Method for determining display content of analysis page and method for displaying analysis page

Abstract

The present application relates to a method for determining the display content of an analysis page and a method for displaying an analysis page. The method for determining the display content of an analysis page includes: obtaining record data generated by a target user operating a data processing unit in a data tool, the data processing unit being used to perform access data analysis on a target application corresponding to the target user; clustering the record data to obtain multiple candidate cluster sets; screening a target cluster set from the candidate cluster sets, wherein the cluster center time corresponding to the cluster center of the target cluster set meets a time screening condition, and the cluster center time is associated with the operation time in the record data in the target cluster set; based on a target data processing unit that matches the record data in the target cluster set, determining the content displayed when the target user accesses the analysis page of the data tool for the target application, thereby enabling the user to conveniently use the data tool.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, apparatus, computer device and storage medium for determining display content of an analysis page, and a method, apparatus, computer device and storage medium for displaying an analysis page. Background Art

[0002] The emergence of data tools has greatly facilitated application development by enabling analysis of application access data. Developers can use data tools to view access statistics and understand user activity and usage. However, different developers, or users of data tools, have varying usage habits and focus on different data points.

[0003] Current data tools are primarily implemented through fixed data modules or personalized customization. However, fixed data modules use a unified standard that isn't applicable to different groups of people, while personalized customization requires developers to invest time and effort in configuration. Neither approach offers convenient data tool usage. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment and storage medium for determining the display content of an analysis page, as well as a method, device, computer equipment and storage medium for displaying the analysis page, which can realize convenient use of data tools, in order to address the above technical problems.

[0005] A method for determining display content of an analysis page, the method comprising:

[0006] Acquiring recorded data generated by a target user operating a data processing unit in a data tool, wherein the data processing unit is used to analyze access data of a target application corresponding to the target user;

[0007] Performing clustering processing on the recorded data to obtain multiple candidate cluster sets;

[0008] Filtering a target cluster set from the candidate cluster set, wherein the cluster center time corresponding to the cluster center of the target cluster set meets the time screening condition, and the cluster center time is associated with the operation time in the recorded data in the target cluster set;

[0009] Based on the target data processing unit that matches the record data in the target cluster set, content displayed when the target user accesses the analysis page of the data tool for the target application is determined.

[0010] A device for determining displayed content of an analysis page, the device comprising:

[0011] A record data acquisition module, used to acquire record data generated by a target user operating a data processing unit in a data tool, wherein the data processing unit is used to perform access data analysis on a target application corresponding to the target user;

[0012] A clustering processing module, configured to perform clustering processing on the recorded data to obtain a plurality of candidate cluster sets;

[0013] a target cluster set screening module, configured to screen a target cluster set from the candidate cluster set, wherein the cluster center time corresponding to the cluster center of the target cluster set meets the time screening condition, and the cluster center time is associated with the operation time in the recorded data in the target cluster set;

[0014] The display content determination module is configured to determine, based on a target data processing unit that matches the record data in the target cluster set, the content displayed when the target user accesses the analysis page of the data tool for the target application.

[0015] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0016] Acquiring recorded data generated by a target user operating a data processing unit in a data tool, wherein the data processing unit is used to analyze access data of a target application corresponding to the target user;

[0017] Performing clustering processing on the recorded data to obtain multiple candidate cluster sets;

[0018] Filtering a target cluster set from the candidate cluster set, wherein the cluster center time corresponding to the cluster center of the target cluster set meets the time screening condition, and the cluster center time is associated with the operation time in the recorded data in the target cluster set;

[0019] Based on the target data processing unit that matches the record data in the target cluster set, content displayed when the target user accesses the analysis page of the data tool for the target application is determined.

[0020] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0021] Acquiring recorded data generated by a target user operating a data processing unit in a data tool, wherein the data processing unit is used to analyze access data of a target application corresponding to the target user;

[0022] Performing clustering processing on the recorded data to obtain multiple candidate cluster sets;

[0023] Filtering a target cluster set from the candidate cluster set, wherein the cluster center time corresponding to the cluster center of the target cluster set meets the time screening condition, and the cluster center time is associated with the operation time in the recorded data in the target cluster set;

[0024] Based on the target data processing unit that matches the record data in the target cluster set, content displayed when the target user accesses the analysis page of the data tool for the target application is determined.

[0025] The above-mentioned method, apparatus, computer equipment and storage medium for determining the display content of the analysis page are based on the recorded data generated by the target user's operation on the data processing unit in the data tool. Through clustering processing, the target cluster set whose cluster center time meets the time screening condition is screened out. Based on the recorded data in the target cluster set, the data processing unit corresponding to the access data analysis result that the target user is concerned about can be screened out from the dimension of operation time, thereby obtaining the content displayed when the target user accesses the analysis page of the data tool for the target application. During the entire processing process, there is no need for the user to manually configure the relevant parameters. Based on the target user's operation on the data processing unit in the data tool, personalized display content can be automatically determined on the data tool analysis page for the target user and the target application corresponding to the target user, so as to realize convenient use of the data tool.

[0026] A method for displaying an analysis page, the method comprising:

[0027] In response to a target user's access operation to an analysis page of a data tool, based on a target application selected by the target user, displaying an analysis page corresponding to the target application;

[0028] Based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, the results of the access data analysis of the target application by each target data processing unit are displayed in order on the analysis page;

[0029] Among them, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool.

[0030] A display device for analyzing a page, the device comprising:

[0031] A first display module is configured to, in response to a target user's access operation to the analysis page of the data tool, display an analysis page corresponding to the target application based on the target application selected by the target user;

[0032] a second display module for displaying, on the analysis page, sorted results of access data analysis of the target application by each target data processing unit based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time;

[0033] Among them, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool.

[0034] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0035] In response to a target user's access operation to an analysis page of a data tool, based on a target application selected by the target user, displaying an analysis page corresponding to the target application;

[0036] Based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, the results of the access data analysis of the target application by each target data processing unit are displayed in order on the analysis page;

[0037] Among them, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool.

[0038] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0039] In response to a target user's access operation to an analysis page of a data tool, based on a target application selected by the target user, displaying an analysis page corresponding to the target application;

[0040] Based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, the results of the access data analysis of the target application by each target data processing unit are displayed in order on the analysis page;

[0041] Among them, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool.

[0042] The above-mentioned analysis page display method, apparatus, computer equipment and storage medium, in response to the target user's access operation to the analysis page of the data tool, displays the analysis page corresponding to the target application based on the target application selected by the target user, and based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, sorts and displays the results of the access data analysis of the target application by each target data processing unit on the analysis page. During the entire processing process, the target data processing units obtained by clustering the recorded data of the target user's operation on the data processing units in the data tool are used to display the results of the access data analysis of the target application by each target data processing unit on the analysis page of the data tool for the target user and the target application corresponding to the target user in a sorted manner. The personalized content display on the analysis page of the data tool facilitates the user's convenient use of the data tool. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A diagram illustrating an application environment of a method for determining display content of an analysis page and a method for displaying an analysis page in one embodiment;

[0044] Figure 2 A schematic flow chart of a method for determining display content of an analysis page in one embodiment;

[0045] Figure 3 A schematic diagram of a display page of an analysis page in one embodiment;

[0046] Figure 4 A schematic diagram of a display page of an analysis page in another embodiment;

[0047] Figure 5 A schematic diagram of a display page of an analysis page in different clustering periods in one embodiment;

[0048] Figure 6 Schematic diagram of a flow chart of a method for displaying an analysis page in another embodiment;

[0049] Figure 7 A schematic flow chart of a method for determining display content of an analysis page in one embodiment;

[0050] Figure 8 Schematic diagram of a flow chart of a method for displaying an analysis page in one embodiment;

[0051] Figure 9 A schematic flow chart of a method for determining display content of an analysis page in one embodiment;

[0052] Figure 10 A structural block diagram of an apparatus for analyzing displayed content of a page and determining the same in one embodiment;

[0053] Figure 11 is a structural block diagram of a display device for analyzing pages in one embodiment;

[0054] Figure 12 is a diagram of the internal structure of a computer device in one embodiment;

[0055] Figure 13 FIG. 4 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0057] The method for determining the display content of the analysis page and the method for displaying the analysis page provided in this application can be applied to Figure 1In the application environment shown. The terminal 110 communicates with the server 120 via a network. A data tool is installed on the terminal 110, and the data processing unit in the data tool is used to analyze the access data of the target application corresponding to the target user, and report the record data generated by the target user operating the data processing unit in the data tool to the server 120. The server 110 obtains the record data generated by the target user operating the data processing unit in the data tool, clusters the record data, and obtains multiple candidate cluster sets; the server 120 filters out the target cluster set from the candidate cluster set, and the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition, and the cluster center time is associated with the operation time in the record data in the target cluster set; the server 120 determines the content displayed when the target user accesses the analysis page of the data tool for the target application based on the target data processing unit that matches the record data in the target cluster set, and sends the information corresponding to the determined display content to the terminal 110. The displayed content is the access data analysis result corresponding to the target data processing unit.

[0058] In response to the target user's access operation to the analysis page of the data tool, the terminal 110 displays the analysis page corresponding to the target application based on the target application selected by the target user; based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, the terminal 110 sorts and displays the results of the access data analysis of the target application by each target data processing unit in the analysis page.

[0059] The terminal 110 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, portable wearable devices or vehicle-mounted terminals, and the server 120 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0060] In one embodiment, Figure 2 As shown, a method for determining the display content of an analysis page is provided, and the method is applied to Figure 1 The following steps are used as an example to illustrate the server in the example:

[0061] Step 202 : obtaining record data generated by the target user operating a data processing unit in the data tool, where the data processing unit is used to perform access data analysis on the target application corresponding to the target user.

[0062] Among them, the target user is an object of use of the data tool. Specifically, when a user is the administrator or operator of at least one application, and the application can access data analysis through the data tool, the user can be used as the target user, and the application can be used as the target application. The target user can access the data tool to view the access data analysis results of the corresponding target application. The number of applications managed or operated by the target user can be one, two or more. Before accessing the data tool, the target user can select the applications he manages or operates so that the number of target applications corresponding to each access to the data tool is 1. Figure 3 As shown, the user information of the target user, such as the user avatar, can be displayed in the data tool, and the target application, such as the mini program "Zhang San Shop" managed or operated by the target user, can also be displayed.

[0063] The data tool is a tool used to analyze access data of the target application. The data tool can be an application installed on the terminal, or it can be a sub-application running in the operating environment of the parent application, for example, a mini-program in social software such as WeChat. Multiple data processing units are configured in the data tool. The data processing unit is a functional unit with the function of data analysis and displaying analysis results. The multiple data processing units in the data tool are used to analyze access data of the target application from different data dimensions, and display the corresponding access data analysis results on the display page of the data tool. On the display page of the data tool, the access data analysis results for the target application are displayed according to modules, and one data processing unit corresponds to one data display module. For example, the data processing unit includes a source analysis unit, a behavior comparison unit, a retained data unit, and a portrait statistics unit. Accordingly, the data of each unit is displayed separately through data display modules such as the source analysis module, the behavior comparison module, the retained data module, and the portrait statistics module.

[0064] An operation on a data processing unit is a trigger action performed by a target user when accessing a data tool. This can be a click or exposure operation. A click operation allows you to view the details of a particular data item within the access data analysis results within a data processing unit, while an exposure operation triggers the display of the access data analysis results within the data processing unit.

[0065] Log data is used to record the operations performed by target users on data processing units within a data tool. Log data can be multidimensional, specifically including the data processing unit, operation time, and user. The dimensionality of log data can be adjusted based on actual clustering needs, for example, by adding operation types and sub-units. The more dimensionality of log data, the more comprehensive the corresponding dimensions of the clustering results.

[0066] Specifically, in response to an operation performed by a target user on a data processing unit in a data tool, the data tool generates recorded data and reports the recorded data to a server.

[0067] Step 204: Perform clustering on the recorded data to obtain multiple candidate clustering sets.

[0068] Clustering is the process of dividing a set of objects into multiple classes composed of similar objects. The clustering sets (clusters) generated by clustering are a set of recorded data, and the recorded data within the same clustering set are similar to each other and different from the recorded data in other clustering sets.

[0069] Specifically, the recorded data for clustering can be the recorded data corresponding to the same target user. Based on the recorded data reported by the data tool and the operating user in the recorded data, the server filters out the recorded data corresponding to the same target user and performs clustering on the filtered recorded data to obtain multiple candidate clustering sets. Among them, the number of candidate clustering sets can be preset or randomly generated, and can be specifically adjusted adaptively according to the clustering algorithm used. The clustering algorithm can specifically be the K-means algorithm (distance-based clustering algorithm), the K-medoids algorithm (clustering method based on "representative objects"), the clarans algorithm (large-scale application clustering algorithm based on random search), etc.

[0070] The clustering process includes: Given a data set with N data records, the splitting method constructs K groups, and each group represents a clustering set, where K < N. The K groups satisfy the following conditions: (1) Each group contains at least one data record; (2) Each data record belongs to and only belongs to one group; For the given number of clustering sets K, the algorithm first gives an initial grouping method, and then changes the grouping through repeated iteration, so that compared with the previous grouping, the data records in the same group have higher similarity, while the data records in different groups have lower similarity.

[0071] Step 206: Screen out the target clustering set from the candidate clustering sets. The clustering center time corresponding to the clustering center of the target clustering set meets the time screening condition, and the clustering center time is associated with the operation time in the recorded data of the target clustering set.

[0072] Among them, the clustering center is a special sample in the clustering set obtained by clustering analysis. The clustering center is used to represent a certain clustering set, and other samples determine whether they belong to this clustering set by calculating the distance from it. The clustering center can be the center point data obtained based on each recorded data in the clustering set, so that the sum of the distances from each recorded data in the clustering set to this center point data is minimized.

[0073] For each candidate cluster set, there is a corresponding cluster center, and each cluster center has data of the same dimension as the recorded data. The cluster center time refers to the data of the dimension of the operation time of the cluster center. For example, when the recorded data used for clustering only contain data of the two dimensions of data processing unit and operation time, the clustering process is based on the two dimensions of data processing unit and operation time. Therefore, the data of the cluster center also contains data of the two dimensions of data processing unit and operation time. When the recorded data used for clustering contain data of extended dimensions such as data processing unit, operation time and operation type, the clustering process is multi-dimensional clustering based on the extended dimensions such as data processing unit, operation time and operation type. Therefore, the data corresponding to the obtained cluster center also contains data of extended dimensions such as data processing unit, operation time and operation type.

[0074] When selecting candidate cluster centers, the selection is based on the cluster center time corresponding to the cluster center. The cluster center time can represent the overall operation time of the entire candidate cluster set. The smaller the time interval between the cluster center time and the current time, the more likely the recorded data in the cluster set is the target user's recent focus.

[0075] Specifically, the time screening condition can be the cluster center time with the shortest time interval from the current time. After obtaining the cluster center of each candidate cluster set, the server extracts the cluster center time corresponding to the cluster center, filters out the target cluster center time with the shortest time interval from the current time from each cluster center time, and determines the candidate cluster set corresponding to the target cluster center time as the target cluster set.

[0076] Step 208 : Determine, based on the target data processing unit that matches the record data in the target cluster set, the content displayed when the target user accesses the analysis page of the data tool for the target application.

[0077] The records in the target cluster set are a subset of all the records participating in the clustering process. Filtering the target cluster set is actually filtering the records. Since the records are generated by the target user's operations on the data processing unit, each record has a matching data processing unit, which is the target data processing unit.

[0078] Specifically, the server determines the target data processing unit that matches the recorded data in the target cluster set. The server then uses the results of the target data processing unit's access data analysis of the target application to determine the content displayed when the target user accesses the data tool's analysis page for the target application.

[0079] The analysis page is a display page within a data tool, used to present key data to target users. Specifically, the analysis page can be the homepage (overview page) of a data tool. The homepage is the first page displayed after opening the data tool, allowing users to quickly access key data.

[0080] The content displayed on the analysis page corresponds to both the target user and the target application. That is, when the target user changes or the target application changes, the content displayed on the analysis page of the data tool will also change accordingly, thereby achieving personalized content display on the analysis page.

[0081] The above-mentioned method for determining the display content of the analysis page is based on the recorded data generated by the target user's operation on the data processing unit in the data tool. Through clustering processing, the target cluster set whose cluster center time meets the time screening condition is screened out. Based on the recorded data in the target cluster set, the data processing unit corresponding to the access data analysis result that the target user is concerned about can be screened out from the dimension of operation time, thereby obtaining the content displayed when the target user accesses the analysis page of the data tool for the target application. During the entire processing process, there is no need for the user to manually configure relevant parameters. Based on the target user's operation on the data processing unit in the data tool, personalized display content can be automatically determined on the data tool analysis page for the target user and the target application corresponding to the target user, thereby realizing convenient use of the data tool.

[0082] In one embodiment, the number of the target data processing unit is 1, and the access data analysis result corresponding to the target data processing unit is directly displayed on the analysis page.

[0083] In one embodiment, the number of target data processing units is no less than two; the displayed content is the access data analysis results corresponding to the target data processing units. The method for determining the display content of the analysis page further includes: obtaining the operation time from the recorded data matched by each target data processing unit; and determining the sorting and display position of the access data analysis results on the analysis page according to the time interval between the operation time and the current time.

[0084] Among them, the operation time is the time when the target user recorded in the recorded data operates the target data processing unit. It can be a specific time point (such as 08:30:05 on January 1, 2021) or the time period in which the specific time point is located (such as January 1, 2021). The time interval between the operation time and the current time can be calculated according to the specific time point, or it can be calculated according to the set time unit. If it is less than a time unit, it can be calculated as a time unit. For example, the calculation is performed in units of "days" to determine the difference in days between the operation time and the current time. For another example, the calculation is performed in units of "hours" to determine the difference in hours between the operation time and the current time.

[0085] The recorded data matching the target data processing unit includes the operation time. The length of the time interval between the operation time and the current time determines the ranking and display position of the access data analysis results on the analysis page. The length of the time interval can indicate the target user's level of interest in the access data analysis results of the target data processing unit. Specifically, the shorter the time interval, the higher the ranking and display position of the access data analysis results corresponding to the target data processing unit on the analysis page; the longer the time interval, the lower the ranking and display position of the access data analysis results corresponding to the target data processing unit on the analysis page.

[0086] In this embodiment, the sorting and display position of the access data analysis results of the target data processing unit on the analysis page is determined by the time interval between the operation time and the current time. The display content can be sorted based on the target user's interest in the access data analysis results of the target data processing unit, which conforms to the user's usage habits and enables the user to quickly and conveniently obtain the access data analysis results of the target data processing unit of interest.

[0087] In one embodiment, the operation time is an operation time period, and the recorded data also includes the number of operations on the same data processing unit within the operation time period. Determining the sorting and display position of the access data analysis results on the analysis page based on the time interval between the operation time and the current time includes: determining the time interval between the operation time period and the current time period based on the operation time period in the recorded data matched by the target data processing unit; when there are at least two target recorded data with the same time interval, respectively obtaining the number of operations in each target recorded data; and determining the sorting and display position of the access data analysis results on the analysis page based on the time interval and the number of operations.

[0088] The "operation time period" refers to the time interval during which the target user operates the data processing unit. The time interval can be divided into equally spaced intervals according to a preset time unit, such as by day or hour. Recording data according to the operation time period is actually the process of converting the initial recorded data containing the operation time points according to the operation time period.

[0089] The time interval between the operating time period and the current time period is calculated based on the same relative time point in the operating time period and the current time period. For example, the comparison can be based on the start point of the time period or the end point of the time period.

[0090] Record data includes the number of operations performed on the same data processing unit within an operation time period. Therefore, different data processing units correspond to different data records. When at least two target records exist with the same time interval, this indicates that the target user performed operations on at least two data processing units within the same operation time period. The server obtains the number of operations from each target record and sorts the target records with at least two identical time intervals based on the number of operations.

[0091] Specifically, the server determines the sorting and display position of the access data analysis results on the analysis page based on the two data dimensions of time interval and number of operations, in an arbitrary order. For example, the server may first sort the data records in the target cluster set based on time interval, and then sort them again based on number of operations; the server may also first sort based on number of operations, and then sort them again based on time interval; the server determines the sorting and display position of the access data analysis results on the analysis page based on the results of the two sorting operations on the data records in the target cluster set.

[0092] In this embodiment, the time interval and the number of operations are taken into consideration to indicate the target user's interest in the access data analysis results corresponding to the data processing unit, and then the sorting and display position of the access data analysis results on the analysis page is determined. This can achieve reasonable sorting of the access data analysis results corresponding to the target data processing unit, so that the user can quickly and conveniently obtain the access data analysis results of the target data processing unit of interest.

[0093] In one embodiment, based on the time interval and the number of operations, the sorting and displaying position of the access data analysis results on the analysis page is determined, including: based on the time interval, performing a primary sorting on the record data, wherein the record data with the same time interval have the same sorting order; based on the number of operations, performing a secondary sorting on the record data with the same sorting order; based on the results of the primary sorting and the secondary sorting, determining the sorting and displaying position of the access data analysis results on the analysis page.

[0094] Specifically, the server first performs an initial sorting of the record data in the target cluster set based on the time interval between the operation time period and the current time period. When there are at least two target record data with the same time interval in the result of the initial sorting, the target record data is secondary sorted based on the number of operations in the target record data. Through the initial sorting and secondary sorting, each record data in the target cluster set is sorted, and then based on the target data processing units that match the sorted record data, the sorting display position of the access data analysis results corresponding to the target data processing unit on the analysis page is determined.

[0095] In this embodiment, considering the impact of interval time and number of operations on user attention, the recorded data is first sorted based on the interval time. If no records with the same interval time exist in the sorted results, the recorded data is sorted directly based on the interval time. If at least two target records with the same interval time exist in the sorted results, the target records are then re-sorted based on the number of operations in the target records. This ensures the accuracy of the sorting results and, if no records with the same interval time exist in the sorted results, eliminates the need to obtain the data required for the re-sort, thus saving resources required for data processing.

[0096] In one embodiment, obtaining recorded data generated by a target user operating a data processing unit in a data tool includes: obtaining initial recorded data of the target user operating the data processing unit in the data tool; converting multiple initial recorded data with different operation time points into recorded data corresponding to the operation time period according to the operation time period to which the operation time point belongs, and the number of operations in the recorded data is the number of converted initial recorded data.

[0097] Initial recorded data refers to the raw data directly generated by the data tool based on the target user's operations on the data processing unit. This raw data record contains comprehensive and detailed data on every operation performed by the target user. Converting this initial recorded data involves converting multiple pieces of initial recorded data that differ only in the time of the operations, but that fall within the same time period, into a single piece of recorded data. The operation time in the converted recorded data can be directly represented by the time interval between the operation period and the current time period.

[0098] Furthermore, the server adds the number of initial recorded data as the number of operations to the corresponding recorded data based on the number of initial recorded data corresponding to the recorded data corresponding to the operation time period.

[0099] Specifically, the server receives the initial record data reported by the data tool, and pre-processes the initial record data to obtain record data that can be used for clustering processing. If the initial record data includes data of three dimensions: operating user, operation time point, and data processing unit, the server determines the operation time period to which the operation time point in the initial record data belongs based on the initial record data corresponding to the same operating user, and converts the initial record data belonging to the same operation time period into one piece of data according to the same data processing unit. The converted record data includes the operating user, data processing unit, operation time period, and number of operations, wherein the number of operations is the number of pieces of the corresponding converted initial record data. If the initial record data includes data of four dimensions: operating user, operation time point, data processing unit, and operation type, the converted record data includes the operating user, data processing unit, operation type, operation time period, and number of operations. Among them, the operation time period can be converted into the time interval corresponding to the operation time period and the current time period, that is, expressed as the number of days from the most recent day of use. In a specific application, the initial record data is shown in Table 1; the record data obtained after conversion is shown in Table 2. Among them, the "interval days" in Table 2 represents the difference between the day when the user last used the data processing unit or the subunit and today. The larger the value, the longer the user has not used the data processing unit or the subunit.

[0100] Table 1: Initial Recording Data

[0101]

[0102] Table 2: Converted record data

[0103]

[0104] In this embodiment, by converting the initial record data, a large amount of initial record data can be simplified based on time periods, and by adding data in the dimension of the number of operations to retain information in the dimension of the total amount of data before the conversion statistics, data simplification is achieved while retaining sufficient information data. Moreover, compared with the method of directly clustering the initial record data, the record data obtained through the conversion processing, by adding a data dimension, achieves the unification of data in the time dimension with many variables according to time periods, which is conducive to obtaining more accurate and reliable clustering results in the clustering process, thereby improving the accuracy of the target data processing unit of interest to the user.

[0105] In one embodiment, the recorded data also includes the sub-unit identifier corresponding to the sub-unit operated by the target user in the data processing unit; the method for determining the display content of the analysis page also includes: determining the candidate data processing unit that matches the sub-unit identifier to be matched based on the sub-unit identifier to be matched contained in each of the recorded data of the target cluster set; and performing deduplication processing on the candidate data processing units to obtain the target data processing unit.

[0106] The data processing unit includes one or more subunits, each of which is capable of independently analyzing access data from the target application. A target user's operations on the data processing unit are operations on one of its subunits. When the data tool records data related to the target user's operations, it can also record the subunit corresponding to each operation and the data processing unit to which the subunit belongs.

[0107] Similarly, based on the principle of converting the initial recorded data into a single piece of data, where multiple pieces of initial recorded data differ only in the time points of the operations, and the different time points of the operations belong to the same operation time period, if the recorded data is converted data including the operation time period and the number of operations, the converted recorded data is converted for the same sub-unit identifier, that is, operations performed on different sub-units under the same data processing unit should be converted into different recorded data.

[0108] The subunit identifier is a subunit identifier in the record data in the target cluster set. The data processing units matched based on the record data containing the subunit identifier may be duplicated. Therefore, the server determines candidate data processing units that match the subunit identifier based on the subunit identifiers to be matched contained in each record data of the target cluster set. The server then performs deduplication processing on the candidate data processing units to obtain the target data processing unit. Deduplication processing refers to the data processing process of removing duplicate candidate data processing units to ensure that the same data processing unit appears only once.

[0109] In this embodiment, by recording the sub-unit identifier corresponding to the sub-unit operated by the target user in the data processing unit in the recorded data, clustering processing can be performed based on more refined dimensions to obtain more accurate clustering results, thereby improving the accuracy of the target data processing unit that the user is interested in.

[0110] In one embodiment, the method for determining the display content of the analysis page also includes: determining the target subunit in each target data processing unit based on the subunit corresponding to the subunit identifier to be matched, and the time interval between the operation time in the recorded data corresponding to the target subunit and the current time meets the time interval screening condition; based on the interval time corresponding to each target subunit, determining the display area of ​​the analysis page for the access data analysis result corresponding to the target data processing unit where the target subunit is located; for each target data processing unit, based on the time interval corresponding to each subunit in the corresponding target data processing unit, determining the display position of the access data analysis result corresponding to each subunit in the display area corresponding to the corresponding target data processing unit.

[0111] The time interval screening condition may be the shortest time interval. The target subunit is one of the subunits corresponding to the to-be-matched subunit identifier contained in each record data of the target cluster set. The time interval between the operation time in the record data corresponding to the target subunit and the current time is the shortest. Each target data processing unit has one and only one target subunit.

[0112] The server determines the display area of ​​the analysis page for the access data analysis results corresponding to each target data processing unit based on the time interval between the operation time in the recorded data corresponding to each target sub-unit and the current time. The shorter the time interval, the closer the access data analysis results corresponding to the target data processing unit are to the front of the display area on the analysis page; the longer the time interval, the closer the access data analysis results corresponding to the target data processing unit are to the back of the display area on the analysis page.

[0113] Each target data processing unit may include two or more sub-units. For each target data processing unit, the server determines the display position of the access data analysis results corresponding to each sub-unit in the display area corresponding to the corresponding target data processing unit based on the time interval corresponding to each sub-unit in the corresponding target data processing unit. Figure 3 As shown, the sub-units of the data processing unit corresponding to "Yesterday's data" may include the number of visitors, the number of new visitors, the total number of visitors, the number of new user retention, the number of newly added users, etc. Generally speaking, on the homepage of the data tool, if the display content determined based on the recorded data is not obtained, the default content will be displayed, such as the access data analysis results of the data processing units corresponding to "Yesterday's data" and "Real-time number of visitors". Figure 4As shown, if the display content determined based on the recorded data is obtained, such as the "focus on new user indicators", it can be displayed in sorting on the homepage of the data tool according to the data processing unit corresponding to the focus on new user indicators and the sub-units in the data processing unit. For example, the "yesterday's data" and "new user TOP5 visit sources" are displayed in sorting. In the display area corresponding to the "yesterday's data", the "number of visitors", "number of new visitors", "new user retention" and "number of new additions" are displayed in sorting.

[0114] Furthermore, among the sub-units in the target data processing unit, the target user may have only operated on some of the sub-units, and corresponding record data may exist. In this case, the server will prioritize the access data analysis results corresponding to the sub-units with record data and display them at the top of the display area corresponding to the corresponding target data processing unit. Then, the server will display the access data analysis results corresponding to the sub-units for which the target user has not performed corresponding operations in the corresponding display area. The access data analysis results corresponding to the sub-units for which the target user has not performed corresponding operations may be displayed in a default order or a historical order.

[0115] In this embodiment, by determining the display position of the access data analysis results corresponding to the target data processing unit in the display area of ​​the analysis page and the access data analysis results corresponding to each sub-unit in the display area corresponding to the corresponding target data processing unit, it is possible to reasonably sort the access data analysis results corresponding to the target data processing unit and its sub-units, so that users can quickly and conveniently obtain the access data analysis results of the target data processing unit and its sub-units of interest.

[0116] In one embodiment, the recorded data is multi-dimensional data; clustering is performed on the recorded data to obtain multiple candidate cluster sets, including: performing multi-dimensional K-means clustering based on the multi-dimensional data to obtain multiple candidate cluster sets.

[0117] K-means clustering is a clustering process based on the K-means algorithm. Multidimensional K-means clustering is a process of clustering data based on multiple dimensions. The basic idea of ​​the multidimensional K-means algorithm is to initially randomly assign K cluster centers and assign the sample points to be classified to each cluster according to the nearest neighbor principle. Then, based on the data of each dimension, the centroid of each cluster is recalculated using the averaging method (the centroid may not be a sample point) to determine the new cluster. The algorithm continues iterating until the moving distance of the cluster center is less than a given value or the number of iterations is reached.

[0118] In this embodiment, multidimensional K-means clustering processing is performed through an unsupervised K-means algorithm to obtain multiple candidate cluster sets, which has the characteristics of fast convergence speed and better clustering effect, and the main parameter that needs to be adjusted is only the number of clusters k, and the parameter setting is simple.

[0119] In one embodiment, the method for determining the display content of the analysis page also includes: for each clustering cycle, obtaining the recorded data generated by the target user operating the data processing unit in the data tool; clustering the recorded data to obtain multiple candidate cluster sets, including: clustering the recorded data within the clustering cycle according to the clustering cycle to obtain multiple candidate cluster sets.

[0120] The clustering cycle is the time for redetermining the content displayed when a target user accesses the analysis page of the data tool for the target application.

[0121] Specifically, the data tool can report the recorded data to the server regularly according to the clustering cycle, so that the server can perform corresponding processing based on the reported recorded data and determine the time when the target user accesses the analysis page of the data tool for the target application in the next clustering cycle. The data tool can also report the recorded data to the server in real time or regularly, and the server can perform corresponding processing on the reported recorded data regularly according to the clustering cycle and determine the time when the target user accesses the analysis page of the data tool for the target application in the next clustering cycle. Figure 5 As shown, by regularly updating according to the clustering cycle, it can be found that the key data that users pay attention to in the early stage is "sharing and source", and the key data that users pay attention to in the later stage is "user retention".

[0122] In this embodiment, by regularly updating the time of the content displayed when the target user accesses the analysis page of the data tool for the target application according to the clustering cycle, it can meet the user's adjustment of the key focus data of the target application at different times. For the same target application, personalized display content can be achieved at different times, so as to enable the target user to use the data tool conveniently.

[0123] In one embodiment, Figure 6 As shown, a method for displaying an analysis page is provided, which is applied to Figure 1 The following steps are used as an example to illustrate the terminal:

[0124] Step 602 : In response to the target user's access operation to the analysis page of the data tool, based on the target application selected by the target user, displaying the analysis page corresponding to the target application.

[0125] The target user is a user of the data tool. Specifically, when a user is the administrator or operator of at least one application, and the application can access data analysis through the data tool, the user can be the target user, and the application can be the target application. The target user can access the data tool to view the access data analysis results of the corresponding target application. The number of target applications managed or operated by the target user can be one, two, or more. Before accessing the data tool, the target user can select the target application to manage or operate so that the number of target applications corresponding to each access to the data tool is one.

[0126] The data tool is a tool used to analyze access data of the target application. The data tool can be an application installed on the terminal, or it can be a sub-application running in the operating environment of the parent application, for example, a mini-program in social software such as WeChat. Multiple data processing units are configured in the data tool. The data processing unit is a functional unit with the functions of data analysis and analysis result display. The multiple data processing units in the data tool are used to analyze access data of the target application from different data dimensions, and display the corresponding access data analysis results on the display page of the data tool. On the display page of the data tool, the access data analysis results for the target application are displayed according to modules, and one data processing unit corresponds to one data display module.

[0127] The analysis page is a display page within a data tool, used to present key data to target users. Specifically, the analysis page can be the homepage (overview page) of a data tool. The homepage is the first page displayed after opening the data tool, allowing users to quickly access key data.

[0128] The content displayed on the analysis page is tailored to the target user and target application. This means that when the target user or target application changes, the content displayed on the data tool's analysis page will also change accordingly, allowing for personalized content display on the analysis page.

[0129] Step 604, based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, the results of the access data analysis of the target application by each target data processing unit are sorted and displayed in the analysis page; wherein, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool.

[0130] The record data that matches the target data processing unit records the operation time, and the sorting and display position of the access data analysis results on the analysis page is determined based on the length of the time interval between the operation time and the current time. The length of the time interval can characterize the target user's interest in the access data analysis results of the target data processing unit. Specifically, the shorter the time interval, the higher the sorting and display position of the access data analysis results of the corresponding target data processing unit on the analysis page; the longer the time interval, the higher the sorting and display position of the access data analysis results of the corresponding target data processing unit on the analysis page. By sorting and displaying the access data analysis results of the target data processing unit on the analysis page based on the time interval between the operation time and the current time, the access data analysis results of the target data processing unit can be sorted and displayed based on the target user's interest in the access data analysis results of the target data processing unit, which conforms to the user's usage habits and enables the user to quickly and conveniently obtain the access data analysis results of the target data processing unit of interest.

[0131] Log data is used to record the operations performed by the target user on the data processing unit in the data tool. Clustering is the process of dividing a collection of objects into multiple clusters composed of similar objects. The cluster set generated by clustering is a collection of log data that is similar to log data in the same cluster set and different from log data in other cluster sets. The data tool reports the log data to the server. The server filters the log data corresponding to the same target user based on the operating user in the log data and clusters the filtered log data to obtain multiple candidate cluster sets. The cluster center can be the center point data obtained based on the center point data of each log data in the cluster set, so as to minimize the sum of the distances from each log data in the cluster set to the center point data. When selecting candidate cluster centers, the selection is based on the cluster center time corresponding to the cluster center, which can represent the overall operation time of the entire candidate cluster set. The smaller the time interval between the cluster center time and the current time, the more likely the log data in the cluster set has been the target user's recent focus. The time filtering condition can be the cluster center time with the shortest time interval from the current time. After obtaining the cluster center of each candidate cluster set, the server extracts the cluster center time corresponding to the cluster center, filters out the target cluster center time with the shortest time interval from the current time from each cluster center time, and determines the candidate cluster set corresponding to the target cluster center time as the target cluster set.

[0132] The above-mentioned method for displaying the analysis page, in response to the target user's access operation to the analysis page of the data tool, displays the analysis page corresponding to the target application based on the target application selected by the target user, and based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, sorts and displays the results of the access data analysis of the target application by each target data processing unit on the analysis page. During the entire processing process, the target data processing units obtained by clustering the recorded data of the target user's operation on the data processing units in the data tool are used to display the results of the access data analysis of the target application by each target data processing unit on the analysis page of the data tool for the target user and the target application corresponding to the target user in a sorted manner. The personalized content display on the analysis page of the data tool facilitates the user's convenient use of the data tool.

[0133] In one embodiment, based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time, the analysis page displays the results of the access data analysis of the target application by each target data processing unit in a sorted manner, including:

[0134] Based on the time interval between the operation time in the recorded data corresponding to the target sub-unit in each target data processing unit and the current time, on the analysis page, the access data analysis results corresponding to each target data processing unit are sorted and displayed in the display area of ​​the analysis page; for each target data processing unit, based on the time interval between the operation time corresponding to each sub-unit in the corresponding target data processing unit and the current time, the access data analysis results corresponding to each sub-unit are sorted and displayed in the display area corresponding to the corresponding target data processing unit; wherein, the time interval between the operation time in the recorded data corresponding to the target sub-unit and the current time meets the time interval filtering condition.

[0135] The time interval filtering condition can be the shortest time interval. The target subunit is one of the subunits corresponding to the to-be-matched subunit identifier contained in each record data of the target cluster set. The time interval between the operation time in the record data corresponding to the target subunit and the current time is the shortest. Each target data processing unit has one and only one target subunit.

[0136] The server determines the display area of ​​the analysis page for the access data analysis results corresponding to each target data processing unit based on the time interval between the operation time in the recorded data corresponding to each target sub-unit and the current time. The shorter the time interval, the closer the access data analysis results corresponding to the target data processing unit are to the front of the display area on the analysis page; the longer the time interval, the closer the access data analysis results corresponding to the target data processing unit are to the back of the display area on the analysis page.

[0137] Since each target data processing unit may include two or more sub-units, the server determines the display position of the access data analysis results corresponding to each sub-unit in the display area corresponding to the corresponding target data processing unit for each target data processing unit based on the time interval corresponding to each sub-unit in the corresponding target data processing unit.

[0138] Furthermore, among the sub-units in the target data processing unit, the target user may have only operated on some of the sub-units, and corresponding record data may exist. In this case, the server will prioritize the access data analysis results corresponding to the sub-units with record data and display them at the top of the display area corresponding to the corresponding target data processing unit. Then, the server will display the access data analysis results corresponding to the sub-units for which the target user has not performed corresponding operations in the corresponding display area. The access data analysis results corresponding to the sub-units for which the target user has not performed corresponding operations may be displayed in a default order or a historical order.

[0139] In this embodiment, by sorting and displaying the access data analysis results corresponding to the target data processing unit in the display area of ​​the analysis page, and sorting and displaying the access data analysis results corresponding to each sub-unit in the display area corresponding to the corresponding target data processing unit, it is possible to achieve a reasonable sorting and display of the access data analysis results corresponding to the target data processing unit and its sub-units, so that users can quickly and conveniently obtain the access data analysis results of the target data processing unit and its sub-units of interest.

[0140] In one embodiment, Figure 7 As shown, a method for determining the display content of an analysis page is provided, comprising the following steps:

[0141] Step 702 : obtaining initial record data of the target user's operations on the sub-units of the data processing unit in the data tool during the clustering period; the sub-units of the data processing unit are used to perform access data analysis on the target application corresponding to the target user.

[0142] Step 704 , converting multiple initial record data with different operation time points into record data corresponding to the operation time period according to the operation time period to which the operation time points belong, and the number of operations in the record data is the number of converted initial record data.

[0143] Step 706 : Perform multi-dimensional K-means clustering on the recorded data according to the clustering period to obtain multiple candidate cluster sets.

[0144] Step 708: Filter out a target cluster set from the candidate cluster sets. The cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition. The cluster center time is associated with the operation time in the recorded data in the target cluster set.

[0145] Step 710 : Based on the to-be-matched sub-unit identifiers contained in each of the record data of the target cluster set, determine a candidate data processing unit that matches the to-be-matched sub-unit identifiers.

[0146] Step 712: De-duplication the candidate data processing units to obtain the target data processing unit.

[0147] Step 714: Determine the target subunit in each target data processing unit based on the subunit corresponding to the to-be-matched subunit identifier, and whether the time interval between the operation time in the recorded data corresponding to the target subunit and the current time meets the time interval screening condition.

[0148] Step 716 : performing initial sorting on the target subunits based on the time interval between the operation time period and the current time period in the recorded data corresponding to the target subunits, wherein the sorting order of the target subunits with the same time interval is the same.

[0149] Step 718: When there are at least two target sub-units with the same time interval, obtain the number of operations in the recorded data corresponding to each target sub-unit.

[0150] Step 720 : performing secondary sorting on the target sub-units with the same sorting order based on the number of operations.

[0151] Step 722: Based on the results of the primary sorting and the secondary sorting, determine the display area of ​​the analysis page for the access data analysis result corresponding to the target data processing unit where the target sub-unit is located.

[0152] Step 724 : For each target data processing unit, based on the time intervals corresponding to the subunits in the corresponding target data processing unit, determine the display position of the access data analysis results corresponding to each subunit in the display area corresponding to the corresponding target data processing unit.

[0153] In one embodiment, Figure 8 As shown, a method for displaying an analysis page is provided, comprising the following steps:

[0154] Step 802 : In response to the target user's access operation to the analysis page of the data tool, based on the target application selected by the target user, displaying the analysis page corresponding to the target application.

[0155] Step 804, based on the time interval between the operation time in the recorded data corresponding to the target sub-unit in each target data processing unit and the current time, on the analysis page, sort and display the access data analysis results corresponding to each target data processing unit in the display area of ​​the analysis page.

[0156] Step 806, for each target data processing unit, based on the time interval between the operation time corresponding to each sub-unit in the corresponding target data processing unit and the current time, sort and display the access data analysis results corresponding to each sub-unit in the display area corresponding to the corresponding target data processing unit.

[0157] Among them, the time interval between the operation time in the recorded data corresponding to the target sub-unit and the current time meets the time interval filtering condition; the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool.

[0158] The present application also provides an application scenario, which applies the above-mentioned method for determining the display content of an analysis page and the method for displaying an analysis page. Specifically, the application of the method for determining the display content of an analysis page and the method for displaying an analysis page in this application scenario is as follows:

[0159] Taking the development and management of mini programs as an example, after developers develop a mini program, they need to use data indicators to check the activity and usage of the mini program. By checking the active data indicators, they can determine the effectiveness of the mini program in increasing the number of active users and improving user stickiness after operating the mini program activities. They can also optimize the mini program opening speed by checking the mini program opening time in the user usage time distribution data. Current data tools mainly use fixed data indicators or personalized active customization. These methods either have unified standards and cannot be tailored to each user, or require merchants to spend manpower and time to configure them themselves. Because developers will focus on different data indicators when using the tools, some data indicators developers will look at more frequently and for longer periods of time. This application records these behaviors of developers and combines them with clustering algorithms to select the data indicators that developers care about most to form the daily report on the homepage. As developers' interest in different indicators varies at different stages, the content of the daily report on the homepage will also be adjusted accordingly, allowing developers to use data tools more efficiently and better operate mini programs.

[0160] Specifically, all mini-program developers (target users) initially see the same homepage interface. For example, the first data display module displays yesterday's data (including the number of visitors, new visitors, total added users, and newly added users), while the second module displays real-time visit counts. The data display module corresponds to the data processing unit of the data tool, which displays the results of the mini-program's access data analysis through the corresponding data display module on the homepage.

[0161] However, target users need to view various data due to the operation of the mini program, and need to use different data display modules to view data indicators. Target users from different industries focus on different data indicators due to industry characteristics or personal needs. This difference in the degree of attention will be reflected in the target users' usage habits of data tools. For example, developer A is particularly concerned about new users, so he will often check the data display module corresponding to retention data. Developer B is very concerned about the source of users, so he will often check the data display module corresponding to source analysis. Furthermore, for the same target user, the indicators he cares about at different stages of operating the mini program are also different. In the early stages of the mini program, the number of users is small, so he is more concerned about the effect of different channels on attracting new users. In this case, he will often visit the data display module corresponding to source analysis. When the number of mini program users increases, he will be more concerned about the retention effect of active users, so he will often visit the data display module corresponding to retention data.

[0162] Since different module paths are different, some data module paths are relatively deep. According to the traditional way of viewing data indicators, target users need to spend more operations to view them frequently. In order to enable target users to efficiently view the data they care about, cluster analysis is performed on the record data of target users using data tools. Then, the data indicators that the target users focus on are obtained, and the data indicators that are focused on are further sorted to obtain the homepage of the data tool.

[0163] Among them, such as Figure 9 As shown, the implementation process details include: the target user (such as user A, user B or user C) operates the displayed data indicators of interest through the client of the data tool, and the client of the data tool records the target user's operation behavior, recording data such as operation time, operation module, operation behavior and other user behavior data. The client of the data tool uploads the recorded data corresponding to each target user's operation to the server. The server uses the clustering module to cluster the recorded data of the same target user to obtain the clustering results. For each target user, a key focus class can be obtained from the clustering results. The data processing units involved in each key focus class are sorted according to the number of days and number of times used since the most recent day, and then the sorting results are returned to the client of the data tool accessed by the corresponding target user. The client of the data tool displays the corresponding access data analysis results according to the data display module corresponding to the data processing unit. The client of the data tool displays different homepages for different target users.

[0164] The clustering process includes: the server converts the initial record data reported by the client of the data tool according to the operation time period to obtain a data table consisting of simplified record data. The server inputs the data table into the clustering analysis model (K-means) to obtain the candidate cluster set corresponding to the target user's record data, selects the focus class, namely the target cluster set, from the candidate cluster set, and sorts the data processing units involved in the target cluster set according to the combination of the number of days and times of use since the most recent day. Based on the sorting of the data processing units, the sorting of the data display module on the homepage of the data tool for the target user is obtained.

[0165] Furthermore, the recorded data can also record the subunits of specific operations in the data processing unit. The subunits in the data processing unit correspond to the data indicators in the data display module. For example, through the clustering model, it is determined that user A's main focus category is new user-related data. The number of days and times of use since the most recent day for the three data indicators of new visiting users, newly added users, and the top 5 new user access sources are (1, 23), (1, 10), and (2, 5), respectively. Therefore, new visiting users and newly added users are ahead of the top 5 new user access sources. To meet the user's adjustment of focus in different periods, the clustering model is re-run every two weeks, and then a new homepage is obtained based on the updated ranking results.

[0166] It should be understood that although Figure 2 、 Figure 6-8 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 2 、 Figure 6-8 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The order of execution of these steps or stages is not necessarily one by one, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0167] In one embodiment, Figure 10 As shown, a device 1000 for determining the display content of an analysis page is provided. The device can be implemented as a software module or a hardware module, or a combination of both to form a part of a computer device. The device specifically includes a record data acquisition module 1002, a cluster processing module 1004, a target cluster set screening module 1006, and a display content determination module 1008:

[0168] The record data acquisition module 1002 is used to acquire the record data generated by the target user's operation on the data processing unit in the data tool, and the data processing unit is used to analyze the access data of the target application corresponding to the target user;

[0169] A clustering processing module 1004 is used to perform clustering processing on the recorded data to obtain multiple candidate cluster sets;

[0170] A target cluster set screening module 1006 is configured to screen a target cluster set from the candidate cluster sets, wherein the cluster center time corresponding to the cluster center of the target cluster set meets the time screening condition, and the cluster center time is associated with the operation time in the recorded data in the target cluster set;

[0171] The display content determination module 1008 is configured to determine, based on the target data processing unit that matches the record data in the target cluster set, the content displayed when the target user accesses the analysis page of the data tool for the target application.

[0172] In one embodiment, the number of the target data processing units is no less than 2; the displayed content is the access data analysis result corresponding to the target data processing unit; the display content determination device of the analysis page further includes a display position determination module; the display position determination module includes an operation time acquisition unit and a display position determination unit;

[0173] The operation time acquisition unit is used to respectively acquire the operation time in the record data matched by each target data processing unit;

[0174] The display position determining unit is configured to determine a sorted display position of the access data analysis result on the analysis page according to a time interval between the operation time and the current time.

[0175] In one embodiment, the operation time is an operation time period, and the recorded data further includes the number of operations on the same data processing unit within the operation time period;

[0176] The display position determination unit includes a time interval determination subunit, an operation number acquisition subunit and a display position determination subunit;

[0177] The time interval determination subunit is configured to determine the time interval between the operation time period and the current time period based on the operation time period in the recorded data matched by the target data processing unit;

[0178] The operation count acquisition subunit is configured to respectively acquire the operation count in each target record data when there are at least two target record data with the same time interval;

[0179] The display position determination subunit is configured to determine a sorted display position of the access data analysis result on the analysis page based on the time interval and the number of operations.

[0180] In one embodiment, the display position determination subunit includes a primary sorting subunit, a secondary sorting subunit, and a sorting display position determination subunit;

[0181] The primary sorting subunit is configured to perform primary sorting on the recorded data based on the time interval, wherein the recorded data with the same time interval have the same sorting order;

[0182] The secondary sorting subunit is used to perform secondary sorting on the record data with the same sorting order based on the number of operations;

[0183] The sorting display position determining subunit is configured to determine a sorting display position of the access data analysis result on the analysis page based on the results of the primary sorting and the secondary sorting.

[0184] In one embodiment, the record data acquisition module includes an initial record data acquisition unit and a record data conversion unit;

[0185] The initial record data acquisition unit is used to acquire initial record data of the target user operating the data processing unit in the data tool;

[0186] The record data conversion unit is used to convert multiple initial record data with different operation time points into record data corresponding to the operation time period according to the operation time period to which the operation time points belong, and the number of operations in the record data is the number of converted initial record data.

[0187] In one embodiment, the recorded data further includes a subunit identifier corresponding to the subunit operated by the target user in the data processing unit;

[0188] The display content determination device of the analysis page further includes a target data processing unit determination module; the target data processing unit determination module includes a candidate data processing unit determination unit and a deduplication processing unit;

[0189] The candidate data processing unit determining unit is configured to determine, based on the to-be-matched sub-unit identifiers contained in the record data of the target cluster set, a candidate data processing unit that matches the to-be-matched sub-unit identifiers;

[0190] The deduplication processing unit is used to perform deduplication processing on the candidate data processing units to obtain a target data processing unit.

[0191] In one embodiment, the display content determination device of the analysis page further includes a display position determination module; the display position determination module includes a target subunit determination module, a first display area determination module, and a second display area determination module;

[0192] The target subunit determining module is configured to determine a target subunit in each target data processing unit based on the subunit corresponding to the to-be-matched subunit identifier, wherein the time interval between the operation time in the recorded data corresponding to the target subunit and the current time meets the time interval screening condition;

[0193] The first display area determination unit is configured to determine, based on the interval time corresponding to each of the target subunits, a display area on the analysis page for the access data analysis result corresponding to the target data processing unit where the target subunit is located;

[0194] The second display area determination unit is used to determine the display position of the access data analysis results corresponding to each subunit in the display area corresponding to the corresponding target data processing unit for each target data processing unit based on the time interval corresponding to each subunit in the corresponding target data processing unit.

[0195] In one embodiment, the recorded data is multi-dimensional data; the clustering processing module is further configured to perform multi-dimensional K-means clustering processing based on the multi-dimensional data to obtain a plurality of candidate cluster sets.

[0196] In one embodiment, the display content determination device of the analysis page also includes a loop module, which is used to obtain the record data generated by the target user's operation on the data processing unit in the data tool for each clustering cycle; according to the clustering cycle, the record data within the clustering cycle is clustered to obtain multiple candidate cluster sets.

[0197] In one embodiment, Figure 11 As shown, a display device 1100 for analyzing pages is provided. The device can adopt a software module or a hardware module, or a combination of the two to become a part of a computer device. The device specifically includes a first display module 1102 and a second display module 1104.

[0198] A first display module 1102 is configured to, in response to a target user's access operation to the analysis page of the data tool, display an analysis page corresponding to the target application selected by the target user;

[0199] A second display module 1104 is configured to display, in order, on the analysis page the results of the access data analysis of the target application by each target data processing unit, based on the time interval between the operation time in the recorded data corresponding to the target data processing unit in the data tool and the current time;

[0200] Among them, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool.

[0201] In one embodiment, the second display module includes a display area sorting display unit and a display area content display unit;

[0202] The display area sorting display unit is used to sort and display the access data analysis results corresponding to each target data processing unit in the display area of ​​the analysis page based on the time interval corresponding to the target sub-unit in each target data processing unit;

[0203] The display area content display unit is used to, for each target data processing unit, sort and display the access data analysis results corresponding to each sub-unit in the display area corresponding to the corresponding target data processing unit based on the time interval between the operation time corresponding to each sub-unit in the corresponding target data processing unit and the current time;

[0204] The time interval between the operation time in the recorded data corresponding to the target subunit and the current time meets the time interval screening condition.

[0205] Regarding the specific embodiments of the display content determination device for the analysis page and the display device for the analysis page, please refer to the embodiments of the display content determination method for the analysis page and the display method for the analysis page above, which will not be repeated here. The various modules in the above-mentioned display content determination device for the analysis page and the display device for the analysis page can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0206] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 12As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store recorded data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a method for determining the display content of an analysis page.

[0207] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 13 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for analyzing a display device of a page is implemented. The display screen of the computer device can be a liquid crystal display or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0208] Those skilled in the art will understand that Figure 12 and Figure 13 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0209] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0210] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above-mentioned method embodiments when executed by a processor.

[0211] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps of each of the above-described method embodiments.

[0212] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0213] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0214] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for determining the display content of an analysis page, characterized in that: The method comprises: Obtaining recorded data generated by a target user operating a data processing unit in a data tool, the data processing unit being used to perform access data analysis on a target application corresponding to the target user; the recorded data recording the subunit corresponding to each operation and the data processing unit to which the subunit belongs; the recorded data being obtained by converting a plurality of initial recorded data according to the operation time period to which the operation time point belongs, the recorded data including the time interval between the operation time period of the recorded data and the current time period; According to the clustering period, clustering is performed on the recorded data within the clustering period to obtain multiple candidate cluster sets; Filtering a target cluster set from the candidate cluster set, wherein the cluster center time corresponding to the cluster center of the target cluster set meets the time screening condition, and the cluster center time is associated with the operation time period in the recorded data in the target cluster set; Based on the target data processing unit that matches the record data in the target cluster set, it is determined that when the target user accesses the analysis page of the data tool for the target application, the access data analysis result corresponding to the target data processing unit is in the display area of ​​the analysis page; the target data processing unit includes target sub-units, and the time interval corresponding to the target sub-unit meets the time interval filtering condition; the display area is determined based on the interval time corresponding to each of the target sub-units; each sub-unit in each target data processing unit is determined based on the time interval corresponding to each sub-unit.

2. The method according to claim 1, characterized in that The number of the target data processing units is no less than 2; and the method further comprises: respectively obtaining an operation time period in the recorded data matched by each target data processing unit; According to the time interval between the operation time period and the current time period, the sorting and display position of the access data analysis result on the analysis page is determined.

3. The method according to claim 2, characterized in that The recorded data also includes the number of operations on the same data processing unit during the operation time period; The determining, according to the time interval between the operation time period and the current time period, a sorting and displaying position of the access data analysis result on the analysis page includes: determining a time interval between the operation time period in the recorded data matched by the target data processing unit and a current time period; When there are at least two target record data with the same time interval, respectively obtain the number of operations in each of the target record data; Based on the time interval and the number of operations, a sorted display position of the access data analysis result on the analysis page is determined.

4. The method according to claim 3, characterized in that The determining, based on the time interval and the number of operations, a sorted display position of the access data analysis result on the analysis page includes: Based on the time interval, the recorded data are initially sorted, wherein the recorded data with the same time interval have the same sorting order; Based on the number of operations, performing secondary sorting on the record data with the same sorting order; Based on the results of the primary sorting and the secondary sorting, a sorting display position of the access data analysis result on the analysis page is determined.

5. The method according to claim 3, characterized in that The obtaining of the recorded data generated by the target user operating the data processing unit in the data tool includes: Acquiring initial record data of a target user operating a data processing unit in a data tool; For multiple initial record data with different operation time points, they are converted into record data corresponding to the operation time period according to the operation time period to which the operation time points belong. The number of operations in the record data is the number of converted initial record data.

6. The method according to claim 1, characterized in that The recorded data also includes a subunit identifier corresponding to the subunit operated by the target user in the data processing unit; The method further comprises: Determining, based on the to-be-matched subunit identifiers contained in each of the record data of the target cluster set, candidate data processing units that match the to-be-matched subunit identifiers; Deduplication processing is performed on the candidate data processing units to obtain a target data processing unit.

7. The method according to claim 6, characterized in that The method further comprises: Determining a target subunit in each target data processing unit based on the subunit corresponding to the to-be-matched subunit identifier; Based on the interval time corresponding to each of the target sub-units, determining the display area of ​​the analysis page for the access data analysis result corresponding to the target data processing unit where the target sub-unit is located; For each target data processing unit, based on the time intervals corresponding to the subunits in the corresponding target data processing unit, the display position of the access data analysis results corresponding to the subunits in the display area corresponding to the corresponding target data processing unit is determined.

8. The method according to any one of claims 1 to 7, characterized in that The recorded data is multi-dimensional data; The clustering process is performed on the recorded data to obtain a plurality of candidate cluster sets, including: Based on the multi-dimensional data, a multi-dimensional K-means clustering process is performed to obtain a plurality of candidate cluster sets.

9. The method according to any one of claims 1 to 7, characterized in that The method further comprises: For each clustering period, record data generated by the target user operating the data processing unit in the data tool is obtained.

10. A method for displaying an analysis page, characterized in that: The method comprises: In response to a target user's access operation to an analysis page of a data tool, based on a target application selected by the target user, displaying an analysis page corresponding to the target application; Based on the time intervals corresponding to the target sub-units filtered out from each target data processing unit, the access data analysis results corresponding to each target data processing unit are displayed in a display area of ​​the analysis page in order; For each target data processing unit, based on the time intervals corresponding to the sub-units in the corresponding target data processing unit, the access data analysis results corresponding to the sub-units are displayed in order in the display area corresponding to the corresponding target data processing unit; Among them, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool; the recorded data records the sub-unit corresponding to each operation and the data processing unit to which the sub-unit belongs; the recorded data is obtained by converting multiple initial recorded data according to the operation time period to which the operation time point belongs; the recorded data includes the time interval between the operation time period of the recorded data and the current time period; the time interval in the recorded data corresponding to the target sub-unit meets the time interval filtering condition.

11. A device for determining the display content of an analysis page, characterized in that: The device comprises: A record data acquisition module is used to acquire record data generated by a target user operating a data processing unit in a data tool, wherein the data processing unit is used to perform access data analysis on a target application corresponding to the target user; the record data records the subunit corresponding to each operation and the data processing unit to which the subunit belongs; the record data is obtained by converting multiple initial record data according to the operation time period to which the operation time point belongs, and the record data includes the time interval between the operation time period of the record data and the current time period; A clustering processing module, configured to perform clustering processing on the recorded data within the clustering period according to the clustering period to obtain a plurality of candidate cluster sets; a target cluster set screening module, configured to screen a target cluster set from the candidate cluster set, wherein the cluster center time corresponding to the cluster center of the target cluster set meets the time screening condition, and the cluster center time is associated with the operation time period in the recorded data in the target cluster set; A display area determination module is used to determine, based on a target data processing unit that matches the record data in the target cluster set, when the target user accesses the analysis page of the data tool for the target application, the display area of ​​the analysis page where the access data analysis result corresponding to the target data processing unit is displayed; the target data processing unit includes a target sub-unit, and the time interval corresponding to the target sub-unit meets the time interval filtering condition; the display area is determined based on the interval time corresponding to each of the target sub-units; and each sub-unit in each target data processing unit is determined based on the time interval corresponding to each sub-unit.

12. The device for determining display content of an analysis page according to claim 11, characterized in that: The number of the target data processing units is not less than 2; the device further comprises: an operation time period obtaining unit, configured to respectively obtain the operation time period in the recorded data matched by each of the target data processing units; The sorting display position determining unit is configured to determine the sorting display position of the access data analysis result on the analysis page according to the time interval between the operation time period and the current time period.

13. The device for determining display content of an analysis page according to claim 12, characterized in that: The recorded data also includes the number of operations on the same data processing unit during the operation time period; The sorting display position determination unit is further configured to: determining a time interval between the operation time period in the recorded data matched by the target data processing unit and a current time period; When there are at least two target record data with the same time interval, respectively obtain the number of operations in each of the target record data; Based on the time interval and the number of operations, a sorted display position of the access data analysis result on the analysis page is determined.

14. The device for determining display content of an analysis page according to claim 13, wherein: The sorting display position determination unit is further configured to: Based on the time interval, the recorded data are initially sorted, wherein the recorded data with the same time interval have the same sorting order; Based on the number of operations, performing secondary sorting on the record data with the same sorting order; Based on the results of the primary sorting and the secondary sorting, a sorting display position of the access data analysis result on the analysis page is determined.

15. The device for determining display content of an analysis page according to claim 13, wherein: The record data acquisition module is also used for: Acquiring initial record data of a target user operating a data processing unit in a data tool; For multiple initial record data with different operation time points, they are converted into record data corresponding to the operation time period according to the operation time period to which the operation time points belong. The number of operations in the record data is the number of converted initial record data.

16. The device for determining display content of an analysis page according to claim 11, characterized in that: The recorded data also includes a subunit identifier corresponding to the subunit operated by the target user in the data processing unit; The device further comprises: a candidate data processing unit determining unit, configured to determine, based on the to-be-matched sub-unit identifiers contained in the record data of the target cluster set, a candidate data processing unit that matches the to-be-matched sub-unit identifiers; The deduplication processing unit is used to perform deduplication processing on the candidate data processing units to obtain the target data processing unit.

17. The device for determining display content of an analysis page according to claim 16, wherein: The device further comprises: a target subunit determining unit, configured to determine a target subunit in each target data processing unit based on the subunit corresponding to the to-be-matched subunit identifier; A first display area determination unit is configured to determine, based on the interval time corresponding to each target sub-unit, a display area of ​​the analysis page for the access data analysis result corresponding to the target data processing unit where the target sub-unit is located; The second display area determination unit is used to determine the display position of the access data analysis results corresponding to each subunit in the display area corresponding to the corresponding target data processing unit for each target data processing unit based on the time interval corresponding to each subunit in the corresponding target data processing unit.

18. The device for determining display content of an analysis page according to any one of claims 11 to 17, characterized in that: The recorded data is multi-dimensional data; The cluster processing module is further configured to perform multi-dimensional K-means clustering processing based on the multi-dimensional data to obtain a plurality of candidate cluster sets.

19. The device for determining display content of an analysis page according to any one of claims 11 to 17, characterized in that: The device further comprises: The periodic record data acquisition unit is used to acquire, for each clustering period, the record data generated by the target user operating the data processing unit in the data tool.

20. A display device for analyzing a page, characterized in that: The device comprises: A first display module is configured to, in response to a target user's access operation to the analysis page of the data tool, display an analysis page corresponding to the target application based on the target application selected by the target user; A second display module is configured to, based on the time intervals corresponding to the target sub-units screened from each target data processing unit, sort and display the access data analysis results corresponding to each target data processing unit in the display area of ​​the analysis page; and for each target data processing unit, based on the time intervals corresponding to each sub-unit in the corresponding target data processing unit, sort and display the access data analysis results corresponding to each sub-unit in the display area corresponding to the corresponding target data processing unit; Among them, the target data processing unit is the data processing unit corresponding to the target cluster set in the candidate cluster set; the candidate cluster set is the result of clustering processing of the recorded data; the cluster center time corresponding to the cluster center of the target cluster set meets the time filtering condition; the cluster center time is associated with the operation time in the recorded data in the target cluster set; the recorded data is used to describe the target user's operation on the data processing unit in the data tool; the recorded data records the sub-unit corresponding to each operation and the data processing unit to which the sub-unit belongs; the recorded data is obtained by converting multiple initial recorded data according to the operation time period to which the operation time point belongs; the recorded data includes the time interval between the operation time period of the recorded data and the current time period; the time interval in the recorded data corresponding to the target sub-unit meets the time interval filtering condition.

21. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 10 is implemented.

22. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 10 is implemented.

23. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the method according to any one of claims 1 to 10 is implemented.

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