Interface display method and device, equipment, computer medium and product
By detecting user interaction behavior data and dynamically adjusting the interface style using a user group classification model, the problem of inconsistent user experience caused by static rules was solved, personalized interface display was achieved, and user satisfaction and interface efficiency were improved.
Patent Information
- Application Number
- CN202511770605.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-01-09
AI Technical Summary
In existing technologies, user interface styles rely on static rules, which cannot adapt to the diverse behavioral patterns of individual users, resulting in inconsistent user experiences and low satisfaction.
By detecting user interaction behavior data and using a user group classification model to identify task types and groups, the interface style is dynamically adjusted, including element weights, emotional states, and display attributes of interactive controls, to achieve personalized interface display.
It enables dynamic updates of the interface style based on user behavior, improving the consistency and satisfaction of the user experience, and enhancing the accuracy and efficiency of interface content presentation.
Smart Images
Figure CN121300902A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of interface display technology, and in particular relates to an interface display method, apparatus, device, computer storage medium and computer program product. Background Technology
[0002] In modern web and application design, user interface (UI) style is a key factor influencing user experience. Currently, most applications primarily determine the display style of the user interface through a pre-defined set of static rules. In this approach, developers predefine a fixed set of style rules, such as uniform font size, color scheme, layout structure, and other CSS properties. These static rules are loaded during application initialization and remain largely unchanged throughout the application's lifecycle, or can only be manually toggled in limited, discrete settings by the user.
[0003] However, the above-mentioned technical solutions that rely on static rules have significant defects and shortcomings: on the one hand, since static rules are pre-set and fixed, they cannot adapt to the diverse behavioral patterns of individual users; on the other hand, since the system cannot dynamically adjust the interface in real time according to the user's interaction behavior, the user's actual operating habits cannot receive positive feedback from the interface, resulting in inconsistent experiences among different users and reducing user satisfaction and usage efficiency.
[0004] Therefore, how to provide an interface display method that can meet users' personalized needs is an urgent problem to be solved. Summary of the Invention
[0005] This application provides an interface display method, apparatus, device, computer storage medium, and computer program product that can dynamically update the display interface based on user interaction behavior data.
[0006] In a first aspect, embodiments of this application provide an interface display method, the method comprising: In response to detecting user interaction on the interface, determine the user's interaction behavior data; The interactive behavior data is input into the task identification module of the user group classification model to obtain the task type corresponding to the interactive behavior data. The task type is input into the group classification module of the user group classification model to obtain the user group to which the user belongs; Determine the user's interface style based on the user group; Based on the interface style, update and display the interface.
[0007] In some possible implementations, determining the user's interface style based on the user group includes: Based on the interaction behavior data, determine the elements that the user is interested in and those that are not interested in; Determine the element weights of the elements on the interface based on the elements that the user is interested in and those that are not. The user's interface style is determined based on the element weights and the user group.
[0008] In some possible implementations, determining the user's interface style based on the element weights and the user group includes: If the element that the user is interested in is an image, the proportion of the interface area occupied by the display area of the image is determined based on the weight of the element. Based on the area ratio, determine the area of the interface occupied by the display area of the image; The user's interface style is determined based on the area of the interface occupied by the image display area and the user group.
[0009] In some possible implementations, determining the user's interface style based on the user group includes: The user's emotional state is determined based on the interactive behavior data; The user's interface style is determined based on the user's emotional state and the user group.
[0010] In some possible implementations, determining the user's emotional state based on the interaction behavior data includes: Based on the interactive behavior data, determine the duration information of interactive operations associated with the user's emotional state; If the duration information is less than a preset duration threshold, the user's emotional state is determined to be a positive emotional state. If the duration information is not less than a preset duration threshold, the user's emotional state is determined to be a negative emotional state.
[0011] In some possible implementations, determining the user's interface style based on the user's emotional state and the user group includes: Get the pixel data of the interface background image; The user's interface style is determined based on the pixel data of the interface background image, the user's emotional state, and the user group.
[0012] In some possible implementations, determining the user's interface style based on the pixel data of the interface background image, the user's emotional state, and the user group includes: When the user's emotional state is positive, the pixel data of the interface background image is adjusted to the first pixel data; Based on the first pixel data and the user group, the user's interface style is determined; When the user's emotional state is not positive, the pixel data of the interface background image is adjusted to the second pixel data, where the second pixel data is greater than the first pixel data. Based on the second pixel data and the user group, the user's interface style is determined.
[0013] In some possible implementations, determining the user's interface style based on the user's emotional state includes: When the user's emotional state is positive, the interface transition effect is set to the first animation effect, which is used to add animation to the interface transition. Based on the first animation effect and the user group, determine the user's interface style; When the user's emotional state is not positive, the interface switching effect is set to the second animation effect, which is used to add scaling animation to the interface interactive elements; Based on the second animation effect and the user group, the user's interface style is determined.
[0014] In some possible implementations, determining the user's interface style based on the user group includes: Based on the interactive behavior data, determine the usage frequency and weight of the interactive controls; The display attributes of the interactive controls are determined based on their usage frequency and weight. The user's interface style is determined based on the display attributes of the interactive controls and the user group.
[0015] Secondly, embodiments of this application provide an interface display device, the device comprising: The detection module is used to determine the user's interactive behavior data in response to the detection of user interaction on the interface. The input module is used to input the interactive operation behavior data into the task recognition module in the user group classification model to obtain the task type corresponding to the interactive operation behavior data. The input module is also used to input the task type into the group classification module in the user group classification model to obtain the user group to which the user belongs; The determination module is used to determine the user's interface style based on the user group; The update module is used to update the displayed interface based on the interface style.
[0016] Thirdly, embodiments of this application provide an interface display device, the device comprising: A processor and a memory storing computer program instructions; a method for displaying an interface that implements any of the above when the processor executes the computer program instructions.
[0017] Fourthly, embodiments of this application provide a computer storage medium on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the interface display method of any one of the above-mentioned methods is implemented.
[0018] Fifthly, embodiments of this application provide a computer program product, wherein when the instructions in the computer program product are executed by the processor of an electronic device, the electronic device is able to execute any of the above-mentioned interface display methods.
[0019] The interface display method, apparatus, device, computer storage medium, and computer program product of this application embodiment first determine the user's interactive behavior data based on the user's interactive operations on the interface when displaying the interface; then, the interactive behavior data is input into the task identification module in the user group classification model to obtain the task type corresponding to the interactive behavior data; the task type is input into the group classification module in the user group classification model to obtain the user group to which the user belongs; then, the user's interface style is determined based on the user group; finally, the display interface is updated based on the interface style. This method fully considers the interactive behavior data corresponding to the user's interactive operations on the interface when determining the interface style, and obtains the user group to which the user belongs through the task identification module and the group classification module in the user group classification model. The task identification module analyzes the inherent purpose of the interactive behavior to ensure that subsequent style adjustments are highly relevant to the user's current actual task. The group classification module performs fine-grained grouping based on task type, so that users within the same group have highly consistent task goals and behavior patterns, thus providing a reliable basis for accurate personalized interface styles. Furthermore, it makes the interface style determined based on the user group more in line with the user's personalized needs, achieving the effect of dynamically updating the display interface based on the user's interactive behavior data. Attached Figure Description
[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0021] Figure 1 This is a flowchart illustrating an embodiment of the interface display method provided in this application; Figure 2 This is a schematic flowchart of S140 provided in one embodiment of this application; Figure 3 This is a schematic diagram of the interface display device provided in another embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application. Detailed Implementation
[0022] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.
[0023] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.
[0024] It should be noted that the acquisition, storage, use, and processing of data in this application embodiment all comply with the relevant provisions of national laws and regulations.
[0025] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used the solution.
[0026] In modern web and application design, user interface (UI) style is a key factor influencing user experience. Currently, most applications primarily determine the display style of the user interface through a pre-defined set of static rules. In this approach, developers predefine a fixed set of style rules, such as uniform font size, color scheme, layout structure, and other CSS properties. These static rules are loaded during application initialization and remain largely unchanged throughout the application's lifecycle, or can only be manually toggled in limited, discrete settings by the user.
[0027] However, the above-mentioned technical solutions that rely on static rules have significant defects and shortcomings: on the one hand, since static rules are pre-set and fixed, they cannot adapt to the diverse behavioral patterns of individual users; on the other hand, since the system cannot dynamically adjust the interface in real time according to the user's interaction behavior, the user's actual operating habits cannot receive positive feedback from the interface, resulting in inconsistent experiences among different users and reducing user satisfaction and usage efficiency.
[0028] To address the problems of the prior art, embodiments of the present invention provide an interface display method, apparatus, device, and computer storage medium.
[0029] The interface display method provided in the embodiments of the present invention will be described below first.
[0030] Figure 1 A flowchart illustrating an embodiment of the interface display method provided by the present invention is shown. Figure 1 As shown, the method may include the following steps: S110. In response to detecting user interaction on the interface, determine user interaction behavior data.
[0031] For example, user interactions on the interface can include button clicks, page scrolling, image viewing, etc. The corresponding user interaction data can include the location of click events, the speed and direction of page scrolling, the time the user spends on each page, and the order and path the user browses pages. In practice, user interaction data can be collected using front-end tracking technology.
[0032] It's important to note that raw user interaction data collected through front-end tracking may contain noise and missing values. Therefore, preprocessing is necessary. For example, missing values can be filled using the mean or nearest neighbor methods; outliers can be detected and removed by setting reasonable thresholds. Preprocessing makes user interaction data more accurate and facilitates subsequent data analysis.
[0033] S120. Input the interactive operation behavior data into the task identification module in the user group classification model to obtain the task type corresponding to the interactive operation behavior data.
[0034] For example, the task recognition module can be implemented using a classification neural network (such as a CNN or RNN). The task recognition module can analyze the behavioral sequences of interactive operation data to output the task type. For instance, if the user's interactive operation data is "quickly click on multiple images - pause briefly - scroll quickly again," the task recognition module could output a task type of "image browsing task." Similarly, if the user's interactive operation data is "pause on text content for a long time," the task recognition module could output a task type of "text reading task."
[0035] S130. Input the task type into the group classification module in the user group classification model to obtain the user group to which the user belongs.
[0036] For example, the group classification module can be trained using a clustering algorithm, such as K-Means clustering. This algorithm matches the most similar group features based on task type, thus assigning users to corresponding user groups. For instance, if a user's task type is "image browsing," their corresponding user group could be the "visual browsing group." Similarly, if a user's task type is "text reading," their corresponding user group could be the "text reading group," which focuses more on text readability.
[0037] S140. Determine the user interface style based on the user group.
[0038] For example, when determining the user interface style based on a user group, a predefined interface style rule library can be queried based on the user group. The interface style matching the user group can then be determined according to the mapping relationship between user groups and interface styles. For instance, for a user group called "visual browsing group," the user's interface style requirement might be to prioritize enlarging the image display area. Correspondingly, the user's interface requirement would also be to prioritize enlarging the image display area.
[0039] S150: Update the display interface based on the interface style.
[0040] After determining the desired interface style for the user, the current interface can be updated accordingly. For example, if the user requests a larger image display area, the image display area can be enlarged to update the interface.
[0041] In some embodiments, such as Figure 2 As shown, S140 may include: S1401. Based on the interaction behavior data, determine the elements that the user is interested in and those that are not interested in; S1402. Determine the element weights of the elements on the interface based on the elements that the user is interested in and those that are not. S1403. Determine the user interface style based on element weights and user groups.
[0042] For example, user interaction behavior data can reflect the elements that users are interested in and those that are not. When determining whether an interface element is an element that the user is interested in, the user's click frequency can be compared with a preset threshold (such as 5 times per minute, the threshold is set in a configuration file or database). When the user's click frequency exceeds the preset threshold, it proves that the interface element is an element that the user is interested in.
[0043] For example, if user interaction data shows "long dwell time on text content," it indicates that the user is interested in text. When text is the element of interest, the importance weight of text elements is greater than that of image elements. Additionally, font size adjustment factors can be used to adjust the font size. Furthermore, if the user group prefers looser layouts, the line spacing can also be adjusted.
[0044] For example, user interaction data showing "quickly click on multiple images - pause briefly - scroll quickly again" indicates that the user is interested in images. Elements that the user is interested in have a higher weight than elements that are not interested in. When the element of interest is an image, the importance weight of the image element is greater than the importance weight of the text element.
[0045] By automatically identifying and quantifying users' interest in different elements from user behavior data, on the one hand, it can transcend uniform static layouts and achieve priority sorting and differentiated configuration of interface elements; on the other hand, by combining "element weights" that represent individual preferences with "user groups" that reflect group characteristics to determine the final style, the generated interface not only conforms to the general operating paradigm of the user group, but also accurately adapts to the unique focus of the current user, achieving a precise integration of personalized preferences and group commonalities.
[0046] For example, the element that the user is interested in may be an image. In some embodiments, when determining the user's interface style based on element weight and user group, the proportion of the interface area occupied by the image display area may be determined based on the element weight; the area of the interface occupied by the image display area may be determined based on the area proportion; and the user's interface style may be determined based on the area of the interface occupied by the image display area and the user group.
[0047] When the user is interested in an image, the proportion of the image's area on the screen can be adjusted according to the image's element weight. For example, the proportion of the image's area can be dynamically increased from the initial proportion to a larger proportion than the initial proportion, while the area of elements that the user is not interested in can be reduced, making the interface layout more in line with the user's actual focus.
[0048] By transforming abstract user interests (element weights) into precise interface layout parameters (image area ratio and specific area), a precise quantitative match between interface content presentation and user subjective preferences is achieved. Simultaneously, by dynamically reconstructing the page layout, the display area of high-attention images is automatically enlarged while the space ratio of low-weight elements is reduced, thereby significantly improving screen space utilization efficiency and ensuring that user attention is prioritized for the content they are most interested in.
[0049] To further improve the relevance of the interface style to the user, in some embodiments, S140 may further include: Determine the user's emotional state based on interaction behavior data; The user interface style is determined based on the user's emotional state and user group.
[0050] For example, a user's emotional state may include a positive emotional state and a negative emotional state. When determining a user's emotional state based on interaction behavior data, the duration information of the interaction operation associated with the user's emotional state can be determined based on the interaction behavior data. If the duration information is less than a preset duration threshold, the user's emotional state is determined to be a positive emotional state. If the duration information is not less than the preset duration threshold, the user's emotional state is determined to be a negative emotional state.
[0051] A user's emotional state can be determined based on the duration of interactive operations associated with that emotional state, such as the user's operation speed (e.g., average click interval) and dwell time. If the average dwell time is less than a preset duration threshold, for example, a threshold of 2 seconds, the user's emotional state is determined to be "positive / eager". If the average dwell time is not less than the preset duration threshold, the user's emotional state is determined to be "negative / hesitant".
[0052] By using user interaction time data as a quantitative basis for judging emotional state, this method achieves efficient and low-cost identification of users' subjective emotions, transforms abstract "emotions" into calculable "duration information," and achieves rapid and automated classification of emotional states (positive / negative) by comparing them with preset thresholds. This provides a reliable and operable emotional data foundation for subsequent personalized interface adaptation.
[0053] In some embodiments, when determining the user's interface style based on the user's emotional state and user group, pixel data of the interface background image can be obtained; the user's interface style is determined based on the pixel data of the interface background image, the user's emotional state, and the user group.
[0054] For example, the pixel data of the interface background image can be the color saturation and brightness of the image. When determining the user's interface style based on the pixel data of the interface background image, the user's emotional state, and the user group, if the user's emotional state is positive, the pixel data of the interface background image can be adjusted to the first pixel data; the user's interface style is determined based on the first pixel data and the user group; if the user's emotional state is negative, the pixel data of the interface background image can be adjusted to the second pixel data, where the second pixel data is greater than the first pixel data; the user's interface style is determined based on the second pixel data and the user group.
[0055] By dynamically linking the user's emotional state with the underlying pixel data of the interface background, a precise match between visual style and the user's psychological state is achieved. When the user is in a positive mood, the first pixel data, which has a smaller amount of data, is used to achieve a brighter and more cheerful visual style, matching the user's efficient and pleasant mood. When the user is in a negative mood, the second pixel data, which has a larger amount of data, is used to present more complex, deeper, or softer visual details, in order to soothe emotions or stimulate interest. This transforms the interface background from a static decoration into a dynamic interactive element that can adapt to the user's emotional state, greatly enhancing the emotional expressiveness and empathy of the interface.
[0056] In some embodiments, when determining the user's interface style based on the user's emotional state, animation effects can also be set. When the user's emotional state is positive, the interface transition effect is set to a first animation effect, which adds animation to the interface transition; the user's interface style is determined based on the first animation effect and the user group. When the user's emotional state is negative, the interface transition effect is set to a second animation effect, which adds scaling animation to the interface interactive elements; the user's interface style is determined based on the second animation effect and the user group.
[0057] For example, when the user's emotional state is "positive / eager," a fast and smooth fade-in animation (the first animation effect) can be chosen as the page transition effect. Conversely, when the user's emotional state is "negative / hesitant," a scaling animation can be added to the element interaction.
[0058] By dynamically associating user emotional states with specific types of interface animation effects, a deep emotional dimension to interactive feedback is achieved. When users are in a positive mood, a first animation effect (such as fade-in / fade-out) is applied to global interface transitions, creating a smooth, consistent, and pleasant experience that aligns with the user's efficient operation. When users are in a negative mood, a second animation effect (such as pulse scaling) is added to interactive elements, attracting and focusing user attention through localized, guiding dynamic feedback, attempting to reignite their interest in interaction. Through differentiated animation strategies, the dynamic performance of the interface becomes a communication language that understands the user's mood and responds intelligently, significantly enhancing the naturalness and emotional resonance of the interaction.
[0059] To further enhance the user's interactive experience, in some embodiments, S140 may further include: Based on the interaction behavior data, determine the usage frequency and weight of interactive controls; The display attributes of interactive controls are determined based on their usage frequency and weight. Determine the user interface style based on the display properties of interactive controls and the user group.
[0060] For example, the frequency of use and weight of an interactive control are used to indicate the importance of the interactive control to the user. Based on this importance, the display properties of the interactive control can be adjusted. The display properties of the interactive control can be, for example, the size, color, and shape of the interactive control.
[0061] By quantifying the actual usage frequency and importance (weight) of user interaction controls (such as buttons and icons), and dynamically adjusting their display attributes (such as size, color, and position) accordingly, intelligent and personalized layout of interface functional elements is achieved. This not only automatically highlights high-frequency, high-weight core controls, making them more eye-catching and easier to operate, but also weakens or simplifies low-frequency controls, thereby significantly optimizing the visual hierarchy and operation path of the interface. This allows users to locate and trigger frequently used functions more quickly, greatly improving interaction efficiency and user experience.
[0062] In some embodiments, the user group classification model can be trained in the following manner: Obtain the training sample set. The training dataset includes multiple training samples, each of which includes interactive behavior data samples and their corresponding user group labels. Input the interactive behavior data samples into the initial user group classification model to generate the initial user group; Based on the initial user groups and user group labels, determine the loss function of the initial user group classification model; If the loss function value does not meet the preset training stopping condition, update the model parameters of the initial user group classification model according to the loss function value, and return to input the interaction behavior data samples into the initial user group classification model to generate the initial user group.
[0063] In some embodiments, training samples can be obtained in the following manner: In response to the detection of user interaction on the interface, determine the interaction behavior data of multiple users; The task identification module identifies the task types corresponding to the interactive behavior data of multiple users. Based on task type, a preset clustering algorithm is used to cluster the interactive behavior data of multiple users to obtain multiple user groups; The interaction behavior data of each user is associated with its corresponding user group to obtain training samples.
[0064] For example, the preset clustering algorithm can be the K-Means clustering algorithm. K-Means clustering is a distance-based unsupervised learning algorithm whose goal is to divide a given dataset into K distinct clusters, such that data points within the same cluster have high similarity (close proximity), while data points between different clusters have significant differences (far distance). In this embodiment, users with similar behavioral patterns are grouped into different groups, each group representing a typical user behavior type.
[0065] In some embodiments, a preset clustering algorithm is used to cluster the interaction behavior data of multiple users to obtain multiple user groups, which may include: Obtain multiple preset first cluster centers, which are used to represent the typical feature vectors of each user group; Convert user interaction behavior into a user interaction behavior feature vector; Compare the distance between typical feature vectors and user interaction behavior feature vectors; If the distance between the typical feature vector and the user interaction behavior feature vector is less than a preset threshold, the user interaction behavior feature vector will be assigned to the corresponding first cluster center. Multiple second cluster centers are determined, which are used to represent the mean feature vector corresponding to each user group; The mean feature vector is updated to a typical feature vector, and the distance between the typical feature vector and the user interaction behavior feature vector is returned. This process continues until the cluster centers remain unchanged, resulting in multiple target cluster centers that can be used as multiple user groups. For example, users who frequently scroll quickly and click on images can be grouped into one group, while users who prefer to read text carefully and spend more time on the page can be grouped into another.
[0066] In practice, firstly, K cluster centers are randomly initialized, which can be considered as representative points of each cluster. Then, for each user behavior data point in the dataset (using click count, scroll distance, dwell time, etc. as feature vectors), the Euclidean distance between it and each cluster center is calculated. Based on the principle of minimum distance, each data point is assigned to the cluster containing the nearest cluster center. The new cluster centers for each cluster are recalculated; these new cluster centers are typically the mean vector of all data points within that cluster. These steps are repeated until the cluster centers no longer change significantly (convergence). At this point, the final user behavior clustering result is obtained, representing different user groups. Users with similar behavioral patterns are grouped into different groups, each group representing a typical user behavior type. For example, users who frequently scroll quickly and click on images are grouped into one category, while users who prefer to carefully read text and spend longer periods of time on the page are grouped into another.
[0067] The interface display method, apparatus, device, computer storage medium, and computer program product of this application embodiment first determine the user's interactive behavior data based on the user's interactive operations on the interface when displaying the interface; then, the interactive behavior data is input into the task identification module in the user group classification model to obtain the task type corresponding to the interactive behavior data; the task type is input into the group classification module in the user group classification model to obtain the user group to which the user belongs; then, the user's interface style is determined based on the user group; finally, the display interface is updated based on the interface style. This method fully considers the interactive behavior data corresponding to the user's interactive operations on the interface when determining the interface style, and obtains the user group to which the user belongs through the task identification module and the group classification module in the user group classification model. The task identification module analyzes the inherent purpose of the interactive behavior to ensure that subsequent style adjustments are highly relevant to the user's current actual task. The group classification module performs fine-grained grouping based on task type, so that users within the same group have highly consistent task goals and behavior patterns, thus providing a reliable basis for accurate personalized interface styles. Furthermore, it makes the interface style determined based on the user group more in line with the user's personalized needs, achieving the effect of dynamically updating the display interface based on the user's interactive behavior data.
[0068] Based on the interface display method provided in the above embodiments, this application also provides specific implementation methods of the interface display device. Please refer to the following embodiments.
[0069] First see Figure 3 The interface display device 300 provided in this application embodiment includes: The detection module 310 is used to determine the user's interactive behavior data in response to the detection of user interaction on the interface. The input module 320 is used to input interactive operation behavior data into the task recognition module in the user group classification model to obtain the task type corresponding to the interactive operation behavior data. The input module 330 is also used to input the task type into the group classification module in the user group classification model to obtain the user group to which the user belongs; Module 340 is used to determine the user interface style based on the user group; Update module 350, used to update the display interface based on the interface style.
[0070] In some possible implementations, module 340 is also used for: Based on interaction behavior data, determine the elements that the user is interested in and those that are not interested in; Determine the element weights of the elements on the interface based on the elements that the user is interested in and those that are not. The user interface style is determined based on element weights and user groups.
[0071] In some possible implementations, the user interface style is determined based on element weights and user groups, including: When the element that the user is interested in is an image, the proportion of the screen area occupied by the image display area is determined based on the element weight. Based on the area ratio, determine the area of the interface occupied by the image display area; The user interface style is determined based on the area of the image display area and the user group.
[0072] In some possible implementations, module 340 is also used for: Determine the user's emotional state based on interaction behavior data; The user interface style is determined based on the user's emotional state and user group.
[0073] In some possible implementations, the user's emotional state is determined based on interaction behavior data, including: Based on interactive behavior data, determine the duration information of interactive operations that are associated with the user's emotional state; If the duration information is less than a preset duration threshold, the user's emotional state is determined to be a positive emotional state; If the duration information is not less than a preset duration threshold, the user's emotional state is determined to be a non-positive emotional state.
[0074] In some possible implementations, the user interface style is determined based on the user's emotional state and user group, including: Get the pixel data of the interface background image; The user interface style is determined based on the pixel data of the background image, the user's emotional state, and the user group.
[0075] In some possible implementations, the user's interface style is determined based on the pixel data of the interface background image, the user's emotional state, and the user group, including: When the user's emotional state is positive, adjust the pixel data of the interface background image to the first pixel data; Based on the first pixel data and the user group, determine the user's interface style; When the user's emotional state is not positive, adjust the pixel data of the interface background image to the second pixel data, which is greater than the first pixel data; Based on the second pixel data and the user group, the user's interface style is determined.
[0076] In some possible implementations, the user interface style is determined based on the user's emotional state, including: When the user's emotional state is positive, the interface transition effect is set to the first animation effect, which is used to add animation to the interface transition. Based on the first animation effect and the user group, determine the user's interface style; When the user's emotional state is not positive, the interface transition effect is set to the second animation effect, which is used to add scaling animation to the interface interactive elements; Based on the second animation effect and the user group, determine the user's interface style.
[0077] In some possible implementations, module 340 is also used for: Based on the interaction behavior data, determine the usage frequency and weight of interactive controls; The display attributes of interactive controls are determined based on their usage frequency and weight. Determine the user interface style based on the display properties of interactive controls and the user group.
[0078] The various modules of the interface display device provided in this application embodiment can achieve Figure 1 It provides the functionality for each step of the interface display method and achieves the corresponding technical effects. For the sake of brevity, it will not be elaborated here.
[0079] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.
[0080] The electronic device 400 may include a processor 401 and a memory 402 storing computer program instructions.
[0081] Specifically, the processor 401 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.
[0082] Memory 402 may include mass storage for data or instructions. For example, and not limitingly, memory 402 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 402 may include removable or non-removable (or fixed) media. Where appropriate, memory 402 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 402 is non-volatile solid-state memory.
[0083] In certain embodiments, the memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this application.
[0084] The processor 401 reads and executes computer program instructions stored in the memory 402 to implement any of the interface display methods in the above embodiments.
[0085] In some examples, electronic device 400 may also include a communication interface 403 and a bus 404. For example, Figure 4 As shown, the processor 401, memory 402, and communication interface 403 are connected through bus 404 and complete communication with each other.
[0086] The communication interface 403 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.
[0087] Bus 404 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not as a limitation, bus 404 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 404 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.
[0088] For example, the electronic device 400 can be a mobile phone, tablet computer, laptop computer, handheld computer, in-vehicle electronic device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc.
[0089] The electronic device 400 can execute the interface display method in the embodiments of this application, thereby achieving the combination Figure 1 The described interface display method.
[0090] In addition, in conjunction with the interface display methods in the above embodiments, this application also provides a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the interface display methods in the above embodiments. Examples of computer-readable storage media include non-transitory computer-readable storage media, such as portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, etc.
[0091] This application also provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, they implement any of the interface display methods described in the above embodiments.
[0092] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.
[0093] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.
[0094] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.
Claims
1. A method for displaying an interface, characterized in that, include: In response to detecting user interaction on the interface, determine the user's interaction behavior data; The interactive behavior data is input into the task identification module of the user group classification model to obtain the task type corresponding to the interactive behavior data. The task type is input into the group classification module of the user group classification model to obtain the user group to which the user belongs; Determine the user's interface style based on the user group; Based on the interface style, update and display the interface.
2. The interface display method according to claim 1, characterized in that, Determining the user's interface style based on the user group includes: Based on the interaction behavior data, determine the elements that the user is interested in and those that are not interested in; Determine the element weights of the elements on the interface based on the elements that the user is interested in and those that are not. The user's interface style is determined based on the element weights and the user group.
3. The interface display method according to claim 2, characterized in that, Determining the user's interface style based on the element weights and the user group includes: If the element that the user is interested in is an image, the proportion of the interface area occupied by the display area of the image is determined based on the weight of the element. Based on the area ratio, determine the area of the interface occupied by the display area of the image; The user's interface style is determined based on the area of the interface occupied by the image display area and the user group.
4. The interface display method according to claim 1, characterized in that, Determining the user's interface style based on the user group includes: The user's emotional state is determined based on the interactive behavior data; The user's interface style is determined based on the user's emotional state and the user group.
5. The interface display method according to claim 4, characterized in that, Determining the user's emotional state based on the interaction behavior data includes: Based on the interactive behavior data, determine the duration information of interactive operations associated with the user's emotional state; If the duration information is less than a preset duration threshold, the user's emotional state is determined to be a positive emotional state. If the duration information is not less than a preset duration threshold, the user's emotional state is determined to be a negative emotional state.
6. The interface display method according to claim 4 or 5, characterized in that, Determining the user's interface style based on the user's emotional state and the user group includes: Get the pixel data of the interface background image; The user's interface style is determined based on the pixel data of the interface background image, the user's emotional state, and the user group.
7. The interface display method according to claim 6, characterized in that, The step of determining the user's interface style based on the pixel data of the interface background image, the user's emotional state, and the user group includes: When the user's emotional state is positive, the pixel data of the interface background image is adjusted to the first pixel data; Based on the first pixel data and the user group, the user's interface style is determined; When the user's emotional state is not positive, the pixel data of the interface background image is adjusted to the second pixel data, where the second pixel data is greater than the first pixel data. Based on the second pixel data and the user group, the user's interface style is determined.
8. The interface display method according to claim 4, characterized in that, Determining the user's interface style based on the user's emotional state includes: When the user's emotional state is positive, the interface transition effect is set to the first animation effect, which is used to add animation to the interface transition. Based on the first animation effect and the user group, determine the user's interface style; When the user's emotional state is not positive, the interface switching effect is set to the second animation effect, which is used to add scaling animation to the interface interactive elements; Based on the second animation effect and the user group, the user's interface style is determined.
9. The interface display method according to claim 1, characterized in that, Determining the user's interface style based on the user group includes: Based on the interactive behavior data, determine the usage frequency and weight of the interactive controls; The display attributes of the interactive controls are determined based on their usage frequency and weight. The user's interface style is determined based on the display attributes of the interactive controls and the user group.
10. An interface display device, characterized in that, The device includes: The detection module is used to determine the user's interactive behavior data in response to the detection of user interaction on the interface. The input module is used to input the interactive operation behavior data into the task recognition module in the user group classification model to obtain the task type corresponding to the interactive operation behavior data. The input module is also used to input the task type into the group classification module in the user group classification model to obtain the user group to which the user belongs; The determination module is used to determine the user's interface style based on the user group; The update module is used to update the displayed interface based on the interface style.
11. An interface display device, characterized in that, The device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the interface display method as described in any one of claims 1-9.
12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the interface display method as described in any one of claims 1-9.
13. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device is able to perform the interface display method as described in any one of claims 1-9.