An app activity interface new creation method and system

Abstract

The application discloses an app activity interface new creation method and system, comprising: in response to a user's activity creation request, displaying an activity configuration interface containing a template selection area and a rule configuration area; using an intelligent template selection strategy to recommend a selected activity template matching the activity request; obtaining a target item number of target configurable rule items associated with the selected template, generating a composite rule item based on a rule item dependency graph and an association degree matrix through clustering analysis; according to the comparison result of the target item number and the preset threshold, adaptively using a unified configuration or a phased guidance configuration strategy; finally, generating an activity interface configuration file using a hierarchical storage structure according to the target template and the rule configuration data. The application can effectively reduce the configuration complexity, improve the activity interface generation efficiency and accuracy, and solve the technical problems of the traditional method, such as blind template selection, chaotic configuration process, poor device compatibility and the like.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of computer software, and particularly relates to an app activity interface new creation method and system. BACKGROUND

[0002] With the rapid development of mobile Internet, various apps often need to carry out operation activities. Currently, the following two ways are usually adopted to create app activity interfaces: one is to write codes by developers to realize, which has long development cycle and poor flexibility; the other is to use visual configuration tools to generate activity interfaces by selecting templates and configuring rule items.

[0003] However, the existing visual configuration scheme has obvious deficiencies: firstly, the template selection process lacks intelligent recommendation, and users need to manually find suitable templates from a large number of templates, which is low in efficiency; secondly, when a template contains a large number of configurable rule items, the configuration interface is complex, and users are prone to miss important configuration items or cause configuration conflicts; in addition, the traditional configuration method does not consider the internal relevance between rule items, resulting in a chaotic configuration process and poor user experience.

[0004] Therefore, there is an urgent need for a solution that can intelligently recommend templates and intelligently group and guidedly configure complex configuration items. SUMMARY

[0005] The present application aims to solve the deficiencies in the prior art and provide an app activity interface new creation method and system that can improve configuration efficiency and accuracy.

[0006] In a first aspect, the present application provides an app activity interface new creation method, comprising:

[0007] In response to a user's activity creation request, an activity configuration interface is displayed, wherein the activity configuration interface comprises an activity template selection area and a rule configuration area, and an activity template in the activity template selection area has an association relationship with at least one configurable rule item in the rule configuration area;

[0008] A preset template selection strategy is adopted to recommend candidate activity templates matching the activity creation request from the activity template selection area, and a target activity template is determined among the candidate activity templates based on the user's point selection operation;

[0009] The target item number of the target configurable rule item associated with the target activity template is obtained, and it is judged whether the target item number is greater than a preset number threshold;

[0010] if the target number of items is greater than the preset number threshold, then according to the configuration operation of the user on the each target configurable rule item, a preset rule configuration strategy is used to configure the each target configurable rule item, to obtain rule configuration data corresponding to the configuration operation;

[0011] According to the target activity template and the rule configuration data, an activity interface configuration file is generated, and based on the activity interface configuration file, a newly created activity interface is rendered and displayed in the app.

[0012] In a second aspect, the present application provides an app activity interface creation system, comprising:

[0013] The display module is configured to display an activity configuration interface in response to an activity creation request of a user, wherein the activity configuration interface comprises an activity template selection area and a rule configuration area, and an activity template in the activity template selection area is associated with at least one configurable rule item in the rule configuration area;

[0014] The selection module is configured to recommend a candidate activity template matching the activity creation request from the activity template selection area using a preset template selection strategy, and determine a target activity template among the each candidate activity template based on a selection operation of the user;

[0015] The judgment module is configured to obtain a target number of items of target configurable rule items associated with the target activity template, and judge whether the target number of items is greater than a preset number threshold;

[0016] The configuration module is configured to, if the target number of items is greater than the preset number threshold, then according to the configuration operation of the user on the each target configurable rule item, a preset rule configuration strategy is used to configure the each target configurable rule item, to obtain rule configuration data corresponding to the configuration operation;

[0017] The generation module is configured to generate an activity interface configuration file according to the target activity template and the rule configuration data, and based on the activity interface configuration file, a newly created activity interface is rendered and displayed in the app.

[0018] In a third aspect, an electronic device is provided, comprising at least one processor, and a memory connected in communication with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the app activity interface creation method of any embodiment of the present application.

[0019] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program. When the program is executed by a processor, the processor executes the steps of the app activity interface creation method of any of the embodiments of the present application.

[0020] The app activity interface creation method and system of the present application effectively reduce the selection cost of the user by using the template recommendation model based on multi-dimensional feature matching, accurately evaluate the real complexity of the configuration task by using the rule item intelligent grouping mechanism based on dependency analysis and clustering algorithm, and adaptively use the unified configuration or phased guidance configuration strategy according to the evaluation result to ensure the clarity and accuracy of the configuration process. Finally, the high-performance, cross-platform compatible activity interface configuration file is generated through the template instantiation, device adaptation optimization and hierarchical serialization technology, thereby fundamentally solving the technical problems of the traditional activity interface configuration mode, such as blind template selection, chaotic complex configuration process, low interface generation efficiency and poor device compatibility, and greatly improving the intelligent level, operation efficiency and output quality of the activity interface configuration. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0022] Figure 1 A flow chart of an app activity interface creation method provided by an embodiment of the present application;

[0023] Figure 2 A structural block diagram of an app activity interface creation system provided by an embodiment of the present application;

[0024] Figure 3 A structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0026] Please refer to Figure 1FIG. 1 shows a flowchart of an app event interface new creation method according to an embodiment of the present application.

[0027] As shown in Figure 1 the app event interface new creation method specifically includes the following steps:

[0028] Step S101, in response to a user's event creation request, an event configuration interface is displayed, wherein the event configuration interface includes an event template selection area and a rule configuration area, and the event templates in the event template selection area are associated with at least one configurable rule item in the rule configuration area.

[0029] Step S102, a pre-set template selection strategy is used to recommend candidate event templates matching the event creation request from the event template selection area, and a target event template is determined among the candidate event templates based on the user's point selection operation.

[0030] In this step, the template features of each event template are obtained, including template type features, configuration complexity features, and usage frequency features;

[0031] The activity attribute information of the current event creation request is determined, including the activity type attribute, the target user group attribute, and the activity timeliness attribute;

[0032] According to the template features of each event template and the activity attribute information, the matching degree of each event template is determined;

[0033] According to the order from high to low of the matching degree, each event template is sorted, and the first K event templates are selected as candidate event templates, wherein K is an integer dynamically determined based on the display area of the template selection area in the event configuration interface.

[0034] In one embodiment, the feature portraits of the templates and events need to be constructed first:

[0035] Obtain and quantify the template features:

[0036] Template type features: extract the category it belongs to (such as "holiday marketing", "user acquisition", "brand promotion", etc.) from the template metadata, and convert it into One-hot encoding or through a word vector model into a numerical vector, so as to calculate the similarity.

[0037] Configuration complexity features: by analyzing the JSON Schema corresponding to the template, based on the number of rule items, types (such as whether nested configuration is needed), and complexity of constraint conditions, a normalized complexity score (for example, between 0.1 and 1.0) is calculated.

[0038] Usage frequency feature: Obtain the historical number of times this template has been selected from the system background and normalize it, or calculate its usage frequency proportion within a certain time period.

[0039] Determine the current activity attribute information:

[0040] Activity type attribute: Automatically identified through the activity creation form filled out by the user or through natural language processing analysis of the activity name / description input by the user.

[0041] Target user group attribute: According to user selection or system inference based on activity type (such as "young women in first-tier cities" or "all registered users"), and map it to predefined user group labels.

[0042] Activity timeliness attribute: According to the user's setting of the activity online time urgency, divide it into multiple levels (such as "high", "medium", "low"), or directly calculate the interval between the current time and the planned online time.

[0043] Build a matching degree calculation model, that is, use a multi-dimensional weighted scoring model to calculate the matching degree of each template and the current activity.

[0044] Dimension one: Type matching degree ( )

[0045] Calculation: Calculate the similarity between the activity type attribute and the template type feature. For example, use cosine similarity to compare the word vectors of the two, or directly perform exact matching / category tree matching.

[0046] Purpose: Ensure that the recommended template is functionally consistent with the user's Figure 1 intent.

[0047] Dimension two: Complexity adaptation degree ( )

[0048] Calculation: Establish an adaptation degree function. For example, =1-|template complexity-recommended complexity|. Where, the recommended complexity is dynamically determined according to the target user group: for internal operation personnel or technical users, the recommended complexity is higher; for beginners or activities targeting ordinary consumers, the recommended complexity is lower.

[0049] Purpose: Avoid recommending overly complex templates to novice users, or failing to meet the needs of advanced users due to overly simple templates.

[0050] Dimension three: Timeliness matching degree ( )

[0051] Calculation: = frequency feature x timeliness weight. Among them, the timeliness weight is set to a high value (such as 1.5) in emergency activities, and is set to 1.0 in regular activities. This means that for emergency activities, the system will preferentially recommend the user to the popular template that the user is more familiar with and faster to configure.

[0052] Objective: In emergency situations, preferentially recommend "out-of-the-box" efficient templates to improve configuration speed.

[0053] Comprehensive matching degree calculation:

[0054] The scores of the three dimensions are weighted and fused: matching degree .

[0055] The initial values of the weight coefficients a, b, and g can be set by experts, and can be dynamically optimized based on the actual selection behavior of users (for example, which dimension does the template the user finally selects have the highest score in) through algorithms such as gradient descent, so that the recommendation model becomes more and more accurate.

[0056] Dynamically determine and render the selected templates

[0057] Dynamically determine K value: not fixed to recommend 3 or 5 templates. It will get the client width and height of the DOM element of the activity template selection area through JavaScript, dynamically calculate how many template cards can be displayed completely in one row in this area according to the preset size and spacing of each template card, and this number is the K value. This ensures that the recommendation list can be fully presented without scrolling, optimizing the user experience.

[0058] In summary, a template recommendation model based on multi-dimensional feature matching and dynamic weight adjustment is constructed, which quantitatively analyzes the internal relationship between the type, complexity, and use frequency of the template and the type, target user, and timeliness of the current activity, etc. Properties, accurately and efficiently filter out a small number of selected templates that best meet the user's current needs from a large number of template libraries, and use the dynamic K value determination mechanism of interface size adaptation to achieve the optimal layout of the recommendation results in limited screen space. This scheme fundamentally solves the technical problems of traditional template selection methods that rely on user manual memory and search, low efficiency, and poor matching accuracy, greatly reducing the user's cognitive load and decision cost, and laying a solid foundation for the subsequent rule configuration link.

[0059] Step S103, obtaining the target item number of the target configurable rule item associated with the target activity template, and determining whether the target item number is greater than a preset number threshold.

[0060] In this step, the dependency relationship between each target configurable rule item is identified, each target configurable rule item is taken as a node in the graph, and a directed edge is established between the corresponding nodes according to the dependency relationship to form a rule item dependency graph, wherein the dependency relationship includes a conditional dependency relationship, a data dependency relationship, and a time sequence dependency relationship;

[0061] Based on the history record of the user configuration data, the co-occurrence frequency of the first target configurable rule item and the second target configurable rule item configured by the same user in the same session in the past configuration record is counted, wherein the first target configurable rule item and the second target configurable rule item are any two target configurable rule items in each target configurable rule item;

[0062] The labels and description texts of the first target configurable rule item and the second target configurable rule item are analyzed, and the semantic similarity between the first target configurable rule item and the second target configurable rule item is calculated through a pre-trained word vector model;

[0063] The co-occurrence frequency is configured with a first correlation degree score, and the semantic similarity is configured with a second correlation degree score, the first correlation degree score and the second correlation degree score are weighted and fused to obtain The final correlation degree score of each pair of target configurable rule items in the global correlation degree matrix M, that is, the global correlation degree matrix M is obtained.

[0064] Based on the rule item dependency graph and the global correlation degree matrix M, a hierarchical clustering algorithm is used to perform clustering analysis on each target configurable rule item to obtain at least one composite rule item, and the number of the at least one composite rule item is defined as the target item number.

[0065] In the specific implementation process, node creation: each rule item (such as "activity budget", "start time") is created as a node in the graph

[0066] Dependency relationship identification and edge building:

[0067] Conditional dependency: if the value of rule item A affects the display state of rule item B (such as selecting "paid activity" to display "paid amount"), a directed edge A→B is established;

[0068] Data dependency: if the value of rule item A is used as the default value or calculation basis of rule item B (such as "total number of people" affecting "per capita limit"), a directed edge A→B is established;

[0069] Time sequence dependency: if rule item A must be configured before rule item B (such as setting "activity type" first to set "type parameter"), a directed edge A→B is established;

[0070] Graph structure storage: Finally form a directed graph data structure, clearly show all the logical constraints between the rules.

[0071] System analysis of rule item relevance from user behavior and data semantics:

[0072] Co-occurrence frequency analysis: From the user configuration log, statistics of any two rules in the history of configuration session configured by the same user. High frequency co-occurrence of rules to obtain higher first correlation degree score;

[0073] Semantic similarity analysis: Use pre-trained Word2Vec or BERT word vector model, the label and description text of the rule item is converted into vector, calculate the cosine similarity as the second correlation degree score;

[0074] Matrix construction: Create an N × N symmetric matrix M, where each element is the weighted sum of co-occurrence frequency score and semantic similarity score, complete the description of the association strength between all rules.

[0075] Based on the above two analysis results, the system carries out intelligent grouping:

[0076] Cluster initialization: Take the correlation matrix M as input, use the bottom-up hierarchical clustering algorithm, initially consider each rule item as a separate cluster;

[0077] Iterative merging: In each iteration, the two clusters with the highest correlation are merged to form a new composite rule item;

[0078] Dependency relationship verification: Before and after each merge, check the connectivity of the merged rule items in the dependency graph. Only allow merging those that are tightly connected in the dependency graph, to ensure that each composite rule item is a logically self-consistent configuration unit;

[0079] Termination condition: When the correlation between clusters is lower than the preset threshold, or the expected number of clusters is reached, stop clustering.

[0080] Target item number determination:

[0081] The final number of composite rule items (including independent rule items not involved in merging) is taken as the target item number. For example, the original 28 rules may be clustered into 7 composite rules, and the target item number is 7.

[0082] In this embodiment, the logical constraint model is constructed by identifying the condition dependency, data dependency and time sequence dependency between the rule items, and the correlation matrix is calculated by combining the historical co-occurrence frequency and semantic similarity, and the composite rule items are generated by using the hierarchical clustering algorithm under the premise of ensuring the logical connectivity, so as to realize the accurate quantification of the configuration workload. This method fundamentally solves the technical defects that the traditional statistical method cannot distinguish the internal relevance of the rule items and cannot accurately reflect the real configuration complexity, provides a reliable basis for the subsequent differentiated configuration strategy selection based on threshold judgment, and significantly improves the intelligent level of the complex activity interface configuration.

[0083] In one specific embodiment, after judging whether the target item number is greater than the preset number threshold, if the target item number is not greater than the preset number threshold, the target configurable rule items are directly configured according to the configuration operation of the user on each target configurable rule item, and rule configuration data corresponding to the configuration operation is obtained. For example, the preset number threshold is set to 1.

[0084] In step S104, if the target item number is greater than the preset number threshold, the target configurable rule items are configured according to the configuration operation of the user on each target configurable rule item by using a preset rule configuration strategy, and rule configuration data corresponding to the configuration operation is obtained.

[0085] In this step, the configuration process of each target configurable rule item is divided into at least one continuous configuration stage, wherein each configuration stage corresponds to a composite rule item or a group of associated independent rule items, wherein the independent rule item is a rule item containing only one target configurable rule item;

[0086] According to the current configuration stage, the corresponding configuration interface is dynamically rendered in the rule configuration area, and only the target configurable rule item required for configuration in the current configuration stage is displayed;

[0087] Based on the rule item values configured by the user in the current stage and the previous stage, the configuration interface is dynamically optimized by a preset optimization method, wherein the preset optimization method includes:

[0088] According to the condition dependency relationship, the optional range or display state of the subsequent target configurable rule item is dynamically adjusted; according to the data dependency relationship, the recommended value or default value of the related target configurable rule item is automatically calculated and filled;

[0089] When all the configuration stages are completed, global configuration optimization is performed to obtain rule configuration data corresponding to the configuration operation.

[0090] In this embodiment, the configuration process is automatically divided into M consecutive stages based on the set of composite rule items obtained from the clustering analysis in step S103. Each stage focuses on configuring one composite rule item (e.g., the "budget and resources" stage) or a group of semantically closely related independent rule items (e.g., the "basic information" stage, which may include several independent input items such as the event title, event description, etc.).

[0091] Establishing a configuration state machine: The system initializes a configuration state machine to precisely manage the life cycle of each stage. This state machine explicitly records the current stage number, completed stages, configuration status of each stage (not started, in progress, completed), and defines the transition conditions between stages (usually based on the validation of all mandatory items in the current stage).

[0092] Dynamic interface rendering:

[0093] The system dynamically renders a form interface in the rule configuration area that only includes the rule items required for the current stage based on the current configuration stage.

[0094] The interface clearly displays a configuration progress bar indicating the current stage and overall progress.

[0095] Dynamic optimization of the configuration process:

[0096] Dynamic UI based on conditional dependencies: The system monitors the user's configuration operations in the current stage in real time. Using the pre-built rule item dependency graph, when the user configures a certain rule item, the system will immediately calculate and update the status of subsequent rule items. For example, in the current "reward setting" stage, when the user selects "reward type" as "physical prize", the system will immediately display the previously hidden "shipping address collection" configuration item.

[0097] Intelligent filling based on data dependencies: Based on the values the user has configured in the current and previous stages, the system automatically calculates and fills in recommended or default values for subsequent rule items through predefined logic rules. For example, after the user sets "total budget" and "total number of people", when entering the "personal reward" configuration stage, the system can automatically calculate and suggest a "per capita budget cap".

[0098] Configuration result integration and global optimization:

[0099] Data staging and verification: After the user completes all configurations for a stage, they need to click "Next" or "Complete this stage". The system performs a stage-by-stage check on the data in this stage to ensure that mandatory items are complete, data formats are correct, and logical constraints are met. After passing, the data is temporarily stored and the state machine advances to the next stage.

[0100] Global configuration optimization: After all M configuration stages are completed, the system does not simply package the data, but performs a global configuration optimization:

[0101] Conflict detection and resolution: Check if there are logical conflicts across stages (e.g., end time of an activity is earlier than start time). If conflicts are found, the user is prompted and provided with automatic repair suggestions.

[0102] Redundant configuration analysis: Identify and prompt the user of possible redundant or inefficient configuration combinations.

[0103] Parameter tuning suggestions: Based on historical successful activity data models, give optimization suggestions for key parameters (such as budget allocation ratio).

[0104] Generate rule configuration data: Finally, the system integrates all stage configuration data and incorporates the results of global optimization to generate complete, consistent and optimized rule configuration data (a structured JSON object) for subsequent form generation.

[0105] In summary, by breaking down the complex configuration task into successive stages based on composite rule items, dynamically rendering focused configuration interfaces at each stage, utilizing conditional and data dependencies between rule items for real-time optimization of interface interaction and intelligent value filling recommendations, and finally ensuring data consistency and rationality through global configuration optimization, this solution fundamentally addresses the technical difficulties of user cognitive overload, configuration logic confusion, and high error rate caused by traditional one-time configuration methods when facing massive rule items, achieving a significant improvement in configuration efficiency and user experience of complex activity interfaces while ensuring configuration accuracy.

[0106] Step S105, according to the target activity template and the rule configuration data, generate an activity interface configuration file, and based on the activity interface configuration file, render and display the newly created activity interface in the app.

[0107] In this step, the rule configuration data is mapped to the corresponding configuration nodes of the target activity template, completing template instantiation to obtain an initial activity interface;

[0108] Based on device screen characteristics and performance parameters, the initial activity interface is optimized to obtain an optimized activity interface, wherein the optimization includes layout adjustment, resource compression and rendering optimization;

[0109] The optimized activity interface and rule configuration data are serialized into a standardized interface description file;

[0110] The interface description file is compressed and encrypted to generate the final activity interface configuration file, wherein the activity interface configuration file adopts a hierarchical storage structure, including an interface layout layer, a business logic layer and a data binding layer.

[0111] Based on the activity interface configuration file, the newly created activity interface is rendered and displayed in the app.

[0112] In this embodiment, node mapping is configured: the system reads the JSON Schema structure of the target activity template and establishes a mapping relationship between each field in the rule configuration data and the template node. For example, "activityTitle":"Anniversary Celebration" in the rule configuration data will be mapped to the corresponding title text node in the template;

[0113] Dynamic content injection: Based on the mapping relationship, the system creates a template instantiation engine and injects the rule configuration data into the corresponding location of the template.

[0114] Generate the initial DOM structure: The engine performs rendering, generating the initial HTML structure containing all static content and dynamic data, forming the initial active interface;

[0115] For the initial activity interface, perform the following optimization operations, including but not limited to:

[0116] Layout adjustments:

[0117] CSS Media Queries are used to detect device screen size and dynamically adjust the layout.

[0118] For mobile devices with small screens, automatically convert multi-column layouts to single-column flow layouts;

[0119] Element sizes are recalculated based on viewport width percentage to ensure readability of key content across different devices;

[0120] Resource compression:

[0121] Image resource processing: Select images of appropriate sizes based on device DPI, convert PNG format to WebP format, and use lossy compression algorithms to reduce image size by 60%-80%;

[0122] Code minification: Remove whitespace and comments from HTML / CSS / JS, and obfuscate and minify JavaScript variables;

[0123] Resource merging: Combines multiple small CSS / JS files into a single file, reducing the number of HTTP requests;

[0124] Rendering optimization:

[0125] Add the loading="lazy" attribute to images and components that are not displayed on the first screen to implement lazy loading;

[0126] Add the CSS will-change property to frequently changing dynamic elements to enable GPU acceleration;

[0127] Generate critical CSS and inline it to the HTML head to ensure fast rendering of the first screen content.

[0128] Standardized serialization: serialize the optimized interface structure, styles, logic, and data uniformly;

[0129] Hierarchical storage structure construction:

[0130] Interface layout layer: stores the optimized HTML structure and CSS styles, responsible for visual presentation;

[0131] Business logic layer: stores activity rules, interaction logic, and conditional judgments, handles user interaction;

[0132] Data binding layer: stores dynamic data models and API interface definitions, manages data flow.

[0133] The final activity interface configuration file is distributed to user devices through CDN, and the rendering engine in the APP receives the file:

[0134] Decrypt and decompress the configuration file;

[0135] Parse the contents of the layout layer, logic layer, and data layer by layer;

[0136] Construct the interface layer by layer in the APP WebView or native rendering engine;

[0137] Establish data binding and activate interaction logic;

[0138] Finally, show the complete and interactive activity interface to the user.

[0139] In summary, the method of the present application constructs a complete technical system from intelligent template selection, accurate configuration complexity evaluation to efficient interface generation. Through the template recommendation model based on multi-dimensional feature matching, the user's selection cost is effectively reduced. The rule item intelligent grouping mechanism based on dependency analysis and clustering algorithm accurately evaluates the true complexity of the configuration task. According to the evaluation results, the unified configuration or phased guided configuration strategy is adaptively adopted to ensure the clarity and accuracy of the configuration process. Finally, through template instantiation, device adaptation optimization, and hierarchical serialization technology, the high-performance, cross-platform compatible activity interface configuration file is generated. Thus, the technical difficulties of traditional activity interface configuration methods such as blind template selection, chaotic complex configuration process, low interface generation efficiency, and poor device compatibility are fundamentally solved, greatly improving the intelligent level, operation efficiency, and output quality of activity interface configuration.

[0140] Please refer toFigure 2 Fig. 1 shows a structural block diagram of an app activity interface new creation system according to an embodiment of the present application.

[0141] As shown in Figure 2 Fig. 2, the app activity interface new creation system 200 includes a display module 210, a selection module 220, a judgment module 230, a configuration module 240 and a generation module 250.

[0142] The display module 210 is configured to display an activity configuration interface in response to a user's activity creation request, wherein the activity configuration interface includes an activity template selection area and a rule configuration area, and an activity template in the activity template selection area is associated with at least one configurable rule item in the rule configuration area. The selection module 220 is configured to recommend candidate activity templates matching the activity creation request from the activity template selection area by using a preset template selection strategy, and determine a target activity template among the candidate activity templates based on the user's point selection operation. The judgment module 230 is configured to obtain a target item number of target configurable rule items associated with the target activity template, and judge whether the target item number is greater than a preset number threshold. The configuration module 240 is configured to, if the target item number is greater than the preset number threshold, configure the target configurable rule items by using a preset rule configuration strategy according to the user's configuration operation on the target configurable rule items, to obtain rule configuration data corresponding to the configuration operation. The generation module 250 is configured to generate an activity interface configuration file according to the target activity template and the rule configuration data, and render and display a newly created activity interface in an app based on the activity interface configuration file.

[0143] It should be understood that Figure 2 the modules described in the above Figure 1 correspond to the steps in the methods described with reference to the Figure 2 above. Therefore, the operations and features described above for the methods and the corresponding technical effects also apply to the modules in , and will not be described here again.

[0144] In some other embodiments, the present application also provides a computer readable storage medium having a computer program stored thereon, wherein the program instructions are executed by a processor to cause the processor to perform the app activity interface new creation method in any of the method embodiments described above.

[0145] As an implementation form, the computer readable storage medium of the present application stores computer executable instructions, and the computer executable instructions are configured to:

[0146] In response to a user's activity creation request, an activity configuration interface is displayed, wherein the activity configuration interface includes an activity template selection area and a rule configuration area, and the activity template in the activity template selection area is associated with at least one configurable rule item in the rule configuration area;

[0147] A preset template selection strategy is used to recommend candidate activity templates that match the activity creation request from the activity template selection area, and the target activity template is determined from each candidate activity template based on the user's click operation;

[0148] Obtain the number of target items associated with the target configurable rule items of the target activity template, and determine whether the number of target items is greater than a preset quantity threshold;

[0149] If the number of target items is greater than a preset quantity threshold, then according to the user's configuration operation on each target configurable rule item, a preset rule configuration strategy is used to configure each target configurable rule item to obtain rule configuration data corresponding to the configuration operation.

[0150] Based on the target activity template and the rule configuration data, an activity interface configuration file is generated, and the newly created activity interface is rendered and displayed in the app based on the activity interface configuration file.

[0151] Computer-readable storage media may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required for at least one function; the data storage area may store data created during the use of the system created based on the app's active interface. Furthermore, the computer-readable storage medium may include high-speed random access memory, and may also include memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include memory remotely configured relative to a processor, which can be connected to the app's active interface to create the system via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0152] Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present invention, such as... Figure 3 As shown, the device includes a processor 310 and a memory 320. The electronic device may also include an input device 330 and an output device 340. The processor 310, memory 320, input device 330, and output device 340 can be connected via a bus or other means. Figure 3The bus is taken as an example. The memory 320 is the computer readable storage medium described above. The processor 310 executes various function applications and data processing of the server, i.e., implements the method embodiment app activity interface new creation method, by running the non-volatile software programs, instructions and modules stored in the memory 320. The input device 330 can receive input digital or character information and generate key signal input related to user settings and function control of the app activity interface new creation system. The output device 340 can include a display device such as a display screen.

[0153] The electronic device described above can execute the method provided by the embodiment of the application, has the function modules and beneficial effects corresponding to the execution method. Technical details not described in detail in the embodiment can refer to the method provided by the embodiment of the application.

[0154] As an implementation manner, the electronic device described above is applied to an app activity interface new creation system for a client, and includes at least one processor and a memory in communication connection with the at least one processor. The memory stores instructions executable by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to:

[0155] In response to an activity creation request of a user, an activity configuration interface is displayed. The activity configuration interface includes an activity template selection area and a rule configuration area. An activity template in the activity template selection area is associated with at least one configurable rule item in the rule configuration area.

[0156] A preset template selection strategy is used to recommend candidate activity templates matching the activity creation request from the activity template selection area, and a target activity template is determined among the candidate activity templates based on a point selection operation of the user.

[0157] A target item number of target configurable rule items associated with the target activity template is obtained, and it is determined whether the target item number is greater than a preset number threshold.

[0158] If the target item number is greater than the preset number threshold, the preset rule configuration strategy is used to configure the target configurable rule items according to a configuration operation of the user on the target configurable rule items, to obtain rule configuration data corresponding to the configuration operation.

[0159] An activity interface configuration file is generated according to the target activity template and the rule configuration data, and a newly created activity interface is rendered and displayed in an app based on the activity interface configuration file.

[0160] Those skilled in the art can clearly understand the technical solutions of the various embodiments from the above description of the embodiments, and the various embodiments can be implemented by means of software with the necessary general hardware platforms, and of course can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, and the like, and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of the various embodiments or some parts of the embodiments.

[0161] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features therein; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An app activity interface creation method, characterized in that, The method comprises the following steps: displaying an activity configuration interface in response to a user's activity creation request, wherein the activity configuration interface comprises an activity template selection area and a rule configuration area, and an activity template in the activity template selection area is associated with at least one configurable rule item in the rule configuration area; adopting a preset template selection strategy to recommend candidate activity templates matching the activity creation request from the activity template selection area, and determining a target activity template among the candidate activity templates based on the user's point selection operation; obtaining a target item number of target configurable rule items associated with the target activity template, and judging whether the target item number is greater than a preset number threshold, comprising: identifying a dependency relationship between each target configurable rule item, taking each target configurable rule item as a node in a graph, establishing a directed edge between the corresponding nodes according to the dependency relationship, and forming a rule item dependency graph, wherein the dependency relationship comprises a conditional dependency relationship, a data dependency relationship and a time sequence dependency relationship; based on the historical record of user configuration data, the co-occurrence frequency of the first target configurable rule item and the second target configurable rule item being configured by the same user in the same session in the past configuration record is counted, wherein the first target configurable rule item and the second target configurable rule item are any two target configurable rule items in the target configurable rule items; analyzing the labels and description texts of the first target configurable rule item and the second target configurable rule item, and calculating the semantic similarity between the first target configurable rule item and the second target configurable rule item through a pre-trained word vector model; a first correlation degree score is configured for the co-occurrence frequency, and a second correlation degree score is configured for the semantic similarity, the first correlation degree score and the second correlation degree score are weighted and fused to obtain a final correlation degree score of each pair of target configurable rule items in the global correlation degree matrix M, that is, a global correlation degree matrix M is obtained. a first correlation degree score is configured for the co-occurrence frequency, and a second correlation degree score is configured for the semantic similarity, the first correlation degree score and the second correlation degree score are weighted and fused to obtain a final correlation degree score of each pair of target configurable rule items in the global correlation degree matrix M, that is, a global correlation degree matrix M is obtained. based on the rule item dependency graph and the global correlation matrix M, a hierarchical clustering algorithm is adopted to perform clustering analysis on each target configurable rule item, and at least one composite rule item is obtained, and the number of the at least one composite rule item is defined as the target item number; if the target item number is greater than the preset number threshold, the preset rule configuration strategy is adopted to configure each target configurable rule item according to the user's configuration operation on each target configurable rule item, and rule configuration data corresponding to the configuration operation is obtained; based on the target activity template and the rule configuration data, an activity interface configuration file is generated, and a newly created activity interface is rendered and displayed in the app based on the activity interface configuration file.

2. The method of claim 1, wherein, The method comprises the following steps: obtaining the template features of each activity template, wherein the template features comprise template type features, configuration complexity features and use frequency features; determining the activity attribute information of the current activity creation request, wherein the activity attribute information comprises activity type attributes, target user group attributes and activity timeliness attributes; determining the matching degrees of the activity templates according to the template features of the activity templates and the activity attribute information; The activity templates are sorted according to the matching degrees from high to low, and the first K activity templates are selected as candidate activity templates, where K is an integer dynamically determined based on a display area of a template selection region in the activity configuration interface.

3. The method of claim 1, wherein, After determining whether the target item number is greater than the preset number threshold, the method further includes: If the target item number is not greater than the preset number threshold, the target configurable rule items are directly configured according to the configuration operation of the user on the target configurable rule items, to obtain rule configuration data corresponding to the configuration operation.

4. The method of claim 1, wherein, The rule configuration data corresponding to the configuration operation is obtained by configuring the target configurable rule items according to the configuration operation of the user on the target configurable rule items, using a preset rule configuration strategy. The configuration process of the target configurable rule items is divided into at least one continuous configuration stage, and each configuration stage corresponds to a composite rule item or a group of associated independent rule items, wherein the independent rule item is a rule item containing only one target configurable rule item; According to the current configuration stage, a corresponding configuration interface is dynamically rendered in a rule configuration region, and only the target configurable rule items required to be configured in the current configuration stage are displayed; Based on the rule item values configured by the user in the current stage and the previous stages, the configuration interface is dynamically optimized by a preset optimization method, wherein the preset optimization method includes: According to the condition dependency relationship, the selectable range or display state of the subsequent target configurable rule item is dynamically adjusted; and according to the data dependency relationship, the recommended value or default value of the related target configurable rule item is automatically calculated and filled; When all configuration stages are completed, global configuration optimization is performed to obtain rule configuration data corresponding to the configuration operation.

5. The method of claim 1, wherein, The activity interface configuration file is generated according to the target activity template and the rule configuration data, including: The rule configuration data is mapped to the corresponding configuration node of the target activity template to complete template instantiation, to obtain an initial activity interface; Based on device screen characteristics and performance parameters, the initial activity interface is adaptively optimized to obtain an optimized activity interface, wherein the adaptive optimization includes layout adjustment, resource compression, and rendering optimization; The optimized activity interface and the rule configuration data are serialized into a standardized interface description file; The interface description file is compressed and encrypted to generate a final activity interface configuration file, wherein the activity interface configuration file adopts a hierarchical storage structure, including an interface layout layer, a business logic layer, and a data binding layer.

6. An app activity interface creation system, characterized by, The display module is configured to display an activity configuration interface in response to a user activity creation request, wherein the activity configuration interface includes an activity template selection region and a rule configuration region, and the activity templates in the activity template selection region are associated with at least one configurable rule item in the rule configuration region. ​ The selecting module is configured to select a target activity template from the candidate activity templates based on a selection operation of the user, by using a preset template selection strategy to select the candidate activity templates matching the activity creation request from the active template selection area. The judging module is configured to obtain a target number of target configurable rule items associated with the target activity template, and judge whether the target number is greater than a preset number threshold, including: identifying a dependency relationship between the target configurable rule items, taking each target configurable rule item as a node in a graph, establishing a directed edge between the corresponding nodes according to the dependency relationship, and forming a rule item dependency graph, wherein the dependency relationship includes a conditional dependency relationship, a data dependency relationship, and a time sequence dependency relationship; based on a historical record of user configuration data, counting a co-occurrence frequency of a first target configurable rule item and a second target configurable rule item being configured by the same user in the same session in past configuration records, wherein the first target configurable rule item and the second target configurable rule item are any two target configurable rule items in the target configurable rule items; analyzing the labels and description texts of the first target configurable rule item and the second target configurable rule item, and calculating a semantic similarity between the first target configurable rule item and the second target configurable rule item by using a pre-trained word vector model; a first correlation degree score is configured for the co-occurrence frequency, and a second correlation degree score is configured for the semantic similarity, the first correlation degree score and the second correlation degree score are weighted and fused to obtain a final correlation degree score of each pair of target configurable rule items in the global correlation degree matrix M, that is, a global correlation degree matrix M is obtained. a first correlation degree score is configured for the co-occurrence frequency, and a second correlation degree score is configured for the semantic similarity, the first correlation degree score and the second correlation degree score are weighted and fused to obtain a final correlation degree score of each pair of target configurable rule items in the global correlation degree matrix M, that is, a global correlation degree matrix M is obtained. based on the rule item dependency graph and the global correlation matrix M, using a hierarchical clustering algorithm to perform clustering analysis on the target configurable rule items, obtaining at least one composite rule item, and defining the number of the at least one composite rule item as the target number; The configuration module is configured to, if the target number is greater than the preset number threshold, configure the target configurable rule items according to the configuration operation of the user on the target configurable rule items by using a preset rule configuration strategy, and obtain rule configuration data corresponding to the configuration operation. The generating module is configured to generate an activity interface configuration file according to the target activity template and the rule configuration data, and render and display a newly created activity interface in the app based on the activity interface configuration file.

7. An electronic device, comprising: comprising: at least one processor, and a memory connected to the at least one processor in communication, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 5.

8. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the method of any one of claims 1 to 5.

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