Methods, apparatus, devices, and storage media for generating list switching components
By generating a component that supports switching between multiple lists, the problem of poor user experience in financial and insurance businesses caused by existing cascading components is solved. It enables intuitive hierarchical display and quick location of data under large data volumes, thereby improving the user interaction experience.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA PING AN PROPERTY INSURANCE CO LTD
- Filing Date
- 2023-06-27
- Publication Date
- 2026-05-26
AI Technical Summary
Existing cascading components cannot provide quick switching and drag-and-drop sorting of multiple selection results in financial and insurance business scenarios, resulting in a poor user experience, especially when dealing with large amounts of data, making it difficult to intuitively understand the hierarchical relationship of the data.
By acquiring the tree structure data of the business data, the maximum level depth of the list is determined, converted into array data, the target root node and its parameters are generated, and a list switching component is generated based on the component rendering function, supporting multiple list switching and selection functions.
It enables users to intuitively understand the hierarchical relationships of financial and insurance data under large data volumes, quickly locate the required data, improve the user interaction experience, and has good scalability and compatibility.
Smart Images
Figure CN116860864B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of artificial intelligence, and in particular to a method for generating a list switching component, an apparatus for generating a list switching component, a computer device, and a computer-readable storage medium. Background Technology
[0002] Cascading components are a commonly used web interface control that displays related data through nested layers, providing a clearer visual effect in data presentation. Users can quickly filter data using cascading components; common examples of cascading components include the ability to select financial and insurance product categories.
[0003] Currently, the financial and insurance business scenarios involve a massive amount of data, including insurance details and insured user information. Existing cascading components typically only provide basic cascading functionality, such as dynamically changing the content of a selection box based on the options in the parent selection box. However, in practical use, users may require more convenient and efficient operation methods, such as quickly switching between different financial and insurance data and displaying the hierarchical relationship of the financial and insurance data. These functions are not well implemented in existing cascading components, which negatively impacts the user experience. Summary of the Invention
[0004] This application provides a method for generating a list switching component, a device for generating a list switching component, a computer device, and a computer-readable storage medium, which aims to generate a component that can display large amounts of financial and insurance data and has multiple list switching selection functions, so that users can intuitively understand the hierarchical relationship of financial and insurance data and improve the user's interactive experience.
[0005] To achieve the above objectives, this application provides a method for generating a list switching component, the method comprising:
[0006] Retrieve the tree structure data corresponding to each business list in the business data;
[0007] The maximum level depth of each business list is determined based on the tree structure data corresponding to each business list.
[0008] Based on the maximum level depth of the list, the tree structure data corresponding to each of the business lists is transformed to obtain the array data corresponding to each of the business lists;
[0009] Multiple preset root nodes are obtained, and data encapsulation processing is performed on the multiple preset root nodes according to the array data corresponding to each of the business lists to generate the target root node and its corresponding node parameters.
[0010] Based on the preset component rendering function, the preset component is rendered according to the target root node and its corresponding node parameters to generate a list switching component.
[0011] To achieve the above objectives, this application also provides an apparatus for generating a list switching component, the apparatus comprising:
[0012] The data acquisition module is used to acquire the tree structure data corresponding to each business list of business data;
[0013] The hierarchy determination module is used to determine the maximum hierarchy depth of each business list based on the tree structure data corresponding to each business list.
[0014] The array data generation module is used to transform the tree structure data corresponding to each of the business lists according to the maximum level depth of the list, so as to obtain the array data corresponding to each of the business lists.
[0015] The root node generation module is used to obtain multiple preset root nodes, perform data encapsulation processing on the multiple preset root nodes according to the array data corresponding to each of the business lists, and generate the target root node and its corresponding node parameters.
[0016] The component rendering module is used to perform component rendering processing on the preset component based on the target root node and its corresponding node parameters, and generate a list switching component.
[0017] In addition, to achieve the above objectives, this application also provides a computer device, the computer device including a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and, when executing the computer program, implement the method for generating a list switching component as described in any of the embodiments of this application.
[0018] In addition, to achieve the above objectives, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to implement the method for generating a list switching component as described in any of the embodiments of this application.
[0019] The list switching component generation method, apparatus, computer device, and computer-readable storage medium disclosed in this application are as follows: The method involves acquiring tree structure data corresponding to each business list of business data; determining the maximum level depth of each business list based on the tree structure data; transforming the tree structure data of each business list based on the maximum level depth to obtain array data corresponding to each business list; acquiring multiple preset root nodes; encapsulating the data of the multiple preset root nodes based on the array data corresponding to each business list to generate target root nodes and their corresponding node parameters; and rendering preset components based on preset component rendering functions according to the target root nodes and their corresponding node parameters to generate the list switching component. This allows the generation of a component capable of displaying large amounts of financial and insurance data and providing multiple list switching options, enabling users to intuitively understand the hierarchical relationships of financial and insurance data and quickly locate the required financial and insurance data, thus improving the user's interactive experience. Attached Figure Description
[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0021] Figure 1 This is a schematic diagram of a scenario illustrating a method for generating a list switching component according to an embodiment of this application;
[0022] Figure 2 This is a flowchart illustrating a method for generating a list switching component according to an embodiment of this application;
[0023] Figure 3 A flowchart illustrating a process for obtaining tree-structured data corresponding to various business lists, as provided in this application;
[0024] Figure 4 This is a schematic block diagram of a list switching component generation device provided in an embodiment of this application;
[0025] Figure 5 This is a schematic block diagram of a computer device provided in one embodiment of this application. Detailed Implementation
[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0027] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily need to be performed in the described order. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation. Furthermore, although functional modules are divided in the device diagram, in some cases, a different module division may be used.
[0028] The term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items, as well as all possible combinations, and includes such combinations.
[0029] Cascading components are a commonly used web interface control that displays related data through nested layers, providing a clearer visual presentation and allowing users to quickly filter data. Common examples of cascading components include those for selecting provinces, cities, districts, or categories of financial and insurance products.
[0030] Currently, existing cascading components typically only provide basic cascading functionality, such as the content of a selection box dynamically changing based on the options in its parent selection box. However, in practical use, users may require more convenient and faster operation methods, such as dragging and sorting multiple selections or quickly switching between different cascading data. These functions are not well implemented in existing cascading components, which negatively impacts the user experience. Furthermore, in the existing cascading component market, other similar UI components such as antd UI and element UI do not support the functionality of switching between multiple lists. Moreover, existing cascading components are modifications of element-UI; the original cascading components would have used el-Cascader. However, el-Cascader does not support many customized functions, such as the ability to switch between multiple lists.
[0031] This application proposes a method for generating a list switching component, a device for generating a list switching component, a computer device, and a computer-readable storage medium. This allows the generation of a component that can display large amounts of financial and insurance data and has multiple list switching options, enabling users to intuitively understand the hierarchical relationship of the financial and insurance data and quickly locate the financial and insurance data they need, thereby improving the user's interactive experience.
[0032] This method can be applied to servers or terminal devices to generate corresponding image classification models. Terminal devices can include fixed terminals such as mobile phones, tablets, and personal digital assistants (PDAs). Servers can be, for example, standalone servers or server clusters. However, for ease of understanding, the following embodiments will describe in detail the method for generating a list switching component applied to a server.
[0033] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.
[0034] like Figure 1 As shown, the method for generating a list switching component provided in this application embodiment can be applied to, for example, Figure 1 The application environment shown includes a terminal device 110 and a server 120. The terminal device 110 can communicate with the server 120 via a network. Specifically, the server 120 obtains the tree structure data corresponding to each business list of the business data; determines the maximum level depth of each business list based on the tree structure data; transforms the tree structure data corresponding to each business list based on the maximum level depth to obtain array data corresponding to each business list; obtains multiple preset root nodes, encapsulates the multiple preset root nodes based on the array data corresponding to each business list, and generates target root nodes and their corresponding node parameters; based on preset component rendering functions, renders preset components based on the target root nodes and their corresponding node parameters to generate list switching components, and sends the generated list switching components to the terminal device 110. The server 120 can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. Terminal device 110 may be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be connected directly or indirectly through wired or wireless communication, and this application does not impose any restrictions.
[0035] Please see Figure 2 , Figure 2This is a schematic flowchart illustrating a method for generating a list switching component according to an embodiment of this application. This method can be applied to a server to generate a component capable of displaying large amounts of financial and insurance data and offering multiple list switching options. This allows users to intuitively understand the hierarchical relationships within the financial and insurance data and quickly locate the desired data, thus enhancing the user experience.
[0036] like Figure 2 As shown, the method for generating the list switching component includes steps S101 to S105.
[0037] S101. Obtain the tree structure data corresponding to each business list of business data.
[0038] The business data comprises all relevant data from the target business, which can be healthcare, government, insurance, finance, etc. The business data may include multiple business lists, each with different categories of business data. Each business list can include business data corresponding to its respective business category. Tree-structured data can be presented as a tree diagram to better determine the hierarchy depth.
[0039] For example, tree structure data corresponding to each business list in insurance business data can be obtained. For instance, business data may include tree structure data corresponding to the auto insurance business list, and may also include tree structure data corresponding to the property insurance business list, and so on.
[0040] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.
[0041] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.
[0042] In some embodiments, based on a topic prediction model, topic prediction is performed according to the category of the business data to obtain topic information corresponding to the business data; a corresponding business list is generated based on the topic information corresponding to the business data; a preset tree structure template is obtained, and the business data corresponding to the business list is filled into the tree structure template to obtain the tree structure data corresponding to the business list. This allows for the accurate generation of tree structure data corresponding to each business list.
[0043] The topic prediction model is trained using a semantic matching model and a topic information database. This model can be trained using models such as LSTM matching, MV-DSSM, and ESIM. Topic information refers to the topic content corresponding to the business data, used to represent the category of the business list. The tree structure template is a pre-defined template without populated information, used to generate the corresponding tree structure data.
[0044] For example, such as Figure 3 As shown, Figure 3 This is a schematic diagram illustrating a process for obtaining tree-structured data corresponding to various business lists, as provided in an embodiment of this application.
[0045] S1011. Based on the topic prediction model, perform topic prediction according to the category of the business data to obtain the topic information corresponding to the business data.
[0046] S1012. Generate a corresponding business list based on the topic information corresponding to the business data.
[0047] S1013. Obtain a preset tree structure template, fill the tree structure template with the business data corresponding to the business list, and obtain the tree structure data corresponding to the business list.
[0048] Specifically, for each category of business data, a topic prediction model can be used to predict the topic based on the category of the business data to obtain the topic information corresponding to the business data; a corresponding business list can be generated based on the topic information corresponding to the business data; a preset tree structure template can be obtained, and the business data of the category can be filled into the tree structure template to obtain the tree structure data corresponding to the business list under the category.
[0049] Specifically, business data and its corresponding business categories can be input into the topic prediction model, so that the topic prediction model can extract keywords based on the business data and its corresponding categories, and make business topic predictions based on the extracted keywords, thereby obtaining the topic information corresponding to the business data.
[0050] Specifically, a preset tree structure template is obtained, and the business data of this category is filled into the tree structure template according to the data hierarchy. The tree structure is then modified, such as deleting redundant branches, and data validation is performed on the tree structure to obtain the tree structure data corresponding to the business list under this category.
[0051] For example, for insurance-related business data, a topic prediction model can be used to predict the topic based on the category of the business data, obtaining the topic information corresponding to the business data, such as car insurance, vehicle, and insurance amount. Therefore, a corresponding business list, namely the car insurance business list, can be generated based on the topic information corresponding to the business data. A preset tree structure template is obtained, and the business data corresponding to the car insurance business list is filled into the tree structure template. Data correction and data supplementation are automatically performed to generate the tree structure data corresponding to the car insurance business list.
[0052] In some embodiments, before performing topic prediction based on the category of the business data using a topic prediction model to obtain the topic information corresponding to the business data, feature extraction processing is performed on the business data to obtain data features; the business data is then classified according to the data features to obtain business data under each category. This allows for accurate classification of the business data to obtain business data under each category.
[0053] Among them, data characteristics can be the characteristic information of business data. For example, the characteristic information of insurance data can include users' personal information, insured amount information, insurance terms information, etc.
[0054] Specifically, feature extraction is performed on different business data to obtain the data features of each business data; business data with the same data features are classified as business data of the same category, and then different business data are classified according to the data features of each business data to obtain business data under each category.
[0055] For example, feature extraction processing is performed on different business data to obtain data features for each business data, such as insured amount information, insurance terms information, government terms information, patient condition information, etc. From this, it can be determined that insured amount information and insurance terms information are data features corresponding to insurance-type data, because it can be determined that business data with data features of insured amount information and insurance terms information are insurance-type business data; business data with data features of government terms information are government-type business data; and business data with data features of patient condition information are medical-type business data.
[0056] S102. Determine the maximum level depth of each business list based on the tree structure data corresponding to each business list.
[0057] The maximum level depth of the list can represent the maximum level depth of the business data in the business list, or the level of the lowest level data in the business list.
[0058] In some embodiments, the tree-structured data corresponding to the business list is parsed to obtain tree structure features; the maximum level depth of the list corresponding to the business list is determined based on the tree structure features. This allows for accurate parsing of the tree structure features, thereby accurately determining the maximum level depth of the list corresponding to the business list.
[0059] Tree structure features can include features such as branch structure and node structure.
[0060] Specifically, the tree-structured data corresponding to the business list is parsed to obtain features such as branch structure and node structure; the maximum level depth of the list corresponding to the business list is determined based on the features such as branch structure and node structure.
[0061] For example, the maximum level depth of the entire business list can be calculated using JavaScript. For instance, the province, city, and district levels are three levels, while the street-community level is two levels.
[0062] For example, if the tree structure data includes insurance at the first level, car insurance at the second level, and premiums at the third level, the tree structure data corresponding to the business list is parsed to obtain features such as branch structure and node structure, thereby determining the tree level. The tree level is then parsed to determine that the maximum level depth of the list corresponding to the business list is three levels.
[0063] S103. Based on the maximum level depth of the list, the tree structure data corresponding to each of the business lists is transformed to obtain the array data corresponding to each of the business lists.
[0064] Among them, array data can be tree structure data represented in array form, which facilitates subsequent data encapsulation and processing.
[0065] In some embodiments, a target number of empty arrays are set according to the maximum level depth of the list; the tree structure data corresponding to the business list is traversed, and the tree structure data is placed into the corresponding empty arrays according to the level, thus obtaining the array data corresponding to the business list. This allows for accurate conversion of the array data corresponding to the business list.
[0066] The target number can be determined based on the maximum level depth of the list, and can be any empty array. An empty array is an array that does not contain any data.
[0067] Specifically, an empty array is set according to the maximum level depth of the list and the number of level depths; the tree structure data corresponding to the business list is traversed, the tree structure data of each level is filtered out, and the data is put into the corresponding empty array in order of level, so as to obtain the array data corresponding to the business list.
[0068] For example, if the maximum level depth of the list is 3 levels, then 3 empty arrays can be set; if the maximum level depth of the list is 5 levels, then 5 empty arrays can be set.
[0069] For example, if the maximum level depth of the list is 3 levels, a first empty array, a second empty array, and a third empty array can be set; the tree structure data is traversed, and the tree structure data of the first level is put into the first empty array; the tree structure data of the second level is put into the second empty array; and the tree structure data of the third level is put into the third empty array, thereby obtaining the array data corresponding to the business list.
[0070] S104. Obtain multiple preset root nodes, and perform data encapsulation processing on the multiple preset root nodes according to the array data corresponding to each of the business lists to generate the target root node and its corresponding node parameters.
[0071] The preset root node is a pre-defined root node that does not contain data, while the target root node is the root node after data encapsulation, which can store corresponding array data. Node parameters can include whether the business list only displays the last node, the list data of the current node, the current level of the node, whether the node supports multi-selection, active node links, whether it is a merged child node, displaying the parent node, and the expansion method of the sub-menu, etc. Among them, active node links are used to highlight the selected path to the user.
[0072] In some embodiments, preset parameter items of the preset root node are obtained, and the preset parameter items are processed according to the array data corresponding to the service list to obtain node parameters; the preset root node is configured according to the node parameters to generate a target root node. This allows for accurate determination of node parameters and generation of the corresponding target root node.
[0073] Among them, the preset parameter items can be the parameter items that need to be input in advance, such as node data items, child node data items, and node function data items, etc.
[0074] Specifically, the preset parameter items that need to be input to the preset root node can be determined according to the business category. The preset parameter items are processed sequentially according to the array data corresponding to the business list to obtain the node parameters corresponding to the preset root node. The preset root node is configured sequentially according to the node parameters to generate the target root node.
[0075] For example, based on the business category being insurance, the preset parameter items that need to be input to the preset root node are determined to be node data items and child node data items. Then, based on the array data corresponding to the business list, the node data items and child node data items are processed sequentially to obtain the node parameters corresponding to the preset root node. Finally, the preset root node is configured sequentially according to the node parameters to generate the target root node.
[0076] S105. Based on the preset component rendering function, perform component rendering processing on the preset component according to the target root node and its corresponding node parameters to generate a list switching component.
[0077] The component rendering function is used to render preset components, giving them corresponding functionalities; specifically, it can be a `render` function. Preset components are open-source basic components, such as selectors. The list switching component allows users to switch between different lists. Specifically, users can switch to the corresponding data list by clicking different tabs. This allows users to quickly locate the required data when dealing with large amounts of data. This feature greatly improves user efficiency, making it easier to switch between different input boxes and thus speeding up the workflow.
[0078] In some embodiments, a preset function template is obtained, and parameter passing processing is performed on the function template according to the target root node and its corresponding node parameters to obtain a document object model; the preset component is then rendered according to the document object model to generate a list switching component. This allows for the quick and convenient generation of list switching components.
[0079] In this context, a function template can represent a family of functions. This template is type-independent; it is only parameterized when used, generating a specific type version based on the actual parameter types. For example, it could be a `template` template. The Document Object Model (DOM) is the programming interface for web pages. Its function is to convert a web page into a JavaScript object, allowing scripts to perform various operations (such as adding or deleting content). It provides a structured representation of the document (structure tree) and defines a way for programs to access the structure tree to modify the document's structure, style, and content.
[0080] Specifically, the Render function can be called to render the page using the full programming capabilities of JavaScript, that is, to build the Document Object Model (DOM) using JavaScript.
[0081] Specifically, the Render function can be called to generate a template; by calling the Render function, parameters can be passed to the Render function according to the target root node and its corresponding node parameters to obtain the document object model; the preset components can be rendered according to the document object model to generate a list switching component.
[0082] Parameter passing can include tag names, tag-related attributes, and the HTML content within the tag. Tag names primarily provide the HTML content for the DOM element; their type can be a string, object, or function. For example, "div" creates a... The `<html>` tag. Its related attributes (object type) are mainly used to set styles, attributes, pass component parameters, and bind events for this DOM element. The HTML content inside the `<html>` tag is mainly used to indicate if there are other nodes under this node; these are placed here.
[0083] For example, you can obtain the root node's div tag, and then use the root node's div tag to implement a recursive expansion of parameter passing, thereby obtaining the document object model.
[0084] The method for generating a list switching component disclosed in this application involves: acquiring tree structure data corresponding to each business list of business data; determining the maximum level depth of each business list based on the tree structure data; transforming the tree structure data of each business list based on the maximum level depth to obtain array data corresponding to each business list; acquiring multiple preset root nodes; encapsulating the multiple preset root nodes based on the array data corresponding to each business list to generate target root nodes and their corresponding node parameters; and rendering preset components based on preset component rendering functions according to the target root nodes and their corresponding node parameters to generate a list switching component. This method can generate a component capable of displaying large amounts of financial and insurance data and possessing multiple list switching selection functions, allowing users to intuitively understand the hierarchical relationship of financial and insurance data and quickly locate the required financial and insurance data, thus improving the user's interactive experience.
[0085] Furthermore, the list switching component generated in this application has the following advantages: 1. Strong scalability: The cascading component proposed in this patent can be seamlessly integrated with other components and technologies, and can be expanded and customized according to the actual needs of users, exhibiting strong scalability. 2. Good compatibility: The cascading component proposed in this patent is compatible with various web browsers and operating systems, and can be used in various environments, exhibiting good compatibility. 3. High ease of use: The cascading component proposed in this patent has a user-friendly interface and operation method, allowing for quick learning and suitability for various user groups, exhibiting high ease of use.
[0086] Please see Figure 4 , Figure 4 This is a schematic block diagram of a list switching component generation apparatus provided in an embodiment of this application. The list switching component generation apparatus can be configured in a server to execute the aforementioned list switching component generation method.
[0087] like Figure 4 As shown, the list switching component generation device 200 includes: a data acquisition module 201, a hierarchy determination module 202, an array data generation module 203, a root node generation module 204, and a component rendering module 205.
[0088] Data acquisition module 201 is used to acquire tree structure data corresponding to each business list of business data;
[0089] The hierarchy determination module 202 is used to determine the maximum hierarchy depth of each business list based on the tree structure data corresponding to each business list.
[0090] The array data generation module 203 is used to convert the tree structure data corresponding to each of the business lists according to the maximum level depth of the list, so as to obtain the array data corresponding to each of the business lists.
[0091] The root node generation module 204 is used to obtain multiple preset root nodes, perform data encapsulation processing on the multiple preset root nodes according to the array data corresponding to each of the business lists, and generate the target root node and its corresponding node parameters.
[0092] The component rendering module 205 is used to perform component rendering processing on the preset component based on the target root node and its corresponding node parameters, according to the preset component rendering function, to generate a list switching component.
[0093] In some embodiments, the data acquisition module 201 is further configured to perform topic prediction based on the category of the business data according to the topic prediction model, and obtain topic information corresponding to the business data; generate a corresponding business list based on the topic information corresponding to the business data; obtain a preset tree structure template, and fill the business data corresponding to the business list into the tree structure template to obtain tree structure data corresponding to the business list.
[0094] In some embodiments, the data classification module 206 is used to perform feature extraction processing on the business data to obtain data features; and to classify the business data according to the data features to obtain business data under each category.
[0095] In some embodiments, the hierarchy determination module 202 is further configured to perform structural parsing processing on the tree structure data corresponding to the business list to obtain tree structure features; and determine the maximum hierarchy depth of the list corresponding to the business list based on the tree structure features.
[0096] In some embodiments, the array data generation module 203 is further configured to set a target number of empty arrays according to the maximum level depth of the list; traverse the tree structure data corresponding to the business list, and put the tree structure data into the corresponding empty arrays according to the level to obtain the array data corresponding to the business list.
[0097] In some embodiments, the root node generation module 204 is further configured to obtain preset parameter items of the preset root node, process the preset parameter items according to the array data corresponding to the service list to obtain node parameters, and configure the preset root node according to the node parameters to generate a target root node.
[0098] In some embodiments, the component rendering module 205 is further configured to obtain a preset function template, perform parameter passing processing on the function template according to the target root node and its corresponding node parameters to obtain a document object model; and perform component rendering processing on the preset component according to the document object model to generate a list switching component.
[0099] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the devices, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0100] The methods and apparatus of this application can be used in a wide variety of general-purpose or special-purpose computing system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer terminal devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.
[0101] For example, the above-described method and apparatus can be implemented as a computer program, which can be used in, for example... Figure 5 It runs on the computer device shown.
[0102] Please see Figure 5 , Figure 5 This is a schematic diagram of a computer device provided in an embodiment of this application. The computer device may be a server.
[0103] like Figure 5 As shown, the computer device includes a processor, memory, and network interface connected via a system bus, wherein the memory may include volatile storage media, non-volatile storage media, and internal memory.
[0104] Non-volatile storage media can store operating systems and computer programs. These computer programs include program instructions that, when executed, cause the processor to perform any method for generating list switching components.
[0105] The processor provides computing and control capabilities, supporting the operation of the entire computer device.
[0106] Internal memory provides an environment for the execution of computer programs in non-volatile storage media, which, when executed by a processor, enable the processor to perform any method of generating list switching components.
[0107] This network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that the structure of this computer device is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.
[0108] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.
[0109] In some embodiments, the processor is used to run a computer program stored in memory to perform the following steps: acquiring tree structure data corresponding to each business list of business data; determining the maximum level depth of each business list based on the tree structure data corresponding to each business list; performing transformation processing on the tree structure data corresponding to each business list based on the maximum level depth of the list to obtain array data corresponding to each business list; acquiring multiple preset root nodes, performing data encapsulation processing on the multiple preset root nodes based on the array data corresponding to each business list to generate a target root node and its corresponding node parameters; and performing component rendering processing on preset components based on a preset component rendering function, according to the target root node and its corresponding node parameters, to generate a list switching component.
[0110] In some implementations, the processor is further configured to perform topic prediction based on the category of the business data according to a topic prediction model to obtain topic information corresponding to the business data; generate a corresponding business list based on the topic information corresponding to the business data; obtain a preset tree structure template, and fill the business data corresponding to the business list into the tree structure template to obtain tree structure data corresponding to the business list.
[0111] In some implementations, the business data is subjected to feature extraction processing to obtain data features; the business data is then classified according to the data features to obtain business data under each category.
[0112] In some implementations, the tree structure data corresponding to the business list is subjected to structural parsing processing to obtain tree structure features; the maximum level depth of the list corresponding to the business list is determined based on the tree structure features.
[0113] In some implementations, a target number of empty arrays are set according to the maximum level depth of the list; the tree structure data corresponding to the business list is traversed, and the tree structure data is placed into the corresponding empty arrays according to the level to obtain the array data corresponding to the business list.
[0114] In some implementations, the preset parameter items of the preset root node are obtained, and the preset parameter items are processed according to the array data corresponding to the service list to obtain node parameters; the preset root node is configured according to the node parameters to generate the target root node.
[0115] In some implementations, a preset function template is obtained, and parameter passing processing is performed on the function template according to the target root node and its corresponding node parameters to obtain a document object model; the preset component is rendered according to the document object model to generate a list switching component.
[0116] This application also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed, implement any of the list switching component generation methods provided in this application.
[0117] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.
[0118] Furthermore, the computer-readable storage medium may primarily include a program storage area and a data storage area, wherein the program storage area may store the operating system, at least one application required for a function, etc.; and the data storage area may store data created based on the use of blockchain nodes, etc.
[0119] This invention refers to a novel application model of computer technologies such as storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms in the blockchain language model. A blockchain, essentially a decentralized database, is a chain of data blocks linked using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer.
[0120] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of equivalent modifications or substitutions within the technical scope disclosed in this application, and such modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A method of generating a list switching component, the method comprising: The method includes: Retrieve the tree structure data corresponding to each business list in the business data; The maximum level depth of each business list is determined based on the tree structure data corresponding to each business list. Based on the maximum level depth of the list, the tree structure data corresponding to each of the business lists is transformed to obtain the array data corresponding to each of the business lists; Multiple preset root nodes are obtained, and data encapsulation processing is performed on the multiple preset root nodes according to the array data corresponding to each of the business lists to generate the target root node and its corresponding node parameters. Based on the preset component rendering function, the preset component is rendered according to the target root node and its corresponding node parameters to generate a list switching component. The step of transforming the tree structure data corresponding to each of the business lists according to the maximum level depth of the list to obtain the array data corresponding to each of the business lists includes: Set an empty array of the target number based on the maximum level depth of the list; Traverse the tree structure data corresponding to the business list, and put the tree structure data into the corresponding empty array according to the level to obtain the array data corresponding to the business list; The step of encapsulating data for multiple preset root nodes based on array data corresponding to each of the business lists to generate a target root node and its corresponding node parameters includes: Obtain the preset parameter items of the preset root node, and process the preset parameter items according to the array data corresponding to the business list to obtain the node parameters; Configure the preset root node according to the node parameters to generate the target root node.
2. The method of claim 1, wherein, The tree structure data corresponding to each business list for acquiring business data includes: Based on the topic prediction model, topic prediction is performed according to the category of the business data to obtain the topic information corresponding to the business data. Generate a corresponding business list based on the theme information corresponding to the business data; Obtain a preset tree structure template, and fill the tree structure template with the business data corresponding to the business list to obtain the tree structure data corresponding to the business list.
3. The method of claim 2, wherein, Before performing topic prediction based on the category of the business data using the topic prediction model to obtain the topic information corresponding to the business data, the method further includes: The business data is subjected to feature extraction processing to obtain data features; The business data is classified according to the data characteristics to obtain business data under each category.
4. The method of claim 1, wherein, The step of determining the maximum level depth of each business list based on the tree structure data corresponding to each business list includes: Perform structural parsing on the tree-structured data corresponding to the business list to obtain tree structure features; The maximum level depth of the list corresponding to the business list is determined based on the tree structure characteristics.
5. The method of claim 1, wherein, The preset component rendering function renders the preset component according to the target root node and its corresponding node parameters to generate a list switching component, including: Obtain a preset function template, and perform parameter passing processing on the function template according to the target root node and its corresponding node parameters to obtain a document object model; The preset components are rendered according to the document object model to generate a list switching component.
6. A generating apparatus of a list switching component, characterized by, include: The data acquisition module is used to acquire the tree structure data corresponding to each business list of business data; The hierarchy determination module is used to determine the maximum hierarchy depth of each business list based on the tree structure data corresponding to each business list. The array data generation module is used to transform the tree structure data corresponding to each of the business lists according to the maximum level depth of the list, so as to obtain the array data corresponding to each of the business lists. The root node generation module is used to obtain multiple preset root nodes, perform data encapsulation processing on the multiple preset root nodes according to the array data corresponding to each of the business lists, and generate the target root node and its corresponding node parameters. The component rendering module is used to perform component rendering processing on the preset component based on the preset component rendering function, according to the target root node and its corresponding node parameters, to generate a list switching component. The step of transforming the tree structure data corresponding to each of the business lists according to the maximum level depth of the list to obtain the array data corresponding to each of the business lists includes: Set an empty array of the target number based on the maximum level depth of the list; Traverse the tree structure data corresponding to the business list, and put the tree structure data into the corresponding empty array according to the level to obtain the array data corresponding to the business list; The step of encapsulating data for multiple preset root nodes based on array data corresponding to each of the business lists to generate a target root node and its corresponding node parameters includes: Obtain the preset parameter items of the preset root node, and process the preset parameter items according to the array data corresponding to the business list to obtain the node parameters; Configure the preset root node according to the node parameters to generate the target root node.
7. A computer device, comprising: The computer device includes a memory and a processor; The memory is used to store computer programs; The processor is configured to execute the computer program and, in executing the computer program, implement: The method for generating a list switching component as described in any one of claims 1-5.
8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to implement the method for generating a list switching component as described in any one of claims 1-5.