Behavior data processing method and device, computer device and storage medium

Abstract

The application relates to a behavior data processing method and device, computer equipment, a storage medium and a computer program product, which can be used in the field of artificial intelligence technology and can collect behavior data without invasion. The method comprises the following steps: generating a page image corresponding to a current page when it is detected that the display time of the current page meets a preset time condition; collecting page operations of a target user for the current page through the page image to obtain a behavior image corresponding to the target user; screening a behavior image meeting a preset similarity condition from a plurality of behavior images corresponding to the target user as a to-be-fused image according to the similarity between the plurality of behavior images; and performing fusion processing on page operation information in a plurality of to-be-fused images to obtain a target behavior image corresponding to the target user.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and in particular to a behavioral data processing method, apparatus, computer equipment, storage medium, and computer program product. Background Technology

[0002] Capturing, processing, and transmitting specific user behaviors or events is an important aspect of user behavior data collection. It enables the collection of user behavior data within applications to track application usage and provide data support for subsequent application optimization and operation.

[0003] Currently, user behavior data is often collected through event tracking technology, such as code-based event tracking. However, this method is highly intrusive to the application's pages, which can easily cause page lag and result in a lot of noise and low accuracy in the collected behavior data. Summary of the Invention

[0004] Therefore, it is necessary to provide a behavioral data processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can collect behavioral data non-intrusively, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a method for processing behavioral data. The method includes:

[0006] If the display time of the current page meets the preset time condition, generate the page image corresponding to the current page;

[0007] By using the page image, the page operations of the target user on the current page are collected to obtain the behavior image corresponding to the target user;

[0008] Based on the similarity between multiple behavioral images corresponding to the target user, behavioral images that meet the preset similarity conditions are selected from the multiple behavioral images and used as images to be fused.

[0009] The page operation information in multiple images to be fused is fused to obtain the target behavior image corresponding to the target user.

[0010] In one embodiment, based on the similarity between multiple behavioral images corresponding to the target user, behavioral images that meet preset similarity conditions are selected from the multiple behavioral images as images to be fused, including:

[0011] Based on the size of each behavior image and the amount of page operation information contained in each behavior image, each behavior image is scaled to obtain scaled behavior images.

[0012] Each of the scaled behavioral images is processed into grayscale to obtain multiple grayscale behavioral images corresponding to each of the scaled behavioral images;

[0013] Based on the similarity between the various grayscale behavioral images, grayscale behavioral images that meet the preset similarity conditions are selected from the various grayscale behavioral images and used as images to be fused.

[0014] In one embodiment, before filtering grayscale behavior images that meet a preset similarity condition from the grayscale behavior images based on the similarity between the grayscale behavior images, the method further includes:

[0015] Variance estimation is performed on each grayscale behavior image to obtain the variance features of each grayscale behavior image;

[0016] The similarity between the grayscale behavioral images is obtained based on the distance between the variance features of each grayscale behavioral image.

[0017] In one embodiment, the page image is used to capture the page operations performed by the target user on the current page, resulting in a behavior image corresponding to the target user, including:

[0018] Overlay the page image on top of the current page;

[0019] When the target user performs a page operation on the current page, the coordinate position corresponding to the page operation is captured through the page image;

[0020] Based on the current page display time and the coordinate position, a behavioral image corresponding to the target user is generated.

[0021] In one embodiment, when it is detected that the display time of the current page meets a preset time condition, a page image corresponding to the target user is generated, including:

[0022] Obtain the preset time threshold;

[0023] If the display time of the current page exceeds the preset time threshold, the current page is drawn on a canvas to obtain the page image corresponding to the target user.

[0024] In one embodiment, after fusing the page operation information in multiple images to be fused to obtain the target behavior image corresponding to the target user, the method further includes:

[0025] The target behavior images are visualized to obtain the visualized behavior data corresponding to each target behavior image, and the visualized behavior data is displayed.

[0026] In response to a selection operation on the visualized behavioral data, the target coordinate position corresponding to the selection operation is obtained;

[0027] Obtain and display all page operation information associated with the target coordinate location.

[0028] Secondly, this application also provides a behavioral data processing apparatus. The apparatus includes:

[0029] The page image generation module is used to generate a page image corresponding to the current page when the display time of the current page meets a preset time condition.

[0030] The behavior image acquisition module is used to collect the page operations of the target user on the current page through the page image, and obtain the behavior image corresponding to the target user;

[0031] The behavior image filtering module is used to filter out behavior images that meet preset similarity conditions from the multiple behavior images corresponding to the target user, based on the similarity between them, and use them as images to be fused.

[0032] The page operation fusion module is used to fuse page operation information in multiple images to be fused to obtain the target behavior image corresponding to the target user.

[0033] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0034] If the display time of the current page meets the preset time condition, generate the page image corresponding to the current page;

[0035] By using the page image, the page operations of the target user on the current page are collected to obtain the behavior image corresponding to the target user;

[0036] Based on the similarity between multiple behavioral images corresponding to the target user, behavioral images that meet the preset similarity conditions are selected from the multiple behavioral images and used as images to be fused.

[0037] The page operation information in multiple images to be fused is fused to obtain the target behavior image corresponding to the target user.

[0038] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0039] If the display time of the current page meets the preset time condition, generate the page image corresponding to the current page;

[0040] By using the page image, the page operations of the target user on the current page are collected to obtain the behavior image corresponding to the target user;

[0041] Based on the similarity between multiple behavioral images corresponding to the target user, behavioral images that meet the preset similarity conditions are selected from the multiple behavioral images and used as images to be fused.

[0042] The page operation information in multiple images to be fused is fused to obtain the target behavior image corresponding to the target user.

[0043] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0044] If the display time of the current page meets the preset time condition, generate the page image corresponding to the current page;

[0045] By using the page image, the page operations of the target user on the current page are collected to obtain the behavior image corresponding to the target user;

[0046] Based on the similarity between multiple behavioral images corresponding to the target user, behavioral images that meet the preset similarity conditions are selected from the multiple behavioral images and used as images to be fused.

[0047] The page operation information in multiple images to be fused is fused to obtain the target behavior image corresponding to the target user.

[0048] The aforementioned behavioral data processing method, apparatus, computer equipment, storage medium, and computer program product generate a page image corresponding to the current page when the display time of the current page meets a preset time condition. Then, using the page image, they collect the target user's page operations on the current page to obtain a behavioral image corresponding to the target user. Based on the similarity between multiple behavioral images corresponding to the target user, they select behavioral images that meet preset similarity conditions from the multiple behavioral images as images to be fused. The page operation information in the multiple images to be fused is then fused to obtain the target behavioral image corresponding to the target user. Using this method, the target user's behavioral image is obtained from the page image corresponding to the current page without configuring code embedding points on the current page, avoiding the impact of page operation information collection on the accuracy of the current page when intruding into the current page, thereby improving the accuracy of the obtained target behavioral image. Furthermore, by fusing the page operation information in the images to be fused, the page operation information in the target behavioral image is made more complete, thus more accurately reflecting the target user's behavior. Attached Figure Description

[0049] Figure 1 This is an application environment diagram of the behavioral data processing method in one embodiment;

[0050] Figure 2 This is a flowchart illustrating a behavioral data processing method in one embodiment;

[0051] Figure 3 This is a flowchart illustrating the step of selecting behavioral images that meet preset similarity conditions from behavioral images as images to be fused in one embodiment.

[0052] Figure 4 This is a flowchart illustrating the behavioral data processing method in another embodiment;

[0053] Figure 5 This is a timing diagram of the behavioral data processing method in yet another embodiment;

[0054] Figure 6 This is a structural block diagram of a behavior data processing device in one embodiment;

[0055] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0057] It should be noted that the behavioral data processing methods, apparatus and systems provided in this application can be used in the field of artificial intelligence technology, and can collect user behavioral data non-intrusively. They can also be used in any field other than artificial intelligence, such as the financial field. The application fields of the behavioral data processing methods, apparatus and systems in this application are not limited.

[0058] The behavioral data processing method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102 or placed on a cloud or other network server. When the display time of the current page meets a preset time condition, terminal 101 generates a page image corresponding to the current page; then, using the page image, it collects the page operations of the target user on the current page to obtain a behavior image corresponding to the target user; based on the similarity between multiple behavior images corresponding to the target user, it filters out behavior images that meet preset similarity conditions from the multiple behavior images as images to be fused; it performs fusion processing on the page operation information in the multiple images to be fused to obtain a target behavior image corresponding to the target user, and terminal 101 sends the target behavior image to server 102, where server 102 stores the received target behavior image. Terminal 101 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. Server 102 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0059] In one embodiment, such as Figure 2 As shown, a behavioral data processing method is provided, which can be applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps:

[0060] Step S201: If the display time of the current page meets the preset time condition, generate the page image corresponding to the current page.

[0061] Here, "current page" refers to the page from which behavioral data needs to be obtained. "Display time" refers to the time spent on the current page. "Page image" refers to an image that is identical to all controls, modules, and other elements on the current page.

[0062] Specifically, when a target user wants to browse a page, they can browse the current page through the terminal. At the same time, the time the target user stays on the current page is monitored and used as the display time of the current page. When the display time meets the preset time condition, the terminal draws a canvas on the current page to obtain the page image corresponding to the current page.

[0063] Step S202: Collect the target user's page operations on the current page through page images to obtain the corresponding behavior images of the target user.

[0064] Behavioral images refer to data captured and processed based on specific user behaviors or events. For example, a behavioral image may include the number of visits to the current page, the display time, the number of clicks, and the coordinates of the clicks.

[0065] Specifically, after the terminal obtains the page image in step S201 above, it can deploy the page image on the terminal. When the target user performs page operations on the current page, such as clicking on controls or refreshing the page, the page image will collect the coordinate position and number of operations corresponding to the page operations and generate corresponding behavior images.

[0066] Step S203: Based on the similarity between multiple behavioral images corresponding to the target user, select behavioral images that meet the preset similarity conditions from the multiple behavioral images as images to be fused.

[0067] The behavioral images collected and processed by the terminal can be used for data analysis of the page to continuously optimize it based on user behavior. Specifically, the terminal can first collect behavioral images corresponding to multiple target users, and then perform data analysis on the page. These behavioral images for multiple target users can be obtained by processing different pages separately; conversely, multiple behavioral images for the same target can also be obtained by processing different pages separately. Since the behavioral images carry the user identifier of the target user, the terminal can retrieve multiple behavioral images corresponding to the target user from the stored multiple behavioral images based on the user identifier. Then, based on the similarity between the multiple behavioral images, the terminal selects behavioral images that meet preset similarity conditions as the images to be fused. This can be seen as fusing behavioral images of the same or similar pages, so that the page operation information of each target user on the same or similar pages can be reflected in a single target behavioral image.

[0068] Among them, the image to be merged refers to the behavioral image in which page operation information needs to be merged.

[0069] Step S204: Perform fusion processing on the page operation information in multiple images to be fused to obtain the target behavior image corresponding to the target user.

[0070] Page operation information refers to the operation data obtained by performing page operations; for example, page operation information can be the coordinates of the page click operation, the number of clicks, or the current page display time. Target behavior image refers to a behavior image that incorporates page operation information from multiple images to be merged.

[0071] Specifically, the terminal performs fusion processing on page operation information from multiple images that meet preset similarity conditions. This can involve adding the display times of each image to obtain the total display time of the page, and storing all page operation information, such as coordinate positions, click counts, and interactive content, from each image on the fused behavior image to obtain the target behavior image corresponding to the target user. Therefore, in this embodiment, all behavioral data about the current page can be fully understood only through the target behavior image. Furthermore, to improve the terminal's resource utilization, after fusing the target behavior image, the images to be fused can be deleted, and only the target behavior image needs to be stored.

[0072] For example, suppose a target user stays on page A for 30 seconds, resulting in behavioral image 'a' for page A, and a display time of 30 seconds for behavioral image 'a'. Suppose the target user stays on page A again for 25 seconds after some time, resulting in behavioral image 'b' for page A, and a display time of 25 seconds for behavioral image 'b'. If the similarity calculation shows that behavioral images 'a' and 'b' both meet the preset similarity criteria, then behavioral images 'a' and 'b' can be merged to obtain the target behavioral image 'c'. The display time of the target behavioral image 'c' is then 30 seconds + 25 seconds = 55 seconds.

[0073] In the aforementioned behavioral data processing method, when the display time of the current page meets a preset time condition, a page image corresponding to the current page is generated. Then, using this page image, the page operations of the target user on the current page are collected to obtain a behavioral image corresponding to the target user. Based on the similarity between multiple behavioral images corresponding to the target user, behavioral images that meet preset similarity conditions are selected from these images as images to be fused. The page operation information in these multiple images to be fused is then fused to obtain the target behavioral image corresponding to the target user. This method obtains the target user's behavioral image from the page image corresponding to the current page without configuring code embedding points on the current page, avoiding the impact of page operation information collection on the accuracy of the data collection when the current page is compromised, thus improving the accuracy of the obtained target behavioral image. Furthermore, by fusing the page operation information in the images to be fused, the page operation information in the target behavioral image is made more complete, thus more accurately reflecting the target user's behavior.

[0074] In one embodiment, such as Figure 3 As shown, step S203 above, which involves selecting behavioral images that meet preset similarity conditions from multiple behavioral images corresponding to the target user as images to be fused based on the similarity between them, specifically includes the following:

[0075] Step S301: Based on the size of each behavior image and the amount of page operation information contained in each behavior image, scale each behavior image to obtain scaled behavior images.

[0076] Because different terminals have different screen sizes, the sizes of the behavioral images processed by different terminals will also be different. Therefore, it is necessary to first process each behavioral image into a behavioral image of the same or similar size. Specifically, the terminal obtains the size of each behavioral image and the amount of page operation information contained in each behavioral image. The terminal performs scaling processing on each behavioral image. This can be done by selecting the behavioral image with the most page operation information as the standard behavioral image, and then scaling all other behavioral images according to the size of the standard behavioral image to obtain scaled behavioral images. Alternatively, the terminal can determine the standard size of the behavioral images based on the average number of page operation information contained in each behavioral image, and then scale each behavioral image according to this standard size, so that the scaled behavioral images of each behavioral image are all of the standard size.

[0077] Step S302: Perform grayscale processing on each scaled behavioral image to obtain multiple grayscale behavioral images corresponding to each scaled behavioral image.

[0078] Since the similarity between the various scaled behavioral images in this embodiment is independent of the color information of each scaled behavioral image, the terminal can perform grayscale processing on each scaled behavioral image to obtain multiple grayscale behavioral images corresponding to each scaled behavioral image, thereby reducing the terminal's computing resource consumption and improving the processing efficiency of the target behavioral image.

[0079] Step S303: Based on the similarity between the grayscale action images, select grayscale action images that meet the preset similarity conditions from the grayscale action images and use them as images to be fused.

[0080] Specifically, the terminal acquires the features of pixels in each grayscale action image, uses the difference between the features of each grayscale action image as the similarity between each grayscale action image, and then determines whether the similarity of each grayscale action image meets the preset similarity condition. For example, the preset similarity condition can be set to meet the similarity below the similarity threshold. Then the terminal can use grayscale action images whose feature differences are below the similarity threshold as images to be fused.

[0081] In this embodiment, each behavior image is scaled according to its size and the amount of page operation information it contains, resulting in scaled behavior images. Then, each scaled behavior image is processed in grayscale to obtain multiple grayscale behavior images corresponding to each scaled behavior image. Finally, based on the similarity between the grayscale behavior images, grayscale behavior images that meet preset similarity conditions are selected as images to be fused, thus achieving reasonable selection of images to be fused. These images are then used as the basis for subsequent fusion processing.

[0082] In one embodiment, before step S303 above, which selects grayscale behavior images that meet preset similarity conditions from the grayscale behavior images based on the similarity between the grayscale behavior images, and uses them as images to be fused, the method further includes: performing variance estimation on each grayscale behavior image to obtain the variance features of each grayscale behavior image; and obtaining the similarity between the grayscale behavior images based on the distance between the variance features of each grayscale behavior image.

[0083] Specifically, the terminal obtains the average value of pixels in each grayscale action image, which can be achieved by sequentially calculating the average value of pixels in each row of each grayscale action image; then, variance estimation is performed on this average value to calculate the variance features of each grayscale action image; the distance between the variance features of each grayscale action image is determined, and the distance between the variance features is used as the similarity between the corresponding grayscale action images. In practical applications, similarity can also be used to describe the closeness between the variance features of two grayscale action images. Therefore, the smaller the difference between two variance features, the closer the distance between the two variance features, and the higher the similarity between the grayscale action images corresponding to the two variance features.

[0084] In this embodiment, variance features of each grayscale behavior image are obtained by performing variance estimation on each grayscale behavior image; the similarity between each grayscale behavior image is obtained based on the distance between the variance features of each grayscale behavior image, thus realizing the reasonable acquisition of the similarity between each grayscale behavior image. This is beneficial for selecting the images to be fused based on similarity and fusing them in subsequent behavior data processing steps. As a result, all behavior data on the same page can be viewed through the target behavior image obtained by fusion, thereby improving the efficiency of behavior data utilization.

[0085] In one embodiment, step S202 above, which involves collecting the target user's page operations on the current page using a page image to obtain a behavior image corresponding to the target user, specifically includes the following: covering the current page with a page image; collecting the coordinate positions corresponding to the page operations using the page image when the target user performs page operations on the current page; and generating a behavior image corresponding to the target user based on the display time and coordinate positions of the current page.

[0086] Specifically, the terminal overlays the acquired page image onto the current page, so that when the target user interacts with the page, the page image can monitor the user's actions and collect the corresponding coordinates and number of operations. When the current page stops displaying, the display time of the current page is acquired again and stored in the page image. At this point, the page image containing the target user's page operation information, such as coordinates, number of operations, and display time, serves as the target user's behavior image. The terminal can also send the behavior image to a server for storage. It is understandable that, since the page image is drawn at the original scale (1:1) of the current page, the coordinates and number of operations in the behavior image accurately reflect the target user's page operations at that moment.

[0087] In this embodiment, by overlaying a page image on top of the current page, the coordinates of the page operation can be captured using the page image when the target user performs page operations on the current page. Then, based on the display time and coordinates of the current page, a behavior image corresponding to the target user is generated, which achieves accurate collection of the target user's page operation information. It also eliminates the need to configure code embedding points in the current page, avoiding the impact on the target user's page operation when the current page is invaded.

[0088] In one embodiment, step S201 above, which generates a page image corresponding to the current page when the display time of the current page meets a preset time condition, specifically includes the following: obtaining a preset time threshold; and drawing a canvas on the current page to obtain a page image corresponding to the current page when the display time of the current page exceeds the preset time threshold.

[0089] Among them, the preset time threshold refers to the threshold that is preset for the decoupling time of the current page's frizz.

[0090] Specifically, the terminal displays the current page for the target user to browse and monitors the time the target user stays on the current page to obtain the display time of the current page. When the display time of the current page is detected to exceed a preset time threshold, the terminal uses Canvas technology to draw the current page at a 1:1 scale and stores the drawn image as a page image in base64 encoded format, and includes the target user's user identifier in the page image. The base64 encoded page image is a text-formatted image, which can reduce the terminal's resource consumption.

[0091] In this embodiment, by obtaining a preset time threshold, and then when the display time of the current page is detected to exceed the preset time threshold, the current page is drawn on a canvas to obtain a page image in the encoding format corresponding to the current page. This greatly reduces the resource consumption of the terminal, thereby further reducing the intrusion on the current page and helping to improve the accuracy and processing efficiency of the behavioral image obtained through page image processing.

[0092] In one embodiment, after fusing page operation information from multiple images to be fused to obtain a target behavior image corresponding to the target user, the method further includes: performing visualization processing on each target behavior image to obtain visualized behavior data corresponding to each target behavior image, and displaying each visualized behavior data; in response to a selection operation on the visualized behavior data, obtaining the target coordinate position corresponding to the selection operation; and obtaining and displaying all page operation information associated with the target coordinate position.

[0093] Visualized behavioral data refers to the conversion of target behavioral images into graphics, images, or charts and displayed on the screen. It should be noted that although the target behavioral image contains the word "image" in its name, it is actually an image stored in base64 encoded format, which is different from images or pictures that intuitively reflect patterns or scenes in the traditional sense.

[0094] The target coordinates refer to the selected coordinates of the location that needs to be viewed.

[0095] Specifically, the terminal performs visualization processing on each target behavior image, which can be done by converting each target behavior image into page images or chart data to obtain the visualization data corresponding to each target behavior image, and then displaying the visualization data on the screen for back-end staff to view.

[0096] In addition, staff can also choose to view data from a specific area. The terminal detects the area selection operation of the visualized behavioral data. This can be done by either circling the area to be viewed, determining the viewing range based on the circle's shape and center coordinates, obtaining the coordinates of all targets within that range, and then retrieving all page operation information associated with each target coordinate from the target behavioral image and displaying it on the screen; or by selecting the area to be viewed using a rectangle in the toolbar displayed on the screen, determining the coordinates of the four vertices of the rectangle, determining the viewing range based on these coordinates, obtaining the coordinates of all targets within that range, and then retrieving all page operation information associated with each target coordinate from the target behavioral image and displaying it on the screen.

[0097] Staff can also choose to view data at a specific location. They can click on the location to be viewed in the visualized behavior data, and the terminal will obtain the target coordinates of the location to be viewed. Based on the target coordinates, all page operation information associated with the target coordinates is obtained from the target behavior image, and all page operation information is displayed on the screen.

[0098] In this embodiment, by visualizing each target behavior image, visualized behavior data corresponding to each target behavior image is obtained and displayed. In response to a selection operation on the visualized behavior data, the target coordinate position corresponding to the selection operation is obtained. All page operation information associated with the target coordinate position is obtained and displayed, thereby realizing the visualized display of the target behavior image and the display of page operation information of the local target coordinate position. This provides the backend staff with behavior data of each page, thereby providing accurate data support for the iterative optimization of the page.

[0099] In one embodiment, such as Figure 4 As shown, another behavioral data processing method is provided, which can be applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps:

[0100] Step S401: Obtain a preset time threshold; if the display time of the current page exceeds the preset time threshold, draw the canvas on the current page to obtain the page image corresponding to the current page.

[0101] Step S402: Overlay the page image on top of the current page; when the target user performs page operations on the current page, collect the coordinate position corresponding to the page operation through the page image.

[0102] Step S403: Generate a behavioral image corresponding to the target user based on the current page display time and coordinate location.

[0103] Step S404: Based on the size of each behavior image and the amount of page operation information contained in each behavior image, scale each behavior image to obtain scaled behavior images.

[0104] Step S405: Perform grayscale processing on each scaled behavioral image to obtain multiple grayscale behavioral images corresponding to each scaled behavioral image.

[0105] Step S406: Perform variance estimation on each grayscale behavior image to obtain the variance features of each grayscale behavior image.

[0106] Step S407: Based on the distance between the variance features of each grayscale action image, obtain the similarity between each grayscale action image.

[0107] Step S408: Perform fusion processing on the page operation information in multiple images to be fused to obtain the target behavior image corresponding to the target user.

[0108] The above-mentioned behavioral data processing method can achieve the following beneficial effects: it can obtain the behavioral image of the target user by collecting the page image corresponding to the current page without configuring code embedding points in the current page, thus avoiding the impact of intrusion into the current page on the accurate collection of page operation information, thereby improving the accuracy of the obtained target behavioral image; by fusing the page operation information in the image to be fused, it also makes the page operation information in the target behavioral image more complete and more accurate.

[0109] To more clearly illustrate the behavioral data processing method provided in this disclosure, a specific embodiment will be used to describe the method in detail below. For example... Figure 5 As shown, another behavioral data processing method is provided, which can be applied to... Figure 1 The terminal in the system specifically includes the following:

[0110] (1) Access the current page: The user requests access to the current page by launching the application through the terminal, and the terminal displays the current page.

[0111] (2) Generate page image: If the display time of the current page on the terminal exceeds the preset time threshold, that is, when the user stays on the current page for more than the preset time threshold, the terminal draws the current page on a 1:1 canvas according to the current page ratio, and stores the drawn image as a page image in base64 format.

[0112] (3) Arrange page image: Place the page image on top of the current page.

[0113] (4) Perform page operations: Users can perform page operations such as clicking and refreshing the current page displayed on the terminal.

[0114] (5) Collect page operations: When the page image overlaid on the current page detects a page operation on the current page, it collects the two-dimensional coordinate position corresponding to the page operation to obtain the behavior image corresponding to the current page; the behavior image stores page information, display time and two-dimensional coordinate position and other page operation information of the current page.

[0115] (6) Stop accessing the current page: If the user requests to stop accessing the current page, the terminal will stop displaying the current page.

[0116] (7) Upload Behavioral Images: Send the behavioral images to the server for storage. Additionally, it can be understood that the server can also fuse page operation information from behavioral images of the same or similar pages of the same user to obtain the target behavioral image corresponding to the user. From the target behavioral images corresponding to each user, determine the behavioral image to be viewed, and obtain and display all relevant page operation information in that behavioral image.

[0117] In this embodiment, the problem of page lag caused by intrusion into the page in traditional methods, resulting in more noise and lower accuracy in behavior images, is solved. By generating a page image corresponding to the current page through canvas technology, and then using the page image to collect the behavior image of the target user, not only is intrusion into the current page avoided, but the accuracy of the acquired behavior image is also improved.

[0118] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0119] Based on the same inventive concept, this application also provides a behavior data processing apparatus for implementing the behavior data processing method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more behavior data processing apparatus embodiments provided below can be found in the limitations of the behavior data processing method described above, and will not be repeated here.

[0120] In one embodiment, such as Figure 6 As shown, a behavior data processing device 600 is provided, including: a page image generation module 601, a behavior image acquisition module 602, a behavior image filtering module 603, and a page operation fusion module, wherein:

[0121] The page image generation module 601 is used to generate the page image corresponding to the current page when the display time of the current page meets the preset time conditions.

[0122] The behavior image acquisition module 602 is used to collect the page operations of the target user on the current page through the page image to obtain the behavior image corresponding to the target user.

[0123] The behavior image filtering module 603 is used to filter out behavior images that meet preset similarity conditions from multiple behavior images based on the similarity between them, and use them as images to be fused.

[0124] The page operation fusion module 604 is used to fuse page operation information in multiple images to obtain the target behavior image corresponding to the target user.

[0125] In one embodiment, the behavior image filtering module 603 is further configured to scale each behavior image according to its size and the amount of page operation information contained in each behavior image to obtain scaled behavior images; perform grayscale processing on each scaled behavior image to obtain multiple grayscale behavior images corresponding to each scaled behavior image; and filter out grayscale behavior images that meet preset similarity conditions from each grayscale behavior image based on the similarity between each grayscale behavior image as images to be fused.

[0126] In one embodiment, the behavior data processing device 600 further includes a similarity determination module, which is used to perform variance estimation on each grayscale behavior image to obtain the variance features of each grayscale behavior image; and to obtain the similarity between each grayscale behavior image based on the distance between the variance features of each grayscale behavior image.

[0127] In one embodiment, the behavior image acquisition module 602 is further configured to overlay a page image on top of the current page; when the target user performs a page operation on the current page, to acquire the coordinate position corresponding to the page operation through the page image; and to generate a behavior image corresponding to the target user based on the display time and coordinate position of the current page.

[0128] In one embodiment, the page image generation module 601 is further configured to obtain a preset time threshold; and if the display time of the current page is detected to exceed the preset time threshold, to draw a canvas on the current page to obtain the page image corresponding to the current page.

[0129] In one embodiment, the behavior data processing device 600 further includes a visualization display module, which is used to perform visualization processing on each target behavior image to obtain visualized behavior data corresponding to each target behavior image, and display each visualized behavior data; in response to a selection operation on the visualized behavior data, obtain the target coordinate position corresponding to the selection operation; and obtain and display all page operation information associated with the target coordinate position.

[0130] Each module in the aforementioned behavioral data processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0131] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a behavioral data processing method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0132] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0133] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0134] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0135] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0136] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0137] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0138] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0139] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A behavioral data processing method, characterized in that, The method includes: If the display time of the current page meets the preset time condition, a page image corresponding to the current page is generated, wherein the page image is an image in an encoded format drawn according to the original scale of the current page; By using the page images, the page operations of the target user on the current page are collected to obtain the behavior images corresponding to the target user; Based on the similarity between multiple behavioral images corresponding to the target user, behavioral images that meet the preset similarity conditions are selected from the multiple behavioral images and used as images to be fused. The page operation information in multiple images to be fused is fused to obtain the target behavior image corresponding to the target user; The page operation information refers to the operation data obtained by performing page operations on the page, and the target behavior image refers to the behavior image that integrates page operation information from multiple images to be integrated. The step of collecting page operations performed by the target user on the current page through the page image to obtain the corresponding behavior image of the target user includes: Overlay the page image on top of the current page; When the target user performs a page operation on the current page, the coordinate position corresponding to the page operation is captured through the page image; Based on the current page display time and the coordinate position, generate a behavior image corresponding to the target user; The step of selecting behavioral images that meet preset similarity conditions from multiple behavioral images corresponding to the target user as images to be fused, based on the similarity between these images, includes: Based on the size of each behavior image and the amount of page operation information contained in each behavior image, each behavior image is scaled to obtain scaled behavior images. Each of the scaled behavioral images is processed into grayscale to obtain multiple grayscale behavioral images corresponding to each of the scaled behavioral images; Based on the similarity between the various grayscale behavioral images, grayscale behavioral images that meet the preset similarity conditions are selected from the various grayscale behavioral images and used as images to be fused.

2. The method according to claim 1, characterized in that, Before selecting grayscale behavior images that meet preset similarity conditions from among the grayscale behavior images based on the similarity between them, the method further includes: Variance estimation is performed on each of the grayscale behavior images to obtain the variance features of each of the grayscale behavior images; The similarity between the grayscale behavioral images is obtained based on the distance between the variance features of each grayscale behavioral image.

3. The method according to claim 1, characterized in that, The step of generating a page image corresponding to the current page when the display time of the current page meets a preset time condition includes: Obtain the preset time threshold; If the display time of the current page exceeds the preset time threshold, the canvas is drawn on the current page to obtain the page image corresponding to the current page.

4. The method according to any one of claims 1 to 3, characterized in that, After fusing page operation information from multiple images to be fused to obtain the target behavior image corresponding to the target user, the process further includes: The target behavior images are visualized to obtain the visualized behavior data corresponding to each target behavior image, and the visualized behavior data is displayed. In response to a selection operation on the visualized behavioral data, the target coordinate position corresponding to the selection operation is obtained; Obtain and display all page operation information associated with the target coordinate location.

5. A behavioral data processing device, characterized in that, The device includes: The page image generation module is used to generate a page image corresponding to the current page when the display time of the current page meets a preset time condition. The page image is an image in an encoded format drawn according to the original scale of the current page. The behavior image acquisition module is used to collect the page operations of the target user on the current page through the page image, and obtain the behavior image corresponding to the target user; The behavior image filtering module is used to filter out behavior images that meet preset similarity conditions from multiple behavior images corresponding to the target user, based on the similarity between them, and use them as images to be fused. The page operation fusion module is used to fuse page operation information in multiple images to be fused to obtain the target behavior image corresponding to the target user; The page operation information refers to the operation data obtained by performing page operations on the page, and the target behavior image refers to the behavior image that integrates page operation information from multiple images to be integrated. The behavior image acquisition module is further configured to: Overlay the page image on top of the current page; When the target user performs a page operation on the current page, the coordinate position corresponding to the page operation is captured through the page image; Based on the current page display time and the coordinate position, generate a behavior image corresponding to the target user; The behavior image filtering module is further configured to scale each behavior image according to its size and the amount of page operation information contained therein, to obtain scaled behavior images; to perform grayscale processing on each scaled behavior image, to obtain multiple grayscale behavior images corresponding to each scaled behavior image; and to filter out grayscale behavior images that meet preset similarity conditions from among the grayscale behavior images based on the similarity between them, as images to be fused.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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