A job recommendation method, system and related device

Abstract

The present application provides a job recommendation method, system and related devices. The method relates to the field of cloud computing. The method is executed by a job recommendation system, which includes a recommendation device and a component device. The component device includes an agent component and multiple business components, and the agent component is loaded onto the business system. The method includes: the agent component obtains the user's operation page information and the user's identification on the business system, and sends the operation page information and the user's identification to the recommendation system; the recommendation system determines the recommended content and the number of the target business component used to carry the recommended content based on the operation page information and the user's identification, and sends the recommended content and the number of the target business component to the agent component; the agent component obtains the target business component corresponding to the number from the target node, so that the business system presents the recommended content through the target business component. The job recommendation method provided by the present application is universal, and the operation, maintenance and management costs of the entire system are low.

Description

Technical Field

[0001] The present application relates to the field of cloud computing, and in particular to a job recommendation method, system, and related devices. Background Art

[0002] To enhance the intelligence of the task system, user behavior and user data are used to predict user behavior or analyze user preferences. This allows the system to provide users with auxiliary pages during the task process to help them complete their tasks better and faster. For example, when a user enters information on a system, the system will recommend related information to the user, allowing the user to select the correct information from the related information and enter it into the system to complete the task more quickly.

[0003] At present, the auxiliary pages recommended to users by the job recommendation system are all customized. For example, in one application scenario, the marketing system, sales system, and customer service system all have multiple business functions. The marketing system, sales system, and customer service system correspond to a job recommendation system, and the job recommendation system is used to provide job assistance for each business function in the marketing system, sales system, and customer service system. Different business functions in the same system have different corresponding auxiliary pages, and different systems also have different corresponding auxiliary pages. Currently, the recommended auxiliary pages are all customized and developed by the job recommendation system according to the various business functions of each business system, that is, the auxiliary pages for different business functions are customized and developed through different program codes. This customized development method leads to high subsequent operation and maintenance and management costs. Summary of the Invention

[0004] The present application provides a job recommendation method, system and related devices. By adopting the method of the present application, the recommended auxiliary pages / recommendation pages do not need to be customized and developed for different business systems and different business functions in the same business system, which facilitates subsequent operation and maintenance and management, and has low operation and maintenance and management costs.

[0005] In a first aspect, the present application provides a job recommendation method, which is performed by a job recommendation system comprising a recommendation device and a component device. The component device comprises a proxy component and multiple business components. The proxy component is loaded into the business system and is used to obtain information about user interactions with the business system, including information about the operation pages used by users in the business system and the input objects entered on the operation pages, and transmits this information to the recommendation device. The proxy component is also used to obtain information sent by the recommendation device, such as recommended content, where the recommended content is determined by the recommendation device based on the operation page information and the input objects. The business component, on the other hand, is used to indicate the presentation medium required to present the recommended content on the user interface. The business system presents the recommended content through the adapted business component, allowing users to view the recommended content and perform other actions based on the recommended content. As can be seen, the present application provides a new system architecture. In this new system architecture, the proxy component and business components in the component device are deployed independently and are not integrated with the recommendation device. The proxy component is used to obtain the operation page information and the input object entered by the user on the business system. The recommendation device is used to determine the recommended content for the user based on the operation page information and the input object entered by the user. The business component is used to carry the recommended content and display the recommended content on the business system through the business component.

[0006] The traditional method is to develop recommendation pages for different business functions in the recommendation system through code customization. Different business systems use different front-end technology stacks, the size of the display page is also different, and the application program interface required to display the auxiliary page is different; different business functions also have different page styles. Therefore, the recommended content and display method for each business function are implemented through code customization in the recommendation system, and the display method is transmitted to the front-end page of the business system through the application program interface. The method of the present application deploys the component devices independently, and the agent component provides a unified application program interface to the outside world. Different business systems can load the agent component through the unified application program interface and display the recommended content through the adapted business component, avoiding the problem of customized development of recommendation pages due to different front-end technology stacks and inconsistent page styles of different business systems. The method of the present application overcomes the problem of different technology stacks of different business systems and realizes the provision of recommendation pages / auxiliary pages across technology stacks. The job recommendation method provided by the present application has wide applicability and strong versatility, and is easy to operate and manage, with low operation and management costs.

[0007] Based on the first aspect, in a possible implementation method, the recommendation device represents the user's operation on the operation page of the business system through a standard behavior model according to the URL of the operation page, and then obtains the associated data of the input object, the associated data including the attribute information of the input object, and determines the recommended content based on preset rules according to the standard behavior model and the associated data of the input object.

[0008] It can be understood that the user's operations on the business system are represented by a unified standard behavior model to facilitate processing by the recommendation device.

[0009] Based on the first aspect, in a possible implementation, the business system includes multiple business objects, each business object has one or more business types, and each business type of each business object corresponds to a URL of an operation page;

[0010] The recommendation device represents the user's operation on the operation page of the business system through a standard behavior model based on the URL of the operation page and the user's ID, including:

[0011] The recommendation device represents the user's operation through a standard behavior model by matching the URL of the operation page and the user's identifier with a preconfigured function tree; the standard behavior model includes the user's identifier, the business object operated by the user, and the business type of the business object operated by the user. The function tree lists the correspondence between multiple business objects contained in the business system, one or more business types of each of the multiple business objects, and the URL of the operation page corresponding to each business type of each business object.

[0012] Based on the first aspect, in a possible implementation, the recommendation device and the component device are both located in the cloud.

[0013] In a second aspect, the present application provides a job recommendation system for providing recommendation services to a business system in which a user is working. The job recommendation system includes a recommendation device and a component device. The component device includes an agent component and multiple different business components. The business components are used to indicate the presentation carrier required for presenting data on a user interface (UI). The presentation carriers indicated by the multiple different business components are different. Each business component has a unique number. The agent component is loaded into the business system and includes:

[0014] The proxy component is used to obtain the user's operation page information and the user's identification on the business system, wherein the operation page information includes the uniform resource locator URL of the operation page and the input object of the user on the operation page, and send the operation page information and the user's identification to the recommendation device;

[0015] The recommendation device is used to determine the recommended content and the number of the target business component for carrying the recommended content based on the operation page information and the user's identification based on preset rules, and send the recommended content and the number of the target business component to the proxy component;

[0016] The proxy component is further used to obtain the target business component corresponding to the number from the component device;

[0017] The business system is used to present recommended content through target business components so that users can take actions based on the recommended content.

[0018] Based on the second aspect, in a possible implementation, it is recommended that the device is used to:

[0019] Based on the URL of the operation page and the user's ID, the user's operation on the operation page of the business system is represented by a standard behavior model;

[0020] Obtaining associated data of an input object, where the associated data includes attribute information of the input object;

[0021] Recommended content is determined based on preset rules according to the standard behavior model and the associated data of the input object.

[0022] Based on the second aspect, in a possible implementation, the business system includes multiple business objects, each business object has one or more business types, and each business type of each business object corresponds to a URL of an operation page;

[0023] The recommendation device is used to represent the user's operation through a standard behavior model by matching the URL of the operation page and the user's identifier with a preconfigured function tree; the standard behavior model includes the user's identifier, the business object operated by the user, and the business type of the business object operated by the user. The function tree lists the correspondence between multiple business objects included in the business system, one or more business types of each of the multiple business objects, and the URL of the operation page corresponding to each business type of each business object.

[0024] Based on the second aspect, in a possible implementation, the recommendation device and the component device are both located in the cloud.

[0025] In a third aspect, the present application provides a computing device cluster, comprising at least one computing device, wherein the at least one computing device includes a memory and a processor, and the processor of the at least one computing device is used to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the method described in the above-mentioned first aspect and any possible implementation of the first aspect.

[0026] In a fourth aspect, the present application provides a computer storage medium comprising program instructions. When the program instructions are executed by a computing device cluster, the computing device cluster implements the method described in the first aspect and any possible implementation of the first aspect.

[0027] In a fifth aspect, the present application provides a computer program product comprising program instructions. When the program instructions are executed by a computing device cluster, the computing device cluster implements the method described in the first aspect and any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of the system architecture provided for this application;

[0029] Figure 2 A flowchart of a recommended method for this application;

[0030] Figure 3 A flow chart of a method for determining recommended content provided in this application;

[0031] Figure 4 A schematic diagram of the structure of a function tree provided for this application;

[0032] Figure 5 A schematic diagram of a standard user behavior model provided in this application;

[0033] Figure 6 A schematic diagram of a set of metadata provided for this application;

[0034] Figure 7 This is an example diagram of a scenario provided for this application;

[0035] Figure 8 A schematic diagram of the structure of a job recommendation system provided for this application;

[0036] Figure 9 A schematic diagram of the structure of a computing device provided in this application;

[0037] Figure 10 A schematic diagram of the structure of a computing device cluster provided in this application. DETAILED DESCRIPTION

[0038] This application provides a system, such as Figure 1 As shown, Figure 1This is a schematic diagram of the system architecture provided for this application. This system involves a job recommendation system and a business system, wherein the job recommendation system includes a recommendation device and component devices. In this system architecture, the business system includes any one or more of the marketing system, sales system, and customer service system. In actual applications, the business system can also be other application systems, and this application does not limit this.

[0039] The component device includes an agent component, which provides a uniform resource locator (URL). The marketing system, sales system, and customer service system can load the agent component from the component device via the URL. The component device is located in the cloud.

[0040] When the agent component is loaded onto the business system, and when the user operates on the business system, the agent component is used to obtain the user's operation page information and the user's identification on the business system. The business system may include any one or more of a marketing system, a sales system, and a customer service system. The user operates on the business system. For example, the user may create an opportunity point on the front-end page of the sales system. Accordingly, the agent component obtains the opportunity point page information created by the user on the front-end page of the sales system. For another example, the user may create a seal application on the front-end page of the sales system. Accordingly, the agent component obtains the page information of the seal application created by the user on the front-end page of the sales system. The agent component is also used to send the operation page information and the user's identification to the recommendation device.

[0041] Among them, the proxy component can be implemented using module federation and web components technology. Module federation is a technology used in front-end architecture that allows different front-end applications to share resources. For example, by using module federation technology, the front-ends of the marketing system, the sales system, and the customer service system can share proxy components, eliminating the need to repeatedly implement the functionality of the proxy components through code when developing the marketing system, sales system, and customer service system. Web components are a set of technologies natively supported by browsers that aim to help developers create well-encapsulated user interface (UI) components. Web components provide standardized application programming interfaces (APIs) for cross-platform use. The core idea of proxy components is to reduce duplication of front-end applications in business systems by exposing interfaces and sharing functions, allowing proxy components to be flexibly applied in different business systems and reducing maintenance costs.

[0042] The recommendation device is configured to receive the operation page information and user identifier sent by the proxy component, analyze the operation page information and user identifier based on preset rules, and determine recommended content and the target business component number for carrying the recommended content. The recommendation device is further configured to send the recommended content and the target business component number to the proxy component, which is further configured to obtain the target business component corresponding to the number from the component device. The business system presents the recommended content to the user via the target business component, allowing the user to take action based on the recommended content.

[0043] The component device also includes the correspondence between the codes and numbers of multiple business components. The business component can be presented through the code of the business component. The component device includes the codes of multiple business components, which can be roughly understood as including multiple business components on the component device. The business component is used to indicate the presentation carrier required for presenting data on the user interface UI, and the presentation carriers indicated by different business components are different. Each business component has a unique number, and the component device stores the correspondence between the codes of multiple business components and the numbers of the business components. When the agent component obtains the number of a business component, the component device sends the code of the business component corresponding to the number to the recommendation device.

[0044] Optionally, the proxy component is further configured to receive user feedback on the recommended content on the front-end page of the business system, which may be user acceptance or rejection of the recommended content, and send the feedback to the recommendation device. The recommendation device is further configured to update the preset rules based on the user feedback.

[0045] In one application scenario, the recommendation device and the component device are both located in the cloud. The recommendation device and the component device can be located on a computing node in the cloud or on different computing nodes in the cloud. The computing node can be any one of a bare metal server, a virtual machine, a container, etc.

[0046] Optionally, the backend of the business system can also be located in the cloud. Customers can log in to the business system by logging into a webpage on their terminal devices and perform operations on the business system. The business system can include one or more of a marketing system, a sales system, and a customer service system. The recommendation device, component device, and business system are services provided by the same cloud service provider. Customers purchase the services provided by the cloud service provider so that the job recommendation system can provide job recommendation services to the business system.

[0047] Alternatively, the business system can be deployed as an application integration package on the customer's terminal device, meaning the backend of the business system is located on the customer's terminal device. In this scenario, the proxy component can be deployed as a program package on the customer's terminal device. When the business system starts, it calls the proxy component on the terminal device, which retrieves information about the user's operating page within the business system and the user's ID.

[0048] Figure 1 This is a system architecture example diagram provided by this application. Figure 1 The description of the system architecture content does not constitute a limitation of this application.

[0049] This application provides a job recommendation method, see Figure 2 , Figure 2 This is a flow chart of a method for job recommendation provided in this application. The method can be performed by Figure 1 The job recommendation system in the application is executed. The job recommendation system includes a recommendation device and a component device. The component device includes an agent component and multiple business components. The agent component is loaded into the business system. The following describes the job recommendation method provided by this application, including but not limited to the following description.

[0050] 201: The proxy component obtains the user's operation page information on the business system and the user's identifier, wherein the operation page information includes the uniform resource locator URL of the operation page and the input object of the user on the operation page.

[0051] A business system can be any system with business functions, such as Figure 1 One or more of the marketing system, sales system and customer service system.

[0052] After the proxy component is loaded into the business system, when the user performs operations on the front-end page of the business system, the proxy component can obtain the user's operation page information and the user's identification. The user identification can be information used to uniquely identify the user's identity, for example, it can be the user's name or the user's identity identification number. The operation page information includes the URL of the operation page and the input object of the user on the operation page. For example, the user's operation includes creating an opportunity point on the sales system and entering the opportunity point name on the operation page. The URL of the operation page is the URL of the sales system's create opportunity point page, and the input object is the opportunity point name. For another example, the user's operation includes creating a seal application on the sales system and entering the name or number of the customer who needs the seal on the operation page. The URL of the operation page is the URL of the sales system's create seal application page, and the input object is the name or number of the customer who needs a seal. It should be noted that the user's input object on the operation page can be one or more. The operation page information can also include other information.

[0053] 202: The agent component sends the operation page information and the user's identification to the recommendation device.

[0054] 203: The recommendation device determines the recommended content and the number of the target service component for carrying the recommended content based on the operation page information and the user's identifier and preset rules.

[0055] Business components are the presentation medium required to present data on the user interface (UI). The recommendation device determines the recommended content and the target business component ID for the recommended content based on preset rules, based on the URL of the operation page, the user's input object on the operation page, and the user's identity.

[0056] Optionally, this step can be achieved by the following method: Figure 3 As shown, Figure 3 This is a flow chart of a method for determining recommended content provided by this application, and the method includes but is not limited to the following description.

[0057] 2031: The recommendation device represents the user's operation on the operation page of the business system through a standard behavior model according to the URL of the operation page and the user's identifier.

[0058] It can be understood that a business system includes multiple business objects, each of which has one or more business types, and each business type of each business object corresponds to a URL for an operation page. For example, a business system includes a marketing system, a sales system, and a customer service system. Business objects include marketing tasks in the marketing system, and the business types can be create marketing tasks, modify marketing tasks, and view marketing tasks. Each business type has a URL for an operation page. Business objects also include seal applications in the sales system, and the business types can be create seal applications, modify seal applications, and view seal applications. Each business type has a URL for an operation page. Business objects also include work orders, and the business types can be create work orders, modify work orders, and view work orders. Each business type has a URL for an operation page.

[0059] The recommendation device can determine the business object and business type based on the URL of the operation page obtained. Specifically, the recommendation device matches the URL of the operation page with the pre-configured function tree to determine the business object and business type. The function tree refers to the hierarchical and structured deployment of the functions of the business system into a tree structure. For example, see Figure 4 , Figure 4 This is a diagram of the structure of a function tree provided for this application. The function tree includes business objects such as marketing tasks, seal applications, and work orders. Marketing tasks, seal applications, and work orders all have three business types: create, modify, and view. Each business type of each business object has a URL for an operation page. Figure 4 The function tree shown is only an example. In actual applications, the function tree lists the correspondence between all business objects included in the business system, one or more business types of each business object, and the URL of the operation page corresponding to each business type of each business object.

[0060] If the URL of the operation page obtained by the recommended device is www.xxxxxxxx.com / mkt-task / create, compare the URL with Figure 4 Match the function tree in the , determine that the business object is a marketing task, and the business type is to create a marketing task; if the URL of the operation page obtained by the recommendation device is www.xxxxxxxx.com / mkt-task / edit, match the URL with Figure 4 Match the function tree in the , determine that the business object is a marketing task, and the business type is to modify the marketing task; if the URL of the operation page obtained by the recommendation device is www.xxxxxxxx.com / seal / create, match the URL with Figure 4 The function tree in the is matched to determine that the business object is a seal application and the business type is creating a seal application. xxxxxxxx can represent any character.

[0061] Furthermore, the recommendation device matches the URL of the operation page and the user's ID with the pre-configured function tree, thereby representing the user's operation through a standard behavior model. The standard behavior model includes the user's ID, the business object operated by the user, and the business type of the business object operated by the user. For example, Figure 5 A schematic diagram of a user's standard behavior model is shown in FIG. Figure 5 The standard behavior model shown in is an example and does not constitute a limitation of the standard behavior model.

[0062] 2032: Obtain associated data of the input object, where the associated data includes attribute information of the input object.

[0063] The recommendation device obtains the associated data of the input object, wherein the associated data includes the attribute information of the input object. For example, when a user creates an application for using a seal, the user enters the name of the customer who will use the seal on the operation page, and the recommendation device obtains the associated data of the customer's name, such as the customer's identification number, the customer's level, the customer's region, etc. For example, the customer who applied for using the seal is customer A, customer A's identification number is aaa, the customer's level is v2, and the customer's region is Beijing. The user only enters customer A on the operation page, and the recommendation device obtains other associated data of customer A. Alternatively, the user only enters customer A's identification number aaa on the operation page, and the recommendation device obtains other associated data of customer A. Among them, the customer's name, customer's identification number, customer's level, customer's region, etc. are all attribute information of the customer.

[0064] The recommendation device stores metadata, which includes objects associated with each business object. For example, Figure 6 A set of metadata. Figure 6 In the application, the business object is the application for using a seal. There are two types of objects associated with the application for using a seal: one is the customer, including all customers who may need to use a seal, and the other is the contracting entity, including all possible contracting entities. The contracting entity refers to the unit / enterprise / company to which the seal belongs. That is, there are two types of objects associated with the application for using a seal: one is the customer who needs to be stamped, and the other is the unit / enterprise / company to which the seal is stamped. It should be noted that in Figure 6 In the example, the metadata only stores one piece of customer information, such as the customer's name or the customer's identification number, but does not store all the customer's attribute information.

[0065] In one example, when the business object is a seal application and the user input object is customer A, the recommendation device obtains the associated data of customer A. In another example, when the business object is a marketing task and the user input object is an opportunity point, the recommendation device obtains the associated data of the opportunity point, which includes the opportunity point identifier, opportunity point name, and opportunity point space.

[0066] It is understood that the associated data of the input object is stored in a computing instance in the cloud, and the computing instance can be any one of a bare metal server, a virtual machine, a container, etc. The recommendation device obtains the associated data of the input object through an API interface.

[0067] It should be noted that metadata also includes data associated with other business objects, which is not limited here.

[0068] 2033: Determine recommended content based on preset rules according to the standard behavior model and the associated data of the input object.

[0069] The recommendation device determines the recommended content based on the preset rules according to the standard behavior model and the associated data of the input object. For example, Figure 7 In the example scenario diagram shown, the standard behavior model is:

[0070] User: Zhang San

[0071] Business object: Application for seal

[0072] Business Type: Create

[0073] The input object is the name of the customer, and the recommendation device obtains the associated data of the input object including:

[0074] Application for seal:

[0075] client:{

[0076] Identification number: account_001,

[0077] Level: v5,

[0078] Region: Shanghai

[0079] }

[0080] }

[0081] The preset rules include:

[0082] Conditions: Business Object = "Seal Application" AND Business Type = "Create or Modify" AND Seal Application.Customer.Region = "Shanghai";

[0083] Suggestion: Modify the properties of the object associated with the seal application - the contracting entity, to:

[0084] Based on the customer you selected, whose location is (region), we recommend you choose the following contracting entities:

[0085]

[0086] Recommended device based on Figure 7 Based on the standard behavior model and the associated data of the input object, the recommended content is determined based on the above preset rules:

[0087] Based on the customer you selected, whose location is (Shanghai), we recommend you choose the following contracting entities:

[0088]

[0089] The recommended content page diagram is as follows Figure 7 shown.

[0090] It should be noted that in Figure 7 In the example shown, the recommended content is one of the objects associated with the seal application, that is, the recommended content is one of the objects associated with the business object. In actual applications, the recommended content is not limited to objects associated with the business object, but can be other content, which is not limited in this application.

[0091] It can be understood that the preset rules are related to the business objects, business types, and associated data of the input objects in the standard behavior model. Specifically, the preset rules limit or constrain the associated data of the input objects according to the business types and business objects.

[0092] Optionally, the preset rules are also related to the user's identity in the standard behavior model. Different user identities, i.e., different user roles, may have different permissions. When users with different permissions operate on the business system, the recommended content may differ. Therefore, the preset rules are also related to the user's identity. 204: The recommendation device sends the recommended content and the target business component ID to the proxy component.

[0093] 205: The proxy component obtains the target service component corresponding to the number from the component device.

[0094] The component device stores the correspondence between the codes of multiple business components and their numbers. Business components are used to indicate the presentation medium required to present data on the user interface (UI). Different business components indicate different presentation mediums. It is understood that different presentation mediums are associated with different page content, page sizes, and page styles. The component device includes the codes of multiple business components, each with a unique number. The proxy component obtains the code of the target business component corresponding to the number from the component device.

[0095] The business system obtains the target business component's code through the proxy component. It can be understood that the target business component's code is used to present the target business component. Therefore, obtaining the target business component's code is equivalent to obtaining the target business component. The business system then presents recommended content through the target business component. Users view the recommended content and provide feedback on it on the business system's front-end page, either accepting or rejecting the recommendation. The proxy component also obtains user feedback on the recommended content and sends it to the recommendation device. The recommendation device then updates its pre-set rules based on the user feedback.

[0096] As can be seen, this application provides a new system architecture. In this new system architecture, the proxy component and business component in the component device are deployed independently and are not integrated with the recommendation device. The proxy component is used to obtain operation page information and user input objects on the business system. The recommendation device is used to determine recommended content for the user based on the operation page information and user input objects. The business component is used to carry the recommended content and display the recommended content on the business system through the business component.

[0097] The traditional method is to develop recommendation pages for different business functions in the recommendation system through code customization. Different business systems use different front-end technology stacks, the size of the display page is also different, and the application program interface required to display the auxiliary page is different; different business functions also have different page styles. Therefore, the recommended content and display method for each business function are implemented through code customization in the recommendation system, and the display method is transmitted to the front-end page of the business system through the application program interface. The method of the present application deploys the component devices independently, and the agent component provides a unified application program interface to the outside world. Different business systems can load the agent component through the unified application program interface and display the recommended content through the adapted business component, avoiding the problem of customized development of recommendation pages due to different front-end technology stacks and inconsistent page styles of different business systems. The method of the present application overcomes the problem of different technology stacks of different business systems and realizes the provision of recommendation pages / auxiliary pages across technology stacks. The job recommendation method provided by the present application has wide applicability and strong versatility, and is easy to operate and manage, with low operation and management costs.

[0098] The above describes the method embodiments provided by this application. The following introduces the device embodiments corresponding to the method embodiments.

[0099] This application provides a job recommendation system, see Figure 8 , Figure 8This is a schematic diagram of the structure of a job recommendation system 500 provided in this application. The job recommendation system 500 includes a recommendation device 510 and a component device 520. The component device 520 includes an agent component 521 and multiple business components 522. The business components 522 are used to indicate the presentation carrier required for data presentation on the user interface. Each business component 522 indicates a different presentation carrier and each business component 522 has a unique number. The agent component 521 is loaded into the business system. The job recommendation system 500 includes:

[0100] The proxy component 521 is used to obtain the user's operation page information and the user's ID on the business system, wherein the operation page information includes the uniform resource locator URL of the operation page and the input object of the user on the operation page, and send the operation page information and the user's ID to the recommendation device 510;

[0101] The recommendation device 510 is used to determine the recommended content and the number of the target business component for carrying the recommended content based on the operation page information and the user's identification based on preset rules, and send the recommended content and the number of the target business component to the proxy component 521;

[0102] The proxy component 521 is further configured to obtain a target business component corresponding to the number from the component device 520 , so that the business system presents the recommended content through the target business component.

[0103] In a possible implementation, the recommendation device 510 is used to:

[0104] Based on the URL of the operation page and the user's ID, the user's operation on the operation page of the business system is represented by a standard behavior model;

[0105] Obtaining associated data of an input object, where the associated data includes attribute information of the input object;

[0106] Recommended content is determined based on preset rules according to the standard behavior model and the associated data of the input object.

[0107] In a possible implementation, the business system includes multiple business objects, each business object has one or more business types, and each business type of each business object corresponds to a URL of an operation page;

[0108] The recommendation device 510 is used to represent the user's operation through a standard behavior model by matching the URL of the operation page and the user's identifier with a preconfigured function tree; the standard behavior model includes the user's identifier, the business object operated by the user, and the business type of the business object operated by the user. The function tree lists the correspondence between multiple business objects included in the business system, one or more business types of each of the multiple business objects, and the URL of the operation page corresponding to each business type of each business object.

[0109] In a possible implementation, the recommendation device 510 and the component device 520 are both located in the cloud.

[0110] The recommendation device 510 and component device 520 in the job recommendation system 500 can be implemented in software or hardware. For example, the implementation of the recommendation device 510 will be described below using the example of the recommendation device 510. Similarly, the implementation of the component device 520 can refer to the implementation of the recommendation device 510.

[0111] A module is an example of a software functional unit. The recommendation device 510 may include code running on a computing instance, wherein the computing instance may include, for example, a computing device, a virtual machine, a container, etc. Further, the computing instance may be one or more. For example, the recommendation device 510 may include code running on multiple computing devices / virtual machines / containers. It should be noted that the multiple computing instances used to run the code may be distributed in the same region or in different regions. Furthermore, the multiple computing instances used to run the code may be distributed in the same availability zone (AZ) or in different AZs, each AZ including one data center or multiple geographically close data centers. Generally, a region may include multiple availability zones (AZs).

[0112] Similarly, multiple compute instances used to run the code can be distributed within the same virtual private cloud (VPC) or across multiple VPCs. Typically, a VPC is set up within a region. Cross-region communication between two VPCs within the same region, or between VPCs in different regions, requires a communication gateway within each VPC to interconnect the VPCs.

[0113] A module is an example of a hardware functional unit. Recommendation device 510 may include at least one computing device, such as a server, a virtual machine, or a container. Alternatively, recommendation device 510 may be implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0114] The multiple computing devices included in the recommendation device 510 can be distributed in the same region or in different regions. The multiple computing devices included in the recommendation device 510 can be distributed in the same AZ or in different AZs. Similarly, the multiple computing devices included in the recommendation device 510 can be distributed in the same VPC or in multiple VPCs. The multiple computing devices can be any combination of servers, ASICs, PLDs, CPLDs, FPGAs, GALs, and other computing devices.

[0115] This application provides a computing device 600, see Figure 9 , Figure 9 This is a schematic diagram of the structure of a computing device 600 provided in this application. Computing device 600 includes a bus 602, a processor 604, a memory 606, and a communication interface 608. Processor 604, memory 606, and communication interface 608 communicate with each other via bus 602. It should be understood that this application does not limit the number of processors and memories in computing device 600.

[0116] The bus 602 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 9 The bus 602 may include a path for transmitting information between various components of the computing device 600 (eg, memory 606, processor 604, and communication interface 608).

[0117] The processor 604 may include any one or more processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0118] The memory 606 may include volatile memory, such as random access memory (RAM). The processor 604 may also include non-volatile memory, such as read-only memory (ROM), flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0119] The memory 606 stores executable code, and the processor 604 executes the executable code to implement the functions of the recommendation device 510 and the component device 520, thereby implementing a job recommendation method. In other words, the memory 606 stores instructions for executing a job recommendation method.

[0120] The communication interface 608 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 600 and other devices or a communication network.

[0121] The present application also provides a computing device cluster. The computing device cluster includes at least one computing device. The computing device can be a server, a virtual machine, or a container, such as a central server, an edge server, or a sidecar container.

[0122] like Figure 10 As shown, Figure 10 This is a structural diagram of a computing device cluster provided in the present application, wherein the computing device cluster includes at least one computing device 600, and the memory 606 in one or more computing devices 600 in the computing device cluster may store the same instructions for executing a job recommendation method.

[0123] In some possible implementations, the memory 606 of one or more computing devices 600 in the computing device cluster may also store partial instructions for executing a job recommendation method. In other words, the combination of one or more computing devices 600 can be used to jointly execute instructions for a job recommendation method.

[0124] When at least one computing device in the computing device cluster is configured as a computing device 600, the memory 606 in different computing devices 600 in the computing device cluster can store different instructions, each used to perform part of the functions of the computing device 600. That is, the instructions stored in the memory 606 in different computing devices 600 can implement one or more functions of the recommendation device 510 and the component device 520. The embodiment of the present application also provides a computer program product containing instructions. The computer program product can be a software or program product that contains instructions and can be run on a computing device or stored in any available medium. When the computer program product is run on at least one computing device, it enables the at least one computing device to perform a job recommendation method.

[0125] Embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium can be any available medium capable of being stored by a computing device, or a data storage device such as a data center that contains one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, hard disk, or magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive). The computer-readable storage medium includes instructions that instruct a computing device or a cluster of computing devices to execute a job recommendation method.

[0126] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the protection scope of the technical solutions of the embodiments of the present application.

Claims

1. A job recommendation method, characterized in that: The method is applied to a job recommendation system, which is used to provide recommendation services to the business system in which the user works. The job recommendation system includes a recommendation device and a component device. The component device includes an agent component and multiple different business components. The business components are used to indicate the presentation carriers required for presenting data on a user interface (UI). The presentation carriers indicated by the multiple different business components are different, and each business component has a unique number. The agent component is loaded into the business system. The method includes: The proxy component obtains the user's operation page information on the business system and the user's identifier, wherein the operation page information includes the uniform resource locator URL of the operation page and the input object of the user on the operation page; The agent component sends the operation page information and the user identification to the recommendation device; The recommendation device determines the recommended content and the number of the target business component for carrying the recommended content based on the operation page information and the user identifier and based on preset rules; The recommendation device sends the recommended content and the number of the target business component to the proxy component; The proxy component obtains the target business component corresponding to the number from the component device, so that the business system presents the recommended content through the target business component.

2. The method according to claim 1, characterized in that The recommendation device determines the recommended content based on the operation page information and the user identifier according to a preset rule, including: The recommendation device represents the user's operation on the operation page of the business system through a standard behavior model according to the URL of the operation page and the user's identifier; Acquire associated data of the input object, where the associated data includes attribute information of the input object; The recommended content is determined based on the preset rules according to the standard behavior model and the associated data of the input object.

3. The method according to claim 2, characterized in that The business system includes multiple business objects, each business object has one or more business types, and each business type of each business object corresponds to a URL of an operation page; The recommendation device represents the user's operation on the operation page of the business system through a standard behavior model according to the URL of the operation page and the user's identifier, including: The recommendation device represents the user's operation through the standard behavior model by matching the URL of the operation page and the user's identifier with a preconfigured function tree; the standard behavior model includes the user's identifier, the business object operated by the user, and the business type of the business object operated by the user; the function tree lists the correspondence between multiple business objects included in the business system, one or more business types of each of the multiple business objects, and the URL of the operation page corresponding to each business type of each business object.

4. The method according to any one of claims 1 to 3, characterized in that The recommendation device and the component device are both located in the cloud.

5. A job recommendation system, characterized in that: The system is used to provide a recommendation service to a business system operated by a user. The system includes a recommendation device and a component device. The component device includes an agent component and multiple different business components. The business components are used to indicate the presentation carriers required for presenting data on a user interface (UI). The presentation carriers indicated by the multiple different business components are different. Each business component has a unique number. The agent component is loaded into the business system and includes: The proxy component is configured to obtain information about an operation page of a user on the business system and an identifier of the user, wherein the information about the operation page includes a uniform resource locator (URL) of the operation page and an input object of the user on the operation page, and send the information about the operation page and the identifier of the user to the recommendation device; The recommendation device is configured to determine, based on the operation page information and the user identifier, recommended content and the number of a target business component for carrying the recommended content based on a preset rule, and send the recommended content and the number of the target business component to the proxy component; The proxy component is further configured to obtain the target business component corresponding to the number from the component device so that the business system presents the recommended content through the target business component.

6. The job recommendation system according to claim 5, characterized in that The recommended device is used to: According to the URL of the operation page and the user identifier, the user's operation on the operation page of the business system is represented by a standard behavior model; Acquire associated data of the input object, where the associated data includes attribute information of the input object; The recommended content is determined based on the preset rules according to the standard behavior model and the associated data of the input object.

7. The job recommendation system according to claim 6, wherein: The business system includes multiple business objects, each business object has one or more business types, and each business type of each business object corresponds to a URL of an operation page; The recommendation device is used to represent the user's operation through the standard behavior model by matching the URL of the operation page and the user's identifier with a preconfigured function tree; the standard behavior model includes the user's identifier, the business object operated by the user, and the business type of the business object operated by the user; the function tree lists the correspondence between multiple business objects included in the business system, one or more business types of each of the multiple business objects, and the URL of the operation page corresponding to each business type of each business object.

8. The job recommendation system according to any one of claims 5 to 7, characterized in that: The recommendation device and the component device are both located in the cloud.

9. A computing device cluster, characterized in that: The method comprises at least one computing device, wherein the at least one computing device comprises a memory and a processor, and the processor of the at least one computing device is configured to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the method according to any one of claims 1 to 4.

10. A computer storage medium, characterized in that The method comprises program instructions, which, when executed by a computing device cluster, enable the computing device cluster to implement the method according to any one of claims 1 to 4.

11. A computer program product, characterized in that The method comprises program instructions, which, when executed by a computing device cluster, enable the computing device cluster to implement the method according to any one of claims 1 to 4.

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