Client user behavior restoration method and device, electronic equipment and storage medium

Abstract

The invention provides a client user behavior restoration method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a target user ID and a target time period of a target user needing behavior restoration; according to the target user ID and a target time period, capturing target front-end and rear-end interaction data of the target user in the target time period; based on the target front-end and back-end interaction data, a moment corresponding to each interface interaction triggered by the target user in the target time period is determined, and the target front-end and back-end interaction data comprises multiple interface interactions; and according to the moment corresponding to each interface interaction, executing each interface interaction in sequence, and restoring to obtain restored behavior data of the target user in the target time period. Through the method and the device, the problem that the problem analysis process is large in workload and tedious due to the fact that the user behavior cannot be quickly restored in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of data backtracking technology, and in particular to a method and apparatus for restoring client user behavior, an electronic device, and a storage medium. Background Technology

[0002] Currently, users frequently encounter unexpected page displays, results, and errors when using the app for business operations, leading to customer complaints. These complaints then need to be addressed by the relevant business teams. Sometimes, user descriptions are vague, requiring analysis and deduction based on user actions, page display styles, and backend interaction feedback. This process is tedious, especially when handling multiple complaints, significantly increasing time and effort required and slowing down problem localization. It also heavily relies on backend, client-side, H5, and product personnel. Existing analysis methods involve accessing a company-specific server, writing custom SQL queries to retrieve relevant user backend data, manually filtering useful requests and responses, examining user action paths via APIs, saving each API's data locally, and manually mocking the backend data returned by each API through third-party tools like Charles in the app. The mock data, created for query purposes, mimics the data format and structure that might be returned from the real system. Then, it is speculated that the above process may be repeated to query more interface data as needed for problem analysis, which is labor-intensive and tedious.

[0003] Therefore, the relevant technologies have the problem of being unable to quickly reconstruct user behavior, which leads to a large workload and cumbersome process in analyzing the problem. Summary of the Invention

[0004] This application provides a method and apparatus for reconstructing client user behavior, an electronic device, and a storage medium to at least solve the problem of large workload and cumbersome process in the analysis of related technologies.

[0005] According to one aspect of the embodiments of this application, a method for reconstructing client user behavior is provided, including:

[0006] Obtain the target user ID and target time period of the target user whose behavior needs to be reconstructed;

[0007] Based on the target user ID and the target time period, capture the target user's front-end and back-end interaction data during the target time period;

[0008] Based on the target front-end and back-end interaction data, the time corresponding to each interface interaction triggered by the target user in the target time period is determined, wherein the target front-end and back-end interaction data includes multiple interface interactions;

[0009] According to the time corresponding to each interface interaction, each interface interaction is executed sequentially to restore the target user's behavior data in the target time period.

[0010] Optionally, as described above, the step of capturing the target user's front-end and back-end interaction data within the target time period according to the target user ID and the target time period includes:

[0011] Based on the target user ID and the target time period, filter all candidate interaction data to obtain the original front-end and back-end interaction data within the target time period and corresponding to the target user ID;

[0012] The target front-end and back-end interaction data that meets the target business conditions is obtained by filtering from the original front-end and back-end interaction data.

[0013] Optionally, as described above, the method further includes:

[0014] The target front-end and back-end interaction data is cached in memory;

[0015] The step of determining the time corresponding to each interface interaction triggered by the target user within the target time period based on the target front-end and back-end interaction data includes: determining the time corresponding to each interface interaction triggered by the target user within the target time period based on the target front-end and back-end interaction data in memory.

[0016] Optionally, as described above, the step of sequentially executing each interface interaction according to the time corresponding to each interface interaction to reconstruct the target user's behavior data in the target time period includes:

[0017] Based on the time corresponding to each interface interaction, all interface interactions are sorted to obtain the behavioral trajectory path of the target user;

[0018] Based on the interface information corresponding to each interface interaction in the behavior trajectory path, the restored behavior sub-data corresponding to each interface interaction is obtained;

[0019] The restoration behavior data is obtained based on all restoration behavior sub-data.

[0020] Optionally, as described above, the step of reconstructing the restored behavior sub-data corresponding to each interface interaction according to the interface information corresponding to each interface interaction in the behavior trajectory path includes:

[0021] When the type of interface information corresponding to the interface interaction is page node data, based on the interface information and the time corresponding to the interface interaction, a request is made to obtain the response page at the time corresponding to the interface interaction, which serves as the sub-data of the restoration behavior. The page node data is used to indicate the status information of each component on the page corresponding to the interface interaction.

[0022] When the type of interface information corresponding to the interface interaction is a functional interaction, obtain the response data that is responded to after the functional interaction request is made at the time corresponding to the interface interaction, and serves as the sub-data of the restoration behavior.

[0023] Optionally, as described above, the method further includes:

[0024] Obtain the specified page with the problem specified by the target user, and create response data corresponding to the target interface interaction performed by the target user on the specified page based on the target front-end and back-end interaction data;

[0025] Based on the response data, the target question corresponding to the target interface interaction is determined.

[0026] Optionally, as described above, determining the target question corresponding to the target interface interaction based on the response data includes:

[0027] If a mismatch is determined between the request data and the response data based on the interaction with the target interface, the target problem is determined to be a page interaction problem; or,

[0028] If an abnormal page display is determined based on the request and response data of the target interface interaction, the problem type corresponding to the target problem is determined, wherein the problem type includes: abnormal backend data return and incompatibility of client page display.

[0029] According to another aspect of the embodiments of this application, a client user behavior restoration device is also provided, comprising:

[0030] The acquisition module is used to obtain the target user ID and target time period of the target user whose behavior needs to be restored;

[0031] The crawling module is used to crawl the target user's front-end and back-end interaction data during the target time period according to the target user ID and the target time period.

[0032] The determining module is used to determine, based on the target front-end and back-end interaction data, the time corresponding to each interface interaction triggered by the target user in the target time period, wherein the target front-end and back-end interaction data includes multiple interface interactions;

[0033] The restoration module is used to execute each interface interaction sequentially according to the time corresponding to each interface interaction, and restore the restoration behavior data of the target user in the target time period.

[0034] According to another aspect of the embodiments of this application, an electronic device is also provided, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; wherein the memory is used to store a computer program; and the processor is used to execute the method steps of any of the above embodiments by running the computer program stored in the memory.

[0035] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to execute the method steps of any of the above embodiments when running.

[0036] In this embodiment, the method of determining the restored behavior data based on user ID and time period is adopted. This involves obtaining the target user ID and target time period of the target user to be restored; capturing the target front-end and back-end interaction data of the target user within the target time period according to the target user ID and target time period; determining the time corresponding to each interface interaction triggered by the target user within the target time period based on the target front-end and back-end interaction data, wherein the target front-end and back-end interaction data includes multiple interface interactions; and executing each interface interaction sequentially according to the time corresponding to each interface interaction to restore the restored behavior data of the target user within the target time period. Since the restored behavior data can be obtained by restoring the target front-end and back-end interaction data captured based on the target user ID and target time period, the target user's behavior within the target time period can be automatically determined. This achieves the technical effect of quickly determining the user's behavior within a specific time period, thereby solving the problem in related technologies where user behavior cannot be quickly restored, leading to a large and cumbersome workload in the problem analysis process. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of the hardware environment for an optional client user behavior restoration method according to an embodiment of this application;

[0040] Figure 2 This is a flowchart illustrating an optional client user behavior restoration method according to an embodiment of this application;

[0041] Figure 3 This is a flowchart illustrating another optional client user behavior restoration method according to an embodiment of this application;

[0042] Figure 4 This is a flowchart illustrating another optional native page interception and mock implementation method according to an embodiment of this application;

[0043] Figure 5 This is a flowchart illustrating another optional H5 page interception and mock implementation method according to an embodiment of this application;

[0044] Figure 6 This is a structural block diagram of an optional client user behavior restoration device according to an embodiment of this application;

[0045] Figure 7 This is a structural block diagram of an optional electronic device according to an embodiment of this application. Detailed Implementation

[0046] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0047] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0048] First, some nouns or terms that appear in the description of the embodiments of this application shall be interpreted as follows:

[0049] Mock data refers to fake data created for testing or development purposes. This data mimics the data format and structure that may be returned in a real system. By using mock data, the front-end or other parts that depend on this data can continue to be developed and tested even when the back-end service is incomplete or unavailable.

[0050] According to one aspect of the embodiments of this application, a method for reconstructing client user behavior is provided. Optionally, in this embodiment, the above-described client user behavior reconstruction method can be applied to, for example... Figure 1 The hardware environment shown consists of terminal 1402 and server 1404. For example... Figure 1 As shown, server 1404 is connected to terminal 1402 via a network and can be used to provide services (such as game services, application services, etc.) to the terminal or clients installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 1404.

[0051] The aforementioned network may include, but is not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network, metropolitan area network, local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth. The terminal is not limited to PC, mobile phone, tablet computer, etc.

[0052] The client-side user behavior restoration method of this application embodiment can be executed by a server, a terminal, or both. Specifically, the client-side user behavior restoration method of this application embodiment can also be executed by a client installed on the terminal.

[0053] Taking the client user behavior restoration method in this embodiment as an example, which is executed by the server, Figure 2 A method for restoring client user behavior provided in this application includes the following steps:

[0054] Step S202: Obtain the target user ID and target time period of the target user whose behavior needs to be restored.

[0055] The client-side user behavior reconstruction method in this embodiment can be applied to scenarios where users, while performing business operations using clients such as apps or browsers, encounter unexpected page displays, results, or errors, prompting customer complaints to the relevant business departments. These complaints need to be processed, but user descriptions are sometimes vague. Therefore, it is necessary to reconstruct the client-side user behavior based on the user's previous and subsequent actions, the page display styles and content they saw, and backend interaction feedback. Furthermore, the above-described client-side user behavior reconstruction method is also applicable to other types of scenarios, provided there are no contradictions.

[0056] Specifically, the target user ID and target time period can be determined by the user ID and target time period carried in the customer complaint form. The target user ID can be a UID (i.e., user identifier, UserID). The target time period can be represented by its start and end times.

[0057] Step S204: Based on the target user ID and the target time period, capture the target user's front-end and back-end interaction data during the target time period.

[0058] Specifically, after determining the target user ID and the target time period, the target user ID and the target time period can be used as query conditions to query the log storage platform to capture the target user's front-end and back-end interaction data during the target time period.

[0059] As an optional implementation, step S204 can be implemented by capturing the target user's front-end and back-end interaction data within the target time period according to the target user ID and the target time period: filtering all candidate interaction data according to the target user ID and the target time period to obtain the original front-end and back-end interaction data corresponding to the target user ID within the target time period; and filtering the original front-end and back-end interaction data to obtain the target front-end and back-end interaction data that meets the target business conditions. Specifically, all candidate interaction data can be storage logs in the storage platform. Furthermore, by first using the target user ID as a filtering condition, all interaction data between the target user and the back-end can be captured from the storage logs. Simultaneously, the start and end times within the aforementioned target time period are set as key conditions for querying, further filtering can be performed to obtain the original front-end and back-end interaction data corresponding to the target user ID within the target time period from all interaction data between the target user and the back-end. After obtaining the original front-end and back-end interaction data, in order to accurately determine the data corresponding to the target business where the target user reported an anomaly, this embodiment can also filter the target front-end and back-end interaction data using the filtering conditions corresponding to the target business (i.e., target business conditions) to obtain the target front-end and back-end interaction data that meets the target business conditions. Business conditions can be business-related, meaning additional filtering conditions set according to the specific needs of the target business. These conditions can help further filter data related to the target business. For example, examples of business-related conditions may include, but are not limited to: operation type conditions, such as only querying purchase behavior (POST / api / orders) and ignoring other types of requests such as browsing product details; response status codes, such as only selecting successful responses (status code 200) and excluding all error or redirect responses; API paths, querying for specific API paths, such as only considering requests involving user personal information ( / api / users / {userId}); geolocation, if the application supports multi-region services, data can be filtered based on the user's geolocation; device type, distinguishing requests from different devices (such as mobile and desktop); specific parameter values, such as only querying product query requests containing a specific product ID. This allows for flexible customization of queries to obtain the most accurate front-end and back-end interaction data corresponding to the target business.

[0060] Step S206: Based on the target front-end and back-end interaction data, determine the time corresponding to each interface interaction triggered by the target user within the target time period, wherein the target front-end and back-end interaction data includes multiple interface interactions.

[0061] Specifically, the target front-end and back-end interaction data may include multiple interface interactions. Therefore, after determining the aforementioned target front-end and back-end interaction data, all interface interactions triggered by the target user corresponding to the target user ID within the target time period can be identified from the target front-end and back-end interaction data, as well as the time corresponding to each interface interaction. Optionally, each interface interaction may include: the back-end interface used to implement the interaction, request data, and data returned by the back-end interface in response to the request data.

[0062] Step S208: Execute each interface interaction sequentially according to the time corresponding to each interface interaction to restore the target user's behavior data during the target time period.

[0063] After determining the times corresponding to all interface interactions, each interface interaction can be executed sequentially according to the order of time (i.e., making interface requests and obtaining the backend response data for the interface requests). Based on the results of each interface interaction, the target user's behavior data for the target time period can be reconstructed. This reconstructed behavior data is the behavioral data obtained by reconstructing the target user's interactions with the backend during the target time period. This reconstructed behavior data will be distributed to the business client so that the business can display the corresponding page on the client and perform subsequent anomaly investigation.

[0064] In this embodiment, the method of determining the restored behavior data based on user ID and time period is adopted. This involves obtaining the target user ID and target time period of the target user to be restored; capturing the target front-end and back-end interaction data of the target user within the target time period according to the target user ID and target time period; determining the time corresponding to each interface interaction triggered by the target user within the target time period based on the target front-end and back-end interaction data, where the target front-end and back-end interaction data includes multiple interface interactions; and executing each interface interaction sequentially according to the time corresponding to each interface interaction to restore the restored behavior data of the target user within the target time period. Since the restored behavior data can be obtained by reconstructing the target behavior data based on the target user ID and target time period captured from the target front-end and back-end interaction data, the target user's behavior within the target time period can be automatically determined. This achieves the technical effect of quickly determining the user's behavior within a specific time period, thereby solving the problem in related technologies where it is impossible to quickly restore user behavior, leading to a large and cumbersome workload in the problem analysis process.

[0065] As an optional implementation, the method described above further includes caching the target front-end and back-end interaction data in memory. That is, after obtaining the target front-end and back-end interaction data in step S204, the target front-end and back-end interaction data can be cached in memory.

[0066] Based on the target front-end and back-end interaction data, the time corresponding to each interface interaction triggered by the target user within the target time period is determined. This includes determining the time corresponding to each interface interaction triggered by the target user within the target time period based on the target front-end and back-end interaction data stored in memory. In other words, by caching the target front-end and back-end interaction data in memory using the aforementioned method, the time corresponding to each interface interaction triggered by the target user within the target time period can be directly obtained from the target front-end and back-end interaction data stored in memory. Using the method of this embodiment to determine the time corresponding to each interface interaction can effectively improve processing efficiency.

[0067] like Figure 3 As shown, as an optional implementation, the method described above can be implemented by the following steps: Step S208 is executed sequentially for each interface interaction according to the time corresponding to each interface interaction, thereby restoring the target user's behavior data for the target time period.

[0068] Step S302: Sort all interface interactions according to the time corresponding to each interface interaction to obtain the target user's behavior trajectory path. That is, since each interface interaction has a unique corresponding time, the interface interactions can be sorted by time according to the correspondence between time and interface interaction. Furthermore, the specific meaning of the interface can be displayed by mapping the corresponding interface to Chinese (i.e., the interface information below). The correspondence between the above time and interface information is displayed on the page in list form, and sorted in chronological order, thus forming a visualized behavior trajectory path corresponding to the target user.

[0069] Step S304: Based on the interface information corresponding to each interface interaction in the behavior trajectory path, restore the restored behavior sub-data corresponding to each interface interaction.

[0070] Specifically, after determining the aforementioned behavioral trajectory path, the interface information of each interface interaction (i.e., the interaction node in the behavioral trajectory path) within that path can be used to determine the interactive content that the corresponding interface can execute. Furthermore, by executing the corresponding interaction method, one can interact with the interface. Based on the requests and returned results in the interaction, the reconstructed behavioral sub-data corresponding to that interface interaction can be obtained. Based on this method, the reconstructed behavioral sub-data corresponding to each interface interaction can be obtained.

[0071] Step S306: Based on all the sub-data of the restoration behavior, obtain the restoration behavior data.

[0072] Specifically, after obtaining all the restoration behavior sub-data, the restoration behavior sub-data can be sorted according to the sequential relationship of each interface interaction in the behavior trajectory path to obtain the restoration behavior data.

[0073] As an optional implementation, the interface information corresponding to each interface interaction in the behavior trajectory path in step S304 above can be restored to obtain the restored behavior sub-data corresponding to each interface interaction through the following steps:

[0074] When the interface information type corresponding to the interface interaction is page node data, based on the interface information and the time corresponding to the interface interaction, a response page is requested as the sub-data of the restoration behavior at the time corresponding to the interface interaction. The page node data indicates the state information of each component on the page corresponding to the interface interaction. That is, the type of interface information corresponding to each interface interaction may be different; for example, it could be page node data or a functional interaction. When the interface information type is page node data, the interface interaction adds an entry page function, allowing direct access to the response page after the interface interaction from the current page. Upon entering the response page, a request is made to the backend interface (hereinafter referred to as the interface) corresponding to that response page. When the interface matches the locally cached interface, a response page as the sub-data of the restoration behavior at the time corresponding to the interface interaction is returned, displaying the page UI used by the target user at the time corresponding to the interface interaction (i.e., the UI of the response page). Furthermore, the local cache can be checked to see if there is response data corresponding to the backend interface that matches the current request; if so, this response data is used as the aforementioned response page; otherwise, a request is sent to the backend. It is worth noting that this response page can be data that can be used to render the interaction page on the client side.

[0075] When the type of interface information corresponding to the interface interaction is a functional interaction, the system retrieves the response data that was received after the functional interaction request was made at the time corresponding to the interface interaction, and uses this response data as the sub-data for restoring the behavior. Specifically, when the type of interface information corresponding to the interface interaction is a functional interaction, that is, when the interface interaction is a functional interaction node in the behavior trajectory path, the system will display the response data of the system responding to the request after the functional interaction request was executed at the time corresponding to the interface interaction, and use this response data as the sub-data for restoring the behavior.

[0076] The aforementioned behavior data can help developers understand the specific circumstances when a target user performs a particular function, including request parameters, response status codes, response bodies, etc., which can effectively improve the efficiency of debugging API call issues.

[0077] As an optional implementation, the method described above also includes the following method:

[0078] The system retrieves the specific page with the problem as specified by the target user and creates response data corresponding to the target interface interaction performed by the target user on that page, based on the target front-end and back-end interaction data. Specifically, the target user can indicate the specific page by providing relevant descriptive information about the problematic page (e.g., screenshots, functions). After identifying the designated page, response data corresponding to the target interface interactions performed by the target user on the designated page can be created based on the aforementioned target front-end and back-end interaction data. For example, the behavior trajectory path displays all interface interactions performed by the target user during the target time period. Developers can select an interface interaction from the list and directly enter the page corresponding to that interface interaction after clicking. A request to load the page data can be automatically sent: when entering the page, the system automatically sends a request to load the data required by the page. Here, the system implementing the method of this embodiment automatically intercepts these requests and renders the page based on the target user's response data (i.e., Mock response) provided by the target front-end and back-end interaction data. In this way, all business logic or page navigation operations of the target user at the target time can be reproduced sequentially according to the order of each interface interaction recorded in the behavior trajectory path. The data of each interface interaction can be mocked in chronological order to simulate the environment at that time. Developers can directly go to the designated page where the user reported a problem, and based on the request and response parameters corresponding to the designated page in the target front-end and back-end interaction data, create response data corresponding to the target interface interactions performed by the target user on the designated page for subsequent analysis by the developer.

[0079] The target problem corresponding to the target interface interaction is determined based on the response data. In other words, after obtaining the response data, the target interface interaction can be analyzed to determine the target problem corresponding to that interface interaction.

[0080] As an optional implementation, the steps of determining the target problem corresponding to the target interface interaction based on the response data can be achieved through the following method:

[0081] If a mismatch is found between the request and response data based on the interaction with the target interface, the problem is identified as a page interaction issue. Specifically, if a mismatch is found between the request and response data based on the interaction with the target interface, it indicates that the backend returned an exception. In this case, the problem can be identified as a page interaction issue caused by a backend issue. Therefore, relevant information (such as information about the mismatch between the request and response data) can be directly sent to the relevant backend developers.

[0082] If the request and response data from the target interface interaction indicate a page display anomaly, determine the corresponding problem type. Problem types include: backend data return anomaly and client-side page display incompatibility. Specifically, if it's a page display anomaly, you can directly determine the corresponding problem type, such as: backend data return anomaly or client-side page display incompatibility. Since this problem is caused by frontend development, you can directly report the page display anomaly to the frontend developers for investigation.

[0083] Furthermore, since client-side pages are generally divided into native (iOS or Android) pages and H5 pages, the implementation process for page rendering based on different page types is as follows:

[0084] like Figure 4 The following is the native page rendering implementation process:

[0085] The methods described in the foregoing embodiments can be applied to business network libraries. Clients can configure corresponding interception switches for the baseline network library to intercept the system network library's responses to requests from the business network library, thereby enabling the generation of corresponding display pages based on the target user's front-end and back-end interaction data.

[0086] When a client makes an interface request to the business network library, the business network library makes an interface request to the system network library. The system network library then responds to the business network library's interface request (i.e., ...). Figure 4 After the response is received, it is distributed to the business network library. The interceptor in the business network library replaces the response with the response data obtained by the target user when requesting and interacting with the interface through this interface (i.e., the interface interaction includes this response data, that is...). Figure 4 (Venus data). The response data is then distributed to the client, where it is received, and relevant business framework data transformations and page rendering are performed to obtain the page displayed on the client.

[0087] like Figure 5 The following is the H5 page rendering process:

[0088] The aforementioned method can be applied to a business webview container (a component in a mobile application (such as an Android or iOS application) used to load and display web content). When a client accesses a URL through the business webview container, the container first analyzes whether the switch is enabled. If it determines that the switch is enabled, it sets and overrides the `shouldInternRequest` method under `CommonWebViewClient` (i.e., a generic webview client). This `shouldInternRequest` method is used to intercept and filter all service loading of the webpage (e.g., js, css, png, jpg, etc.). After filtering out the required request interface, it matches the response data corresponding to that request interface, which is stored locally (i.e., the response data is included in the interface interaction). Figure 5 (Venus data), based on this response data, after making sufficient responses, setting network parameters such as request headers, and returning them to the client, thus obtaining the page displayed on the client.

[0089] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0090] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM (Read-Only Memory) / RAM (Random Access Memory), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0091] According to another aspect of the embodiments of this application, a client user behavior restoration apparatus for implementing the above-described client user behavior restoration method is also provided. Figure 6 This is a structural block diagram of an optional client user behavior reconstruction device according to an embodiment of this application, such as... Figure 6 As shown, the device may include:

[0092] Module 61 is used to obtain the target user ID and target time period of the target user whose behavior needs to be restored;

[0093] The crawling module 62 is used to crawl the target user's front-end and back-end interaction data during the target time period according to the target user ID and the target time period;

[0094] The determining module 63 is used to determine, based on the target front-end and back-end interaction data, the time corresponding to each interface interaction triggered by the target user in the target time period, wherein the target front-end and back-end interaction data includes multiple interface interactions;

[0095] The restoration module 64 is used to execute each interface interaction sequentially according to the time corresponding to each interface interaction, and restore the restoration behavior data of the target user in the target time period.

[0096] It should be noted that the acquisition module 61 in this embodiment can be used to perform the above step S202, the capture module 62 in this embodiment can be used to perform the above step S204, the determination module 63 in this embodiment can be used to perform the above step S206, and the restoration module 64 in this embodiment can be used to perform the above step S208.

[0097] In addition to the modules described above, the apparatus in this embodiment may also include modules that execute any method in any of the aforementioned client user behavior restoration methods.

[0098] It should be noted that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of a device, can operate in environments such as... Figure 1 The hardware environment shown can be implemented through software or hardware, and the hardware environment includes the network environment.

[0099] According to another aspect of the embodiments of this application, an electronic device for implementing the above-described client user behavior restoration method is also provided. The electronic device may be a server, a terminal, or a combination thereof.

[0100] According to another embodiment of this application, an electronic device is also provided, comprising: Figure 7 As shown, the electronic device may include: a processor 1501, a communication interface 1502, a memory 1503, and a communication bus 1504, wherein the processor 1501, the communication interface 1502, and the memory 1503 communicate with each other through the communication bus 1504.

[0101] Memory 1503 is used to store computer programs;

[0102] When processor 1501 executes the program stored in memory 1503, it performs the following steps:

[0103] Step S202: Obtain the target user ID and target time period of the target user whose behavior needs to be restored.

[0104] Step S204: Based on the target user ID and the target time period, capture the target user's front-end and back-end interaction data during the target time period.

[0105] Step S206: Based on the target front-end and back-end interaction data, determine the time corresponding to each interface interaction triggered by the target user within the target time period, wherein the target front-end and back-end interaction data includes multiple interface interactions.

[0106] Step S208: Execute each interface interaction sequentially according to the time corresponding to each interface interaction to restore the target user's behavior data during the target time period.

[0107] Optionally, in this embodiment, the communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is used to represent it in the figure, but this does not mean that there is only one bus or one type of bus. The communication interface is used for communication between the aforementioned electronic device and other devices.

[0108] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0109] As an example, the memory 1503 described above may include, but is not limited to, the acquisition module 61, capture module 62, determination module 63, and restoration module 64 from the client user behavior restoration device described above. Furthermore, it may include, but is not limited to, other module units from the client user behavior restoration device described above, which will not be elaborated upon in this example.

[0110] The processors mentioned above can be general-purpose processors, including but not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; they can also be DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0111] This application also provides a computer-readable storage medium, which includes a stored program, wherein the program executes the method steps of the above method embodiments when it runs.

[0112] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, ROMs, RAMs, portable hard drives, magnetic disks, or optical disks.

[0113] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0114] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0115] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0116] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0117] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the solution provided in this embodiment, depending on actual needs.

[0118] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0119] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for reconstructing client-side user behavior, characterized in that, include: Obtain the target user ID and target time period of the target user whose behavior needs to be reconstructed; Based on the target user ID and the target time period, capture the target user's front-end and back-end interaction data during the target time period; Based on the target front-end and back-end interaction data, the time corresponding to each interface interaction triggered by the target user in the target time period is determined, wherein the target front-end and back-end interaction data includes multiple interface interactions; According to the time corresponding to each interface interaction, each interface interaction is executed sequentially to restore the target user's behavior data in the target time period.

2. The method according to claim 1, characterized in that, The step of capturing the target user's front-end and back-end interaction data within the target time period according to the target user ID and the target time period includes: Based on the target user ID and the target time period, filter all candidate interaction data to obtain the original front-end and back-end interaction data within the target time period and corresponding to the target user ID; The target front-end and back-end interaction data that meets the target business conditions is obtained by filtering from the original front-end and back-end interaction data.

3. The method according to claim 2, characterized in that, The method further includes: The target front-end and back-end interaction data is cached in memory; The step of determining the time corresponding to each interface interaction triggered by the target user within the target time period based on the target front-end and back-end interaction data includes: determining the time corresponding to each interface interaction triggered by the target user within the target time period based on the target front-end and back-end interaction data in memory.

4. The method according to claim 1, characterized in that, The step of sequentially executing each interface interaction according to the time corresponding to each interface interaction to reconstruct the target user's behavior data in the target time period includes: Based on the time corresponding to each interface interaction, all interface interactions are sorted to obtain the behavioral trajectory path of the target user; Based on the interface information corresponding to each interface interaction in the behavior trajectory path, the restored behavior sub-data corresponding to each interface interaction is obtained; The restoration behavior data is obtained based on all restoration behavior sub-data.

5. The method according to claim 4, characterized in that, The step of reconstructing the restored behavior sub-data corresponding to each interface interaction according to the interface information corresponding to each interface interaction in the behavior trajectory path includes: When the type of interface information corresponding to the interface interaction is page node data, based on the interface information and the time corresponding to the interface interaction, a request is made to obtain the response page at the time corresponding to the interface interaction, which serves as the sub-data of the restoration behavior. The page node data is used to indicate the status information of each component on the page corresponding to the interface interaction. When the type of interface information corresponding to the interface interaction is a functional interaction, obtain the response data that is responded to after the functional interaction request is made at the time corresponding to the interface interaction, and serves as the sub-data of the restoration behavior.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the specified page with the problem specified by the target user, and create response data corresponding to the target interface interaction performed by the target user on the specified page based on the target front-end and back-end interaction data; Based on the response data, the target question corresponding to the target interface interaction is determined.

7. The method according to claim 6, characterized in that, The step of determining the target question corresponding to the target interface interaction based on the response data includes: If a mismatch is determined between the request data and the response data based on the interaction with the target interface, the target problem is determined to be a page interaction problem; or, If an abnormal page display is determined based on the request and response data of the target interface interaction, the problem type corresponding to the target problem is determined, wherein the problem type includes: abnormal backend data return and incompatibility of client page display.

8. A client-side user behavior reconstruction device, characterized in that, include: The acquisition module is used to obtain the target user ID and target time period of the target user whose behavior needs to be restored; The crawling module is used to crawl the target user's front-end and back-end interaction data during the target time period according to the target user ID and the target time period. The determining module is used to determine, based on the target front-end and back-end interaction data, the time corresponding to each interface interaction triggered by the target user in the target time period, wherein the target front-end and back-end interaction data includes multiple interface interactions; The restoration module is used to execute each interface interaction sequentially according to the time corresponding to each interface interaction, and restore the restoration behavior data of the target user in the target time period.

9. An electronic device comprising a processor, a communication interface, a memory, and a communication bus, wherein, The processor, the communication interface, and the memory communicate with each other via the communication bus, characterized in that... The memory is used to store computer programs; The processor is configured to perform the method of any one of claims 1 to 7 by running the computer program stored in the memory.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the method described in any one of claims 1 to 7 when run on a processor.

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