Job recommendation method, system and related device

Abstract

The invention provides a job recommendation method, system and related device, the method relates to the field of cloud computing, the method is executed by a job recommendation system, and the job recommendation system comprises a recommendation device and a component device. The component device comprises an agent component and a plurality of service components, and the agent component is loaded to a service system. The method comprises the following steps: an agent component obtains operation page information of a user on a service system and an identifier of the user, and sends the operation page information and the identifier of the user to a recommendation system; the recommendation system determines recommended content and a serial number of a target service component used for bearing the recommended content according to the operation page information and the identifier of the user, and sends the recommended content and the serial number of the target service component to an agent component; and the proxy component obtains a target service component corresponding to the number from the target node, so that the service system presents the recommended content through the target service component. The job recommendation method provided by the invention has universality, and the operation, maintenance and management cost of the whole system is low.

Description

Technical Field

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

[0002] To improve the intelligence of the job system, user behavior and user data are used to predict user behavior or analyze user preferences, so that the system can provide an auxiliary page to the user during the user's job process to help the user complete the job better and faster. For example, when a user enters a certain piece of information in a certain system, the system will recommend information associated with the input information to the user, so that the user can select a correct piece of information from the associated information and fill it into the system to complete the job faster.

[0003] At present, the auxiliary pages recommended by the job recommendation system to users are all customized. For example, in an 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. The auxiliary pages corresponding to different business functions in the same system are different, and the auxiliary pages corresponding to different systems are also different. Currently, the recommended auxiliary pages are all customized and developed by the job recommendation system according to each business function of each business system, that is, the auxiliary pages of different business functions are customized and developed through different program codes. This customized development method results in relatively high later-stage operation and maintenance and management costs. Summary of the Invention

[0004] This application provides a job recommendation method, system, and related devices. By using the method of this application, for different business systems and different business functions in the same business system, the recommended auxiliary pages / recommended pages do not need to be customized and developed, which is convenient for later operation and maintenance and management, and the operation and maintenance and management costs are relatively low.

[0005] In a first aspect, the present application provides a job recommendation method, which is executed by a job recommendation system. The job recommendation system includes a recommendation device and a component device. The component device includes an agent component and a plurality of business components. The agent component is loaded into the business system to obtain information on the interaction between the user and the business system. This information includes the operation page information when the user operates on the business system and the input objects on the operation page, and sends these to the recommendation device. The agent component is also used to obtain the information sent by the recommendation device. For example, it obtains the recommended content sent by the recommendation device, where the recommended content is determined by the recommendation device based on the operation page information and the input objects. The business component is used to indicate the presentation carrier required to present the recommended content on the user interface. The business system presents the recommended content through the adapted business component so that the user can view the recommended content and perform other operations based on the recommended content. It can be seen that the present application provides a new system architecture. In the new system architecture, the agent component and the business component in the component device are both independently deployed and not integrated with the recommendation device. The agent component is used to obtain the operation page information on the business system and the input objects input by the user. The recommendation device is used to determine the recommended content for the user based on the operation page information and the input objects input 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 customize and develop the recommendation page through code for different business functions in the recommendation system. For different business systems, the front-end technology stacks are different, the sizes of the display pages are different, and the application programming interfaces required for displaying the auxiliary pages are different; for different business functions, the page styles are also different. 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 programming interface. In the method of the present application, the component device is independently deployed, and the agent component provides a unified application programming interface externally. Different business systems can load the agent component through the unified application programming interface and display the recommended content through the adapted business component, avoiding the problem of customizing and developing the recommendation page 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, realizes the provision of recommendation pages / auxiliary pages across technology stacks, and the job recommendation method provided by the present application has wide applicability, strong generality, and is convenient for operation and maintenance and management, with low operation and maintenance and management costs.

[0007] Based on the first aspect, in a possible implementation, the recommendation device represents the operations of the user 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 includes the attribute information of the input object. Based on the standard behavior model and the associated data of the input object, the recommendation content is determined based on a preset rule.

[0008] It can be understood that representing the operations of the user on the business system using a unified standard behavior model facilitates the 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; The recommendation device represents the operations of the user on the operation page of the business system through a standard behavior model according to the URL of the operation page and the user identifier, including: The recommendation device matches the URL of the operation page and the user identifier with a pre-configured function tree, so as to represent the user's operations through a standard behavior model; the standard behavior model includes the user 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 corresponding relationships among the multiple business objects included in the business system, one or more business types of each business object among the multiple business objects, and the URL of the operation page corresponding to each business type of each business object.

[0010] Based on the first aspect, in a possible implementation, both the recommendation device and the component device are located in the cloud.

[0011] In a second aspect, the present application provides a job recommendation system for providing a recommendation service to the business system in which the 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 carriers required for presenting data on the 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 onto the business system and includes: The agent component is used to obtain the operation page information of the user on the business system and the user identifier. Among them, 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 sends the operation page information and the user identifier to the recommendation device; The recommendation device is used to determine the recommendation content and the number of the target business component for carrying the recommendation content based on the operation page information and the user identifier according to a preset rule, and send the recommendation content and the number of the target business component to the agent component; The proxy component is also used to obtain the target service component corresponding to the number from the component device; The service system is used to present the recommended content through the target service component so that the user can operate according to the recommended content.

[0012] Based on the second aspect, in a possible implementation, the recommendation device is used for: According to the URL of the operation page and the user identifier, represent the operations of the user on the operation page of the service system through a standard behavior model; Obtain the associated data of the input object, where the associated data includes the attribute information of the input object; Determine the recommended content based on the preset rules according to the standard behavior model and the associated data of the input object.

[0013] Based on the second aspect, in a possible implementation, the service system includes multiple service objects, each service object has one or more service types, and each service type of each service object corresponds to the URL of an operation page; The recommendation device is used to represent the operations of the user through a standard behavior model by matching the URL of the operation page and the user identifier with a pre-configured function tree; the standard behavior model includes the user identifier, the service object operated by the user, and the service type of the service object operated by the user, and the function tree lists the correspondence between the multiple service objects included in the service system, one or more service types of each service object among the multiple service objects, and the URL of the operation page corresponding to each service type of each service object.

[0014] Based on the second aspect, in a possible implementation, both the recommendation device and the component device are located in the cloud.

[0015] In a third aspect, the present application provides a computing device cluster, including at least one computing device, 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 the instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the method described in the first aspect and any possible implementation of the first aspect.

[0016] In a fourth aspect, the present application provides a computer storage medium, including program instructions, when the program instructions are executed by the computing device cluster, the computing device cluster is enabled to implement the method described in the first aspect and any possible implementation of the first aspect.

[0017] In a fifth aspect, the present application provides a computer program product, including program instructions which, when executed by a cluster of computing devices, cause the cluster of computing devices to implement the method described in the above first aspect and any possible implementation manner of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a schematic diagram of a system architecture provided by the present application; Figure 2 is a schematic flowchart of a job recommendation method provided by the present application; Figure 3 is a flowchart of a method for determining recommended content provided by the present application; Figure 4 is a schematic diagram of the structure of a functional tree provided by the present application; Figure 5 is a schematic diagram of a standard behavior model of a user provided by the present application; Figure 6 is a schematic diagram of a set of metadata provided by the present application; Figure 7 is a scenario example diagram provided by the present application; Figure 8 is a schematic diagram of the structure of a job recommendation system provided by the present application; Figure 9 is a schematic diagram of the structure of a computing device provided by the present application; Figure 10 is a schematic diagram of the structure of a cluster of computing devices provided by the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The present application provides a system, as Figure 1 shown, Figure 1 is a schematic diagram of the system architecture provided by the present application. This system relates to a job recommendation system and a business system. Among them, the job recommendation system includes a recommendation device and a component device. In this system architecture, taking the business system including any one or more of a marketing system, a sales system, and a customer service system as an example, in actual applications, the business system can also be other application systems, which is not limited in the present application.

[0020] The component device includes an agent component, and the agent component provides a uniform resource locator (URL) externally. The marketing system, the sales system, and the customer service system can load the agent component on the component device through the URL. The component device is located in the cloud.

[0021] When the proxy component is loaded onto the business system and the user operates on the business system, the proxy component is used to obtain the operation page information of the user on the business system and the user's identifier. The business system can include any one or more of a marketing system, a sales system, and a customer service system. When the user operates on the business system, for example, it can be that the user creates an opportunity point on the front-end page of the sales system. Correspondingly, the proxy component obtains the opportunity point page information created by the user on the front-end page of the sales system. Another example is that the user creates a seal application on the front-end page of the sales system. Correspondingly, the proxy component obtains the page information of the seal application created by the user on the front-end page of the sales system. The proxy component is also used to send the operation page information and the user's identifier to the recommendation device.

[0022] Among them, the proxy component can be implemented using module federation and Web components technology. Module federation is a technology used in the front-end architecture that allows different front-end applications to share resources. For example, using module federation technology enables the front-ends of the marketing system, the sales system, and the customer service system to share the proxy component, without the need to repeatedly implement the functions of the proxy component through code when developing the marketing system, the sales system, and the customer service system. Web components are a set of technologies natively supported by browsers, aiming 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 the proxy component is to reduce the duplication of front-end applications in the business system by exposing interfaces and sharing functions, enabling the proxy component to be flexibly applied in different business systems and reducing the maintenance cost.

[0023] The recommendation device is used to receive the operation page information and the user's identifier sent by the proxy component, and analyze them based on preset rules according to the operation page information and the user's identifier to determine the recommended content and the number of the target business component for carrying the recommended content. The recommendation device is also used to send the recommended content and the number of the target business component to the proxy component. The proxy component is also used to obtain the target business component corresponding to the number from the component device. The business system presents the recommended content to the user through the target business component so that the user can operate according to the recommended content.

[0024] The component device also includes the correspondence between the codes and numbers of multiple service components. Through the code of a service component, the service component can be presented. The component device includes the codes of multiple service components, which can be approximately understood as that the component device includes multiple service components. A service component is used to indicate the presentation carrier required for data to be presented on the user interface UI, and different service components indicate different presentation carriers. Each service component has a unique number, and the component device stores the correspondence between the codes of multiple service components and the numbers of the service components. When the proxy component obtains the number of a certain service component, the component device sends the code of the service component corresponding to the number to the recommendation device.

[0025] Optionally, the proxy component is further configured to receive the feedback of the user on the recommended content on the front-end page of the service system. The feedback can be that the user accepts the recommended content or rejects the recommended content, and send the feedback to the recommendation device. The recommendation device is further configured to update the preset rules according to the feedback of the user.

[0026] In an application scenario, both the recommendation device and the component device are located in the cloud. The recommendation device and the component device can be located on one 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.

[0027] Optionally, the backend of the service system can also be located in the cloud. The customer logs in to the service system by logging in to a web page on the terminal device and operates on the service system. Among them, the service system can include one or more of a marketing system, a sales system, and a customer service system. The recommendation device, the component device, and the service system are services provided by the same cloud service provider. The customer purchases the services provided by the cloud service provider so that the job recommendation system provides job recommendation services for the service system.

[0028] Optionally, the service system can also be an application program integration package deployed on the customer's terminal device, that is, the backend of the service system is located on the customer's terminal device. In this application scenario, the proxy component can be deployed as a program package on the customer's terminal device. When the service system is started, the service system calls the proxy component on the terminal device, and the proxy component is used to obtain the operation page information and the user identification of the user on the service system.

[0029] Figure 1 It is a schematic diagram of a system architecture provided by the present application. Figure 1 The description of the system architecture content does not constitute a limitation to the present application.

[0030] The present application provides a job recommendation method. Refer to Figure 2 , Figure 2 It is a schematic flow chart of a job recommendation method provided by the present application. The method can be performed byFigure 1 The job recommendation system in [[ ]] executes. The job recommendation system includes a recommendation device and a component device. The component device includes an agent component and multiple business components. Among them, the agent component is loaded onto the business system. The following describes the job recommendation method provided by this application. The method includes but is not limited to the following description.

[0031] 201: The agent component obtains the operation page information of the user on the business system and the user identifier. Among them, 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.

[0032] The 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 in [[ ]].

[0033] After the agent component is loaded onto the business system, when the user operates on the front-end page of the business system, the agent component can obtain the user's operation page information and the user identifier. The user identifier 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, if the user's operation includes creating an opportunity point on the sales system and entering the opportunity point name on the operation page, then the URL of the operation page is the URL of the create opportunity point page of the sales system, and the input object is the opportunity point name. Another example is that 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. Then the URL of the operation page is the URL of the create seal application page of the sales system, and the input object is the name or number of the customer who needs to be sealed. It should be noted that the input object of the user on the operation page can be one or multiple. The operation page information can also include other information.

[0034] 202: The agent component sends the operation page information and the user identifier to the recommendation device.

[0035] 203: 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 according to the preset rules.

[0036] The business component is the presentation carrier required for data to be presented on the user interface (UI). The recommendation device determines the recommended content to be recommended to the user and the number of the target business component for carrying the recommended content based on the URL of the operation page, the input object of the user on the operation page, and the user identifier according to the preset rules.

[0037] Optionally, this step can be implemented by the following method, as Figure 3 shown.Figure 3 A flowchart of a method for determining recommended content provided by this application, and the method includes but is not limited to the following content description.

[0038] 2031: The recommendation device represents the operations of the user on the operation page of the business system through a standard behavior model according to the URL of the operation page and the identifier of the user.

[0039] It can be understood 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. For example, the business system includes a marketing system, a sales system, and a customer service system. The business objects include marketing tasks in the marketing system. The business types can be creating a marketing task, modifying a marketing task, and viewing a marketing task. Each business type has a URL of an operation page. The business objects also include the seal application in the sales system. The business types can be creating a seal application, modifying a seal application, and viewing a seal application. Each business type has a URL of an operation page. The business objects also include work orders. The business types can be creating a work order, modifying a work order, and viewing a work order. Each business type has a URL of an operation page.

[0040] The recommendation device can determine the business object and business type according to the obtained URL of the operation page. Specifically, the recommendation device matches the URL of the operation page with a pre-configured function tree to determine the business object and business type. Among them, the function tree refers to hierarchically and structurally deploying the functions of the business system into a tree structure. For example, see Figure 4 , Figure 4 A schematic structural diagram of a function tree provided by 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: creating, modifying, and viewing. Each business type of each business object has a URL of an operation page. Figure 4 The function tree shown is only an example. In actual applications, the function tree lists the correspondence relationships 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.

[0041] If the URL of the operation page obtained by the recommendation device is www.xxxxxxxx.com / mkt-task / create, match this URL with the function tree in Figure 4 , and determine that the business object is a marketing task and the business type is creating a marketing task; if the URL of the operation page obtained by the recommendation device is www.xxxxxxxx.com / mkt-task / edit, match this URL with the function tree in Figure 4Match with the function tree in it to 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 this URL with Figure 4 in the function tree to determine that the business object is a seal application and the business type is to create a seal application. Among them, xxxxxxxx can represent any character.

[0042] Furthermore, the recommendation device matches the URL of the operation page and the user's identifier with the pre-configured function tree, so as to represent the user's operation through a standard behavior model. Among them, the standard behavior model includes the user's identifier, the business object of the user's operation, and the business type of the business object of the user's operation. For example, Figure 5 shows a schematic diagram of the user's standard behavior model. Figure 5 The standard behavior model shown in it is an example and does not constitute a limitation on the standard behavior model.

[0043] 2032: Obtain the associated data of the input object, and the associated data includes the attribute information of the input object.

[0044] The recommendation device obtains the associated data of the input object, where the associated data includes the attribute information of the input object. For example, when the user creates a seal application and enters the name of the customer for whom the seal is used on the operation page, the recommendation device obtains the associated data of the customer's name, such as the customer's identification number, the customer's level, the region where the customer is located, etc. For example, if the customer for the seal application is customer a, the identification number of customer a is aaa, the level of customer a is v2, and the region where the customer is located is Beijing, and the user only enters customer a on the operation page, the recommendation device obtains other associated data of customer a, or if the user only enters the identification number aaa of customer a on the operation page, the recommendation device obtains other associated data of customer a. Among them, the customer's name, the customer's identification number, the customer's level, the region where the customer is located, etc. are all the attribute information of the customer.

[0045] The recommendation device stores metadata, and the metadata includes objects associated with each business object. For example, Figure 6 is a set of metadata. Figure 6 In, the business object is a seal application, and the objects associated with the seal application include two categories. One category is customers, including all customers who may need a seal, and the other category is signing entities, including all possible signing entities. The signing entity refers to the unit / enterprise / company to which the seal belongs. That is, the two types of objects associated with the seal application are one is the customer who needs to affix the seal, and the other is which unit / enterprise / company's seal to affix. It should be noted that in Figure 6In the example described, only one piece of information about the customer is stored in the metadata. For example, it could be the customer's name or their identification number, but not all of the customer's attribute information is stored.

[0046] In one example, when the business object is a seal usage application and the user's input object is customer A, the recommendation device obtains the associated data of customer A. In one example, when the business object is a marketing task and the user's input object is an opportunity point, the recommendation device obtains the associated data of the opportunity point, and the associated data of the opportunity point includes the identifier of the opportunity point, the name of the opportunity point, and the opportunity point space.

[0047] It can be 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.

[0048] It should be noted that the metadata also includes data associated with other business objects, which is not limited here.

[0049] 2033: Determine the recommended content based on the standard behavior model and the associated data of the input object according to preset rules.

[0050] The recommendation device determines the recommended content based on the standard behavior model and the associated data of the input object according to preset rules. For example, Figure 7 In the scenario example diagram shown, the standard behavior model is: User: Zhang San Business object: Seal usage application Business type: Creation The input object is the name of the customer, and the associated data obtained by the recommendation device includes: Seal usage application: { Customer: { Identifier: account_001, Level: v5, Region: Shanghai } } The preset rules include: Condition: Business object = "Seal usage application" and business type = "Creation or modification" and seal usage application.customer.region = "Shanghai"; Recommendation: Modify the attributes of the object associated with the seal usage application - the signing entity to: Based on the customer you selected, whose place of origin is (region), it is recommended that you select the following signing entity:

[0051] The recommendation device is based on Figure 7The associated data of the standard behavior model and the input object in it, based on the above preset rules, determines that the recommended content is: Based on the customer you selected, whose place of origin is (Shanghai), it is recommended that you select the following signing entities:

[0052] The schematic diagram of the page of the recommended content is as Figure 7 shown.

[0053] It should be noted that in the Figure 7 shown example, the recommended content is one of the objects associated with the seal use 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 the objects associated with the business object and can be other content, which is not limited in this application.

[0054] It can be understood that the preset rules are related to the associated data of the business object, business type, and input object in the standard behavior model. Specifically, the preset rules limit or constrain the associated data of the input object according to the business type and business object.

[0055] Optionally, the preset rules are also related to the identifier of the user in the standard behavior model. Different identifiers of the user, that is, different roles of the user, may have different permissions. When users with different permissions operate on the business system, the recommended content may be different. Therefore, the preset rules are also related to the identifier of the user. 204: The recommendation device sends the recommended content and the number of the target business component to the proxy component.

[0056] 205: The proxy component obtains the target business component corresponding to the number from the component device.

[0057] The component device stores the correspondence between the codes of multiple business components and the numbers of multiple business components. The business component is used to indicate the presentation carrier required for the data to be presented on the user interface UI. The presentation carriers indicated by multiple different business components are different. It can be understood that the content presented on the page is different, the page size is different, and the page style is different, so the presentation carriers are different. The component device includes the codes of multiple business components, and each code of the business component has a unique number. The proxy component obtains the code of the target business component corresponding to the number from the component device.

[0058] The business system obtains the code of the target business component through the proxy component. It can be understood that the code of the target business component is used to present the target business component. When the business system obtains the code of the target business component, it is equivalent to obtaining the target business component. The business system presents recommended content through the target business component. The user views the recommended content and gives feedback on the front-end page of the business system for the recommended content. The feedback can be accepting the recommended content or rejecting the recommended content. The proxy component is also used to obtain the feedback information of the user for the recommended content and send the feedback information to the recommendation device. The recommendation device updates the preset rules according to the user's feedback.

[0059] It can be seen that the present application provides a new system architecture. In the new system architecture, the proxy component and the business component in the component device are both independently deployed and not integrated with the recommendation device. The proxy component is used to obtain the operation page information on the business system and the input object input by the user. The recommendation device is used to determine the recommended content for the user according to the operation page information and the input object input 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.

[0060] The traditional method is to customize and develop the recommendation page through code for different business functions in the recommendation system. For different business systems, the front-end technology stacks are different, the sizes of the display pages are different, and the application program interfaces required for displaying the auxiliary pages are different; for different business functions, the page styles are also different. 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 independently deploys the component device. The proxy component provides a unified application program interface externally. Different business systems can load the proxy component through the unified application program interface and display the recommended content through the adapted business component, avoiding the problem of customizing and developing the recommendation page 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, realizes providing the recommendation page / auxiliary page across technology stacks, and the job recommendation method provided by the present application has wide applicability, strong generality, and is convenient for operation and maintenance and management, and the operation and maintenance and management costs are low.

[0061] The above describes the method embodiment provided by the present application. Next, the device embodiment corresponding to the method embodiment is introduced.

[0062] The present application provides a job recommendation system. Refer to Figure 8 , Figure 8Schematic diagram of a job recommendation system 500 provided for 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 carriers required for presenting data on the user interface. The presentation carriers indicated by each business component 522 are different, and each business component 522 has a unique number. The agent component 521 is loaded onto the business system. The job recommendation system 500 includes: The agent component 521 is used to obtain the operation page information of the user on the business system and the identifier of the user. Among them, 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 identifier of the user to the recommendation device 510; 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 preset rules according to the operation page information and the identifier of the user, and send the recommended content and the number of the target business component to the agent component 521; The agent component 521 is further used to obtain the 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.

[0063] In a possible implementation, the recommendation device 510 is used to: Represent the operations of the user on the operation page of the business system through a standard behavior model according to the URL of the operation page and the identifier of the user; Obtain the associated data of the input object, and the associated data includes the attribute information of the input object; Determine the recommended content based on preset rules according to the standard behavior model and the associated data of the input object.

[0064] 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; The recommendation device 510 is used to match the URL of the operation page and the identifier of the user with a pre-configured function tree, so as to represent the operations of the user through a standard behavior model; the standard behavior model includes the identifier of the user, the business object operated by the user, and the business type of the business object operated by the user. The function tree lists the corresponding relationships between multiple business objects included in the business system, one or more business types of each business object among the multiple business objects, and the URL of the operation page corresponding to each business type of each business object.

[0065] In a possible implementation, both the recommendation device 510 and the component device 520 are located in the cloud.

[0066] Among them, the recommendation device 510 and the component device 520 in the homework recommendation system 500 can be implemented by software or by hardware. Exemplarily, taking the recommendation device 510 as an example, the implementation manner of the recommendation device 510 will be introduced next. Similarly, the implementation manner of the component device 520 can refer to the implementation manner of the recommendation device 510.

[0067] The module is an example of a software functional unit. The recommendation device 510 may include code running on a computing instance, where 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 for running this code may be distributed in the same region or in different regions. Further, the multiple computing instances for running this code may be distributed in the same availability zone (AZ), or in different AZs, and each AZ includes one data center or multiple geographically proximate data centers. Among them, generally one region may include multiple availability zones AZs.

[0068] Similarly, the multiple computing instances for running this code may be distributed in the same virtual private cloud (VPC), or in multiple VPCs. Among them, generally one VPC is set within one region. For cross-region communication between two VPCs within the same region and between VPCs in different regions, a communication gateway needs to be set in each VPC, and the interconnection between VPCs is achieved through the communication gateway.

[0069] The module is an example of a hardware functional unit. The recommendation device 510 may include at least one computing device, such as a server, a virtual machine, a container, etc. Alternatively, the recommendation device 510 may also be a device implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). Among them, the above PLD may be implemented by a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0070] 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. Among them, the multiple computing devices can be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0071] This application provides a computing device 600. Refer to Figure 9 , Figure 9 which is a schematic structural diagram of a computing device 600 provided by this application. The computing device 600 includes: a bus 602, a processor 604, a memory 606, and a communication interface 608. The processor 604, the memory 606, and the communication interface 608 communicate with each other through the bus 602. It should be understood that this application does not limit the number of processors and memories in the computing device 600.

[0072] The bus 602 can be a peripheral component interconnect (PCI) bus, an extended industry standard architecture (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity of representation, Figure 9 only one line is shown in , but it does not mean that there is only one bus or one type of bus. The bus 602 can include a path for transmitting information between various components of the computing device 600 (for example, the memory 606, the processor 604, and the communication interface 608).

[0073] The processor 604 can include any one or more of processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0074] 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).

[0075] Executable code is stored in the memory 606, and the processor 604 executes the executable code to respectively implement the functions of the foregoing recommendation device 510 and component device 520, thereby implementing a job recommendation method. That is to say, instructions for executing a job recommendation method are stored on the memory 606.

[0076] 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.

[0077] This application also provides a computing device cluster. The computing device cluster includes at least one computing device. The computing device may be a server, a virtual machine, a container, such as a central server, an edge server, or a sidecar container.

[0078] As Figure 10 shown, Figure 10 is a schematic structural diagram of a computing device cluster provided by this application. The computing device cluster includes at least one computing device 600. Instructions for executing a job recommendation method may be stored in the same manner in the memory 606 of one or more computing devices 600 in the computing device cluster.

[0079] In some possible implementation manners, partial instructions for executing a job recommendation method may also be stored separately in the memory 606 of one or more computing devices 600 in the computing device cluster. In other words, a combination of one or more computing devices 600 can be used to jointly execute the instructions of a job recommendation method.

[0080] When at least one computing device in a computing device cluster is configured as computing device 600, the memories 606 in different computing devices 600 in the computing device cluster may store different instructions respectively for performing partial functions of the computing device 600. That is to say, the instructions stored in the memories 606 in different computing devices 600 may implement the functions of one or more of the recommendation device 510 and the component device 520. An embodiment of the present application also provides a computer program product including instructions. The computer program product may be software or a program product including instructions that can run on a computing device or be stored in any available medium. When the computer program product runs on at least one computing device, at least one computing device is caused to execute a job recommendation method.

[0081] An embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium may be any available medium that a computing device can store or a data storage device such as a data center including one or more available media. The available medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state drive), etc. The computer-readable storage medium includes instructions that instruct a computing device or a computing device cluster to execute a job recommendation method.

[0082] 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 foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate 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 where the user conducts operations. 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 data to be presented on the 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 onto the business system. The method includes: The agent component obtains the operation page information of the user on the business system and the identifier of the user. Among them, 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 identifier of the user 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 preset rules according to the operation page information and the identifier of the user; The recommendation device 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 component device, so that the business system presents the recommended content through the target business component.

2. The method according to claim 1, wherein The recommendation device determines the recommended content based on the preset rules according to the operation page information and the identifier of the user, including: The recommendation device represents the operations of the user on the operation page of the business system through a standard behavior model according to the URL of the operation page and the identifier of the user; Obtain the associated data of the input object, where the associated data includes the attribute information of the input object; Determine the recommended content 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 operations of the user on the operation page of the business system through a standard behavior model according to the URL of the operation page and the identifier of the user, including: The recommendation device matches the URL of the operation page and the identifier of the user with a pre-configured function tree, so as to represent the operations of the user through the standard behavior model; the standard behavior model includes the identifier of the user, the business object operated by the user, and the business type of the business object operated by the user. The function tree lists the corresponding relationships between the multiple business objects included in the business system, one or more business types of each business object among 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 Both the recommendation device and the component device are located in the cloud.

5. A job recommendation system, characterized in that, For providing a recommendation service to the business system where the user operates, the job recommendation system includes a recommendation device and a component device. The component device includes an agent component and a plurality of different business components. The business components are used to indicate the presentation carriers required for presenting data on the user interface UI. The presentation carriers indicated by the plurality of different business components are different, and each business component has a unique number. The agent component is loaded onto the business system and includes: The agent component is used to obtain the operation page information of the user on the business system and the identifier of the user. Among them, 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 identifier of the user to the recommendation device; 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 preset rules according to the operation page information and the identifier of the user, and send the recommended content and the number of the target business component to the agent component; The agent component is further used 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, wherein The recommendation device is used for: Represent the operations of the user on the operation page of the business system through a standard behavior model according to the URL of the operation page and the identifier of the user; Obtain the associated data of the input object, and the associated data includes the attribute information of the input object; Determine the recommended content 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 There are a plurality of business objects in the business system. Each business object has one or more business types, and each business type of each business object corresponds to the URL of an operation page; The recommendation device is used to represent the operations of the user through the standard behavior model by matching the URL of the operation page and the identifier of the user with a pre-configured function tree. The standard behavior model includes the identifier of the user, the business object operated by the user, and the business type of the business object operated by the user. The function tree lists the corresponding relationships among the plurality of business objects included in the business system, one or more business types of each business object among the plurality of 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, Both the recommendation device and the component device are located in the cloud.

9. A cluster of computing devices, characterized in that, Including at least one computing device, the at least one computing device includes a memory and a processor. The processor of the at least one computing device is used to execute the 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, Including program instructions, when the program instructions are executed by the computing device cluster, the computing device cluster is caused to implement the method according to any one of claims 1 to 4.

11. A computer program product, characterized in that, Comprising program instructions that, when executed by a cluster of computing devices, cause the cluster of computing devices to implement the method according to any one of claims 1 to 4.

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