inputting the input data to a location requesting the input data on a web page of the second shopping mall when the task is performed interlocking device.
first shopping mall;
a second shopping mall; and
Whether there is an execution planning module in the database that receives a request from the first shopping mall to perform a specific task through the second shopping mall, and in response to the request, automatically performs the task through the second shopping mall To check whether or not, and if it is confirmed that the execution planning module exists in the database, including a server that performs the execution planning module,
The performance planning module includes at least one unit module,
The unit module includes a URL (Universal Resource Locator) of the web page of the second shopping mall associated with the unit operation, information indicating the type of the unit operation, information indicating the action sequence of the unit operation, and X for performing the unit operation contains path (xpath) information;
The operation is an operation of selling at least one product of the first shopping mall through the second shopping mall,
and displaying a request icon for requesting to sell the product through the second shopping mall on one side of a product sale web page of the first shopping mall.
The method of claim 19, wherein the server,
and displaying an icon indicating whether a specific task is to be performed through the second shopping mall in the first shopping mall, and receiving the request according to the selection of the icon.
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