Method, device, medium and electronic device for updating interactive content display mode

Abstract

The present disclosure provides a method for updating an interactive content display mode, an apparatus for updating an interactive content display mode, a computer-readable medium, and an electronic device, and relates to the field of computer technology. The method includes: collecting user behavior data from each application of the same category; determining the user preference weights and interactive content offsets corresponding to each type of interactive content in the application of the same category based on the user behavior data; updating the display mode of each type of interactive content in the target application based on the user preference weights and interactive content offsets; wherein the application of the same category includes the target application. The method for updating the interactive content display mode in the present disclosure can overcome the problem of low shopping convenience to a certain extent, and improve the user's shopping convenience and user experience by personalizing and updating the interactive content display mode for the user.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method for updating an interactive content display mode, an apparatus for updating an interactive content display mode, a computer-readable medium, and an electronic device. Background Art

[0002] With the continuous development and innovation of major e-commerce platforms, people are shopping online more and more conveniently, which can not only change users' shopping habits through technology but also drive economic development. Generally speaking, users usually shop in two ways: online and offline. Offline, users can choose physical stores of different sizes according to their shopping needs. Online, users can enter the shopping software and place orders through different interactive contents such as searching for goods or finding the required goods according to categories or finding the required goods according to favorites. It can be seen that different users may have different online shopping methods, and the complexity of different shopping methods may also be different. Therefore, for users who prefer to use a certain type of more complex online shopping method, there will be a problem of low shopping convenience.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0004] The purpose of the present disclosure is to provide a method for updating an interactive content display method, an apparatus for updating an interactive content display method, a computer-readable medium, and an electronic device, which can at least to some extent overcome the problem of low shopping convenience, and improve the shopping convenience and user experience of users by personalizing and updating the interactive content display method for users.

[0005] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0006] A first aspect of the present disclosure provides a method for updating an interactive content display mode, comprising:

[0007] Collect user behavior data from various applications of the same category;

[0008] Determine the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of applications based on user behavior data;

[0009] The display mode of each type of interactive content in the target application is updated according to the user preference weight and the interactive content offset; wherein the target application is included in the applications of the same category.

[0010] In an exemplary embodiment of the present disclosure, collecting user behavior data in various applications of the same category includes:

[0011] Determine globally all applications including navigation functions as applications of the same category; wherein the navigation functions include at least one of object search, object classification, recommended information, and user collection;

[0012] Collect user behavior data for applications that use the system application programming interface among applications of the same category;

[0013] Perform user interface acquisition for applications that use custom application programming interfaces in the same category of applications.

[0014] In an exemplary embodiment of the present disclosure, user behavior data collection is performed on applications using a system application programming interface among applications of the same category, including:

[0015] Perform data analysis on the interface elements of applications that use the system application programming interface among applications in the same category;

[0016] The data analysis results are filtered according to preset rules and stored as user behavior data.

[0017] In an exemplary embodiment of the present disclosure, determining the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of applications according to user behavior data includes:

[0018] Input the sample data into the prediction model to calculate the loss function between the prediction result output by the prediction model and the result corresponding to the sample, and update the parameters of the prediction model according to the loss function;

[0019] The user behavior data is input into the prediction model with updated parameters, and the user preference weights and interaction content offsets corresponding to various types of interaction content in the same category of applications are determined through the prediction model with updated parameters.

[0020] In an exemplary embodiment of the present disclosure, the method for updating the interactive content display mode further includes:

[0021] If there are target interaction contents with the same user preference weight, then determining the target interaction content offsets corresponding to the target interaction contents respectively;

[0022] Prioritize the same user preference weights in order from low to high according to the target interaction content offset;

[0023] All user preference weights are prioritized according to the priority ranking results of the same user preference weights.

[0024] In an exemplary embodiment of the present disclosure, updating the display mode of various types of interactive content in the target application according to the user preference weight and the interactive content offset includes:

[0025] Determine the target user preference weights that are above a preset threshold in the priority ranking results of the user preference weights;

[0026] The display mode of various interactive contents in the target application is updated according to the target user preference weight and the interactive content offset corresponding to the target user preference weight.

[0027] In an exemplary embodiment of the present disclosure, updating the display mode of various types of interactive content in the target application according to the target user preference weight and the interactive content offset corresponding to the target user preference weight includes:

[0028] The interactive content that is not displayed at the first level in the target application corresponding to the target user's preference weight is displayed at the first level according to the interactive content offset corresponding to the target user's preference weight;

[0029] Adjust the display method of other interactive contents in the target application according to the first-level display result.

[0030] According to a second aspect of the present disclosure, a device for updating an interactive content display mode is provided, the device comprising a data collection unit, a weight determination unit, and a display mode updating unit, wherein:

[0031] A data collection unit, used to collect user behavior data from various applications of the same category;

[0032] A weight determination unit, used to determine user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of application programs according to user behavior data;

[0033] The display mode updating unit is used to update the display mode of various interactive contents in the target application according to the user preference weight and the interactive content offset; wherein the target application is included in the applications of the same category.

[0034] In an exemplary embodiment of the present disclosure, the data collection unit may collect user behavior data in various applications of the same category in the following manner:

[0035] The data collection unit globally determines each application program including a navigation function as an application program of the same category; wherein the navigation function includes at least one of object search, object classification, recommended information, and user collection;

[0036] The data collection unit collects user behavior data from applications using the system application programming interface among applications of the same category;

[0037] The data collection unit collects user interfaces of application programs that use a custom application programming interface among application programs of the same category.

[0038] In an exemplary embodiment of the present disclosure, the data collection unit collects user behavior data from applications using the system application programming interface among applications of the same category in a specific manner as follows:

[0039] The data collection unit performs data analysis on interface elements of applications using the system application programming interface in applications of the same category;

[0040] The data collection unit filters the data analysis results according to preset rules and stores the filtered results as user behavior data.

[0041] In an exemplary embodiment of the present disclosure, the weight determination unit determines the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of application programs according to the user behavior data in the following manner:

[0042] The weight determination unit inputs the sample data into the prediction model to calculate the loss function between the prediction result output by the prediction model and the result corresponding to the sample, and updates the parameters of the prediction model according to the loss function;

[0043] The weight determination unit inputs the user behavior data into the prediction model with updated parameters, and determines the user preference weights and interaction content offsets corresponding to various types of interaction content in the same category of application programs through the prediction model with updated parameters.

[0044] In an exemplary embodiment of the present disclosure, the apparatus for updating the interactive content display mode may further include an interactive content offset determination unit and a priority sorting unit, wherein:

[0045] An interactive content offset determination unit, used to determine the target interactive content offsets corresponding to the target interactive contents respectively when there are target interactive contents with the same user preference weight;

[0046] A priority sorting unit, used to prioritize the same user preference weights in order of target interactive content offset from low to high;

[0047] The priority sorting unit is further used to prioritize all user preference weights according to the priority sorting results of the same user preference weights.

[0048] In an exemplary embodiment of the present disclosure, the display mode updating unit updates the display modes of various interactive contents in the target application according to the user preference weight and the interactive content offset in a specific manner as follows:

[0049] The display mode updating unit determines a target user preference weight that is higher than a preset threshold value in the priority sorting result of the user preference weights;

[0050] The display mode updating unit updates the display modes of various interactive contents in the target application according to the target user preference weight and the interactive content offset corresponding to the target user preference weight.

[0051] In an exemplary embodiment of the present disclosure, the display mode updating unit updates the display modes of various interactive contents in the target application according to the target user preference weight and the interactive content offset corresponding to the target user preference weight in a specific manner as follows:

[0052] The display mode updating unit displays the interactive content in the target application corresponding to the target user preference weight in a first-level manner according to the interactive content offset corresponding to the target user preference weight;

[0053] The display mode updating unit adjusts the display mode of other interactive contents in the target application according to the primary display result.

[0054] According to a third aspect of the present disclosure, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for updating the interactive content display mode as described in the first aspect of the above embodiment is implemented.

[0055] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, which, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the method for updating the interactive content display method as described in the first aspect of the above embodiment.

[0056] The technical solution provided by the present disclosure may have the following beneficial effects:

[0057] In the technical solution provided in the embodiments of the present disclosure, user behavior data in various applications of the same category (such as applications for online shopping) can be collected; then, user preference weights and interactive content offsets corresponding to various types of interactive content (such as object search, photo recognition, etc.) in applications of the same category can be determined based on the user behavior data; then, the display methods of various types of interactive content in the target application can be updated based on the user preference weights and interactive content offsets; wherein the target application is included in the applications of the same category. According to the above-mentioned solution description, on the one hand, the present disclosure can overcome the problem of low shopping convenience to a certain extent, and improve the user's shopping convenience and user experience by personalizing and updating the interactive content display method for users; on the other hand, it can personalize the application according to the preferences of different users to improve the user's usage stickiness.

[0058] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0060] Figure 1 A schematic diagram showing a flow chart of a method for updating an interactive content display mode according to an exemplary embodiment of the present disclosure;

[0061] Figure 2 A schematic diagram of a process for collecting user behavior data of various applications of the same category according to an exemplary embodiment of the present disclosure is shown;

[0062] Figure 3 A flow chart showing another method for updating an interactive content display mode according to an exemplary embodiment of the present disclosure is shown;

[0063] Figure 4 A structural block diagram of an apparatus for updating an interactive content display mode according to an exemplary embodiment of the present disclosure is shown;

[0064] Figure 5 A schematic diagram showing an exemplary system architecture of a method for updating an interactive content display mode and an apparatus for updating an interactive content display mode to which the embodiments of the present disclosure can be applied;

[0065] Figure 6A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0066] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more comprehensive and complete and will fully convey the concept of the example embodiments to those skilled in the art.

[0067] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0068] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0069] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0070] See also Figure 1 , Figure 1 A flow chart of a method for updating an interactive content display mode according to an exemplary embodiment of the present disclosure is shown. The method for updating the interactive content display mode can be implemented by a server or a terminal device.

[0071] like Figure 1 As shown, according to an embodiment of the present disclosure, a method for updating an interactive content display mode includes the following steps S110, S120, and S130, wherein:

[0072] Step S110: Collect user behavior data from each application of the same category.

[0073] Step S120: Determine the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of application programs based on the user behavior data.

[0074] Step S130: updating the display mode of each type of interactive content in the target application according to the user preference weight and the interactive content offset; wherein the target application is included in the applications of the same category.

[0075] The following is a detailed description of each step:

[0076] In step S110, user behavior data of each application of the same category is collected.

[0077] In this example implementation, applications of the same category are used to represent applications of the same category in a terminal device used by a user; the category may be shopping, games, travel, ticket purchase, or social networking, etc., which is not limited in the embodiments of the present disclosure.

[0078] In the present example implementation, collecting user behavior data in each application of the same category can be understood as collecting user behavior data in all applications in one category (e.g., shopping program A, shopping program B, and shopping program C), or can be understood as collecting user behavior data in all applications in each category (e.g., shopping program A, shopping program B, shopping program C, ticket purchasing program A, ticket purchasing program B, and ticket purchasing program C), which is not limited to the embodiments of the present disclosure.

[0079] In this example implementation, user behavior data may include user search behavior, user click-through hierarchical selection from product categories to determine desired products, user click-through favorites to determine desired products from favorites, and user click-through product recommendations to determine desired products, etc., which are not limited to the embodiments of the present disclosure.

[0080] In this example implementation, optionally, the method of collecting user behavior data in each application of the same category may specifically be:

[0081] When a mobile terminal used by a user sends a webpage request of an application of the same category to a server, receiving a log file sent by the server including at least one of an IP address, a login name, a date of sending the request, an event of sending the request, a request method, a webpage protocol, and a return status, and performing data analysis on the log file to obtain user behavior data; or,

[0082] Obtain user access records in various applications of the same category, and obtain user behavior data based on the user access records; or,

[0083] The user requests are collected through the sniffer, and the data corresponding to the user requests are sent to the data collection and processing server, so as to perform data analysis through the data collection and processing server, and then obtain the user behavior data. Among them, the sniffer can obtain the data packets flowing through the network.

[0084] In this example implementation, optionally, before step S110, the server may send the navigation model saved by tf.train.Saver() in the save module (save module) to the client in the .cpkt file format, and the client executes step S110 after initializing the navigation model. Among them, the way in which the client initializes the navigation model may include setting model parameters in the navigation model according to the configuration corresponding to the terminal device, etc. In addition, the navigation model may include at least one navigation function of object search, object classification, recommended information, and user collection, that is, the navigation model is used to provide users with a variety of functions for finding required objects, and the above-mentioned objects may be commodities, information or social information, etc., which are not limited by the embodiments of the present disclosure. In addition, the navigation model also includes a user interface (UI) corresponding to the navigation function, so that the client can quickly determine the elements corresponding to the navigation function based on the UI.

[0085] In this example implementation, optionally, user behavior data in each application of the same category is collected, including:

[0086] Determine globally all applications including navigation functions as applications of the same category; wherein the navigation functions include at least one of object search, object classification, recommended information, and user collection;

[0087] Collect user behavior data for applications that use the system application programming interface among applications of the same category;

[0088] Perform user interface acquisition for applications that use custom application programming interfaces in the same category of applications.

[0089] Among them, user behavior data collection for applications that use system application programming interfaces in the same category of applications includes:

[0090] Perform data analysis on the interface elements of applications that use the system application programming interface among applications in the same category;

[0091] The data analysis results are filtered according to preset rules and stored as user behavior data.

[0092] In this example implementation, the above-mentioned navigation function may be a function included in the above-mentioned navigation model.

[0093] In this example implementation, the method of determining the applications including the navigation function as the same category applications in the global scope can be specifically: detecting the applications including the navigation function in the global scope through the hook function, and determining the applications including the navigation function as the same category applications. It should be explained that the same category applications are a type of applications defined in this example implementation, and since these types of applications all include the navigation function, these applications are the same type of applications in this example implementation. In addition, the hook function can be expressed as a hook, and the hook can be injected into the system to obtain the required information.

[0094] This example implementation may also include the following steps: detecting whether the same category application uses a system application programming interface (ie, system API) or a custom application programming interface (ie, custom API). The system API may be understood as a known API.

[0095] If the system API is used, user behavior data is collected through the system API, and if the custom API is used, user interface data is collected. API (Application Programming Interface) is a set of predefined functions that aims to provide application and developers with the ability to access a set of routines based on certain software or hardware without accessing the source code or understanding the details of the internal working mechanism.

[0096] In this example implementation, the method of collecting the user interface of an application using a custom application programming interface among applications of the same category may specifically be: determining the user interface of an application using a custom application programming interface among applications of the same category, and taking a screenshot of the user interface.

[0097] Furthermore, it can be determined whether the content corresponding to the screenshot contains navigation content. If so, data analysis and data filtering are performed on the screenshot, and the filtering results are stored as user behavior data. Among them, navigation content can be understood as content containing the above navigation function.

[0098] In this example implementation, the method of performing data analysis on the interface elements of applications that use the system application programming interface among applications of the same category may specifically be: determining the interface elements of applications that use the system application programming interface among applications of the same category; and collecting user click counts for each interface element.

[0099] In this example implementation, the preset rules are used to filter invalid clicks, and invalid clicks can be understood as clicks on elements corresponding to non-navigation functions.

[0100] For example, see Figure 2 , Figure 2 FIG. 2 shows a flow chart of collecting user behavior data of various applications of the same category according to an exemplary embodiment of the present disclosure. Figure 2 As shown, the following steps are included: step S210 to step S280, wherein:

[0101] Step S210: Detect applications including navigation functions globally through hook, and determine the applications including navigation functions as applications of the same category.

[0102] Step S220: Detect whether the same category application uses the system API or the custom API. If it is the system API, execute step S230; if it is the custom API, execute step S240.

[0103] Step S230: Perform data analysis on the interface elements of the application.

[0104] Step S240: Take a screenshot of the user interface of the application.

[0105] Step S250: Filter the data analysis results according to preset rules, and store the filtered results as user behavior data.

[0106] Step S260: Determine whether the content corresponding to the screenshot contains navigation content. If yes, execute step S270; if not, end this process.

[0107] Step S270: Perform data analysis and data filtering on the screenshot.

[0108] Step S280: Store the filtering results as user behavior data.

[0109] Specifically, hook can be used to detect applications containing navigation functions on a global scale, and applications containing navigation functions can be determined as applications of the same category, where hook is a hook function; further, it can be detected whether applications of the same category use system APIs or custom APIs. If it is a system API, data analysis is performed on the interface elements of the application, where the interface elements can be understood as identifiers representing navigation functions. Further, the data analysis results can be filtered according to preset rules, and the filtered results can be stored as user behavior data so that the user behavior data can be called during data analysis; in addition, if it is a custom API, a screenshot of the user interface of the application can be taken to determine whether the content corresponding to the screenshot contains navigation content. If it contains navigation content, data analysis and data filtering can be performed on the screenshot, and the filtered results can be stored as user behavior data; it should be noted that a custom API can be understood as an API of an application that is not independently developed among applications of the same category.

[0110] For example, the mobile terminal includes shopping application A, shopping application B and shopping application C, among which the shopping application is an independently developed application and uses the system API; the shopping application B is an application that is not independently developed (it can be understood as an application developed by other companies) and uses the system API; the shopping application C is an application that is not independently developed and uses a custom API. Data analysis can be performed on the interface elements in shopping application A and shopping application B, and invalid data (such as data corresponding to invalid clicks) can be filtered according to preset rules. The results of the filtering can be user behavior data (such as click data corresponding to when users search for products, and click data corresponding to when users search for products according to product categories), and they are stored. In addition, a screenshot of the user interface of shopping application C can be taken. If the screenshot contains navigation content, data analysis and data filtering are performed on the screenshot, and the filtering results are stored as user behavior data.

[0111] It can be seen that by implementing this optional implementation, the accuracy of the user behavior analysis results can be improved by collecting user behavior data of applications of the same category respectively.

[0112] In step S120, user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of application programs are determined based on the user behavior data.

[0113] In this example implementation, the method of determining the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of applications based on user behavior data may specifically be: based on TensorFlow and based on user behavior data, determining the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of applications; wherein TensorFlow is an open source software library for data flow programming across a range of tasks. It is a symbolic mathematics library that can be used in machine learning applications, such as neural networks.

[0114] In addition, the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of applications are determined based on user behavior data, which is based on edge computing. It can be understood that the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of applications are determined by the client based on user behavior data, which can save server resources, simplify the interaction process between the client and the server, and thus improve computing efficiency. Among them, edge computing refers to processing data at the edge of the network, which can reduce request response time, improve battery life and reduce network bandwidth, while ensuring data security and privacy.

[0115] In this example implementation, the user preference weight is used to indicate the user's usage frequency for each type of interactive content, and the interactive content offset is used to indicate the position of each interactive content after the display position of the interactive content is adjusted according to the user's usage frequency for each type of interactive content.

[0116] In this example implementation, optionally, determining the user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of application programs based on user behavior data includes:

[0117] Input the sample data into the prediction model to calculate the loss function between the prediction result output by the prediction model and the result corresponding to the sample, and update the parameters of the prediction model according to the loss function;

[0118] The user behavior data is input into the prediction model with updated parameters, and the user preference weights and interaction content offsets corresponding to various types of interaction content in the same category of applications are determined through the prediction model with updated parameters.

[0119] In this example implementation, the sample data includes user behavior data with annotated user preference weights and interaction content offsets.

[0120] In this example implementation, the loss function between the prediction result output by the prediction model and the result corresponding to the sample can be calculated according to the following expression:

[0121] x i’ (i) = -∑i′ ylog(i y )

[0122] Among them, i y is the prediction result, i′ y is the result corresponding to the sample, which can be calculated based on x i’ (i) Update the parameters of the prediction model.

[0123] Specifically, the method of updating the parameters of the prediction model according to the loss function may be: updating the parameters of the prediction model according to the loss function until the loss function is less than a preset loss value.

[0124] It can be seen that by implementing this optional implementation method, the user preference weights and interactive content offsets corresponding to various types of interactive content can be predicted through the trained prediction model, so as to personalize the display method of interactive content for terminal users based on the user preference weights and interactive content offsets.

[0125] In this example implementation, optionally, the method for updating the interactive content display mode further includes:

[0126] If there are target interaction contents with the same user preference weight, then determining the target interaction content offsets corresponding to the target interaction contents respectively;

[0127] Prioritize the same user preference weights in order from low to high according to the target interaction content offset;

[0128] All user preference weights are prioritized according to the priority ranking results of the same user preference weights.

[0129] In this example implementation, the same user preference weight can be understood as the same user usage frequency of two different interactive contents.

[0130] In this example implementation, the method for prioritizing all user preference weights according to the priority sorting results of the same user preference weights can specifically be: prioritizing different user preference weights among all user preference weights in order from high to low, and prioritizing the same user preference weights in order from low to high according to the target interaction content offset, and combining the two sorting results to obtain the result of prioritizing all user preference weights.

[0131] It can be seen that the implementation of this optional implementation method can sort the user preference weights according to the weight size and the target interactive content offset size, so as to determine the priority order of the interactive content that the user prefers to use, which is conducive to personalized adjustment of the display method of the interactive content, so as to improve the user experience and enhance the user's usage stickiness.

[0132] In step S130, the display mode of each type of interactive content in the target application is updated according to the user preference weight and the interactive content offset; wherein the target application is included in the applications of the same category.

[0133] In this example implementation, the display mode of each type of interactive content can be understood as the setting mode of the element position corresponding to each type of interactive content in the user interface. The target application can be the application whose element display mode is to be updated.

[0134] In this example implementation, optionally, updating the display mode of various types of interactive content in the target application according to the user preference weight and the interactive content offset includes:

[0135] Determine the target user preference weights that are above a preset threshold in the priority ranking results of the user preference weights;

[0136] The display mode of various interactive contents in the target application is updated according to the target user preference weight and the interactive content offset corresponding to the target user preference weight.

[0137] Among them, the display mode of various interactive contents in the target application is updated according to the target user preference weight and the interactive content offset corresponding to the target user preference weight, including:

[0138] The interactive content that is not displayed at the first level in the target application corresponding to the target user's preference weight is displayed at the first level according to the interactive content offset corresponding to the target user's preference weight;

[0139] Adjust the display method of other interactive contents in the target application according to the first-level display result.

[0140] In this example implementation, the first-level display can be understood as display on the homepage of the application, and the interactive content not displayed at the first level can be understood as the interactive content not displayed on the homepage.

[0141] In this example implementation, the interactive content that is not displayed at the first level in the target application corresponding to the target user preference weight is displayed at the first level according to the interactive content offset corresponding to the target user preference weight, and the display method of other interactive content in the target application is adjusted according to the first level display result. Specifically, the method may be:

[0142] Determine the first interactive content in the target application that is not displayed at the first level and corresponds to the target user preference weight, and determine the second interactive content in the interactive content displayed at the first level whose user preference weight is not the target user preference weight, delete the element corresponding to the second interactive content from the first level display interface, and display the element corresponding to the first interactive content at the position of the second interactive content according to the interactive content offset.

[0143] It can be seen that the implementation of this optional implementation can personalize the application according to the preferences of different users and improve the user stickiness.

[0144] It can be seen that the implementation Figure 1 The updating method of the interactive content display method shown can overcome the problem of low shopping convenience to a certain extent, and improve the user's shopping convenience and user experience by personalizing and updating the interactive content display method for users; and can personalize the application according to the preferences of different users to improve user stickiness.

[0145] See also Figure 3 , Figure 3 FIG. 2 is a flow chart showing another method for updating an interactive content display mode according to an exemplary embodiment of the present disclosure. Figure 3 As shown, the following steps S310 to S390 are included, wherein:

[0146] Step S310: globally determining various applications including navigation functions as applications of the same category.

[0147] Step S320: Collect user behavior data for applications in the same category that use the system application programming interface; and collect user interface data for applications in the same category that use the custom application programming interface.

[0148] Step S330: Input the sample data into the prediction model to calculate the loss function between the prediction result output by the prediction model and the result corresponding to the sample, and update the parameters of the prediction model according to the loss function.

[0149] Step S340: inputting the user behavior data into the prediction model with updated parameters, and determining the user preference weights and interaction content offsets corresponding to various types of interaction content in the same category of application programs through the prediction model with updated parameters.

[0150] Step S350: If there are target interaction contents with the same user preference weight, then the target interaction content offsets corresponding to the target interaction contents are determined.

[0151] Step S360: Prioritize the same user preference weights in descending order of target interactive content offset.

[0152] Step S370: Prioritize all user preference weights according to the priority ranking result of the same user preference weight.

[0153] Step S380: Determine the target user preference weights that are higher than a preset threshold in the priority ranking results of the user preference weights.

[0154] Step S390: updating the display mode of each type of interactive content in the target application according to the target user preference weight and the interactive content offset corresponding to the target user preference weight.

[0155] It should be noted that Figure 3 For specific embodiments corresponding to the steps shown, please refer to Figure 1 The specific implementation method in the embodiment will not be described in detail here. Figure 3 The other interactive content display method shown can overcome the problem of low shopping convenience to a certain extent. By personalizing and updating the interactive content display method for users, it can improve the user's shopping convenience and improve the user's usage experience; and it can personalize the application according to the preferences of different users to improve user stickiness.

[0156] See also Figure 4 , Figure 4 The structural block diagram of an apparatus for updating an interactive content display mode according to an exemplary embodiment of the present disclosure is shown. The apparatus for updating an interactive content display mode includes a data collection unit 401, a weight determination unit 402, and a display mode update unit 403, wherein:

[0157] The data collection unit 401 is used to collect user behavior data from various applications of the same category;

[0158] A weight determination unit 402 is used to determine user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of application programs according to user behavior data;

[0159] The display mode updating unit 403 is used to update the display modes of various interactive contents in the target application according to the user preference weight and the interactive content offset; wherein the target application is included in the applications of the same category.

[0160] It can be seen that implementation Figure 4 The updating device for the interactive content display method shown can overcome the problem of low shopping convenience to a certain extent. By personalizing and updating the interactive content display method for users, the shopping convenience of users is improved and the user experience is improved. In addition, the application program can be personalized according to the preferences of different users to improve the user stickiness.

[0161] As an exemplary embodiment, the data collection unit 401 may collect user behavior data in various applications of the same category in the following manner:

[0162] The data collection unit 401 globally determines each application program including a navigation function as a same-category application program; wherein the navigation function includes at least one of object search, object classification, recommended information, and user collection;

[0163] The data collection unit 401 collects user behavior data from applications in the same category that use the system application programming interface;

[0164] The data collection unit 401 collects user interfaces of applications using a custom application programming interface among applications of the same category.

[0165] The data collection unit 401 collects user behavior data from applications using the system application programming interface in the same category of applications in a specific manner:

[0166] The data collection unit 401 performs data analysis on the interface elements of the application programs that use the system application programming interface among the application programs of the same category;

[0167] The data collection unit 401 filters the data analysis results according to preset rules and stores the filtered results as user behavior data.

[0168] It can be seen that by implementing this optional implementation, the accuracy of the user behavior analysis results can be improved by collecting user behavior data of applications of the same category respectively.

[0169] As another exemplary embodiment, the weight determination unit 402 may determine the user preference weights and interaction content offsets corresponding to various types of interaction content in the same category of application programs according to the user behavior data in the following manner:

[0170] The weight determination unit 402 inputs the sample data into the prediction model to calculate the loss function between the prediction result output by the prediction model and the result corresponding to the sample, and updates the parameters of the prediction model according to the loss function;

[0171] The weight determination unit 402 inputs the user behavior data into the prediction model with updated parameters, and determines the user preference weights and interaction content offsets corresponding to various types of interaction content in the same category of application programs through the prediction model with updated parameters.

[0172] It can be seen that by implementing this optional implementation method, the user preference weights and interactive content offsets corresponding to various types of interactive content can be predicted through the trained prediction model, so as to personalize the display method of interactive content for terminal users based on the user preference weights and interactive content offsets.

[0173] As another exemplary embodiment, the updating device for the interactive content display mode may further include an interactive content offset determination unit (not shown) and a priority sorting unit (not shown), wherein:

[0174] An interactive content offset determination unit, used to determine the target interactive content offsets corresponding to the target interactive contents respectively when there are target interactive contents with the same user preference weight;

[0175] A priority sorting unit, used to prioritize the same user preference weights in order of target interactive content offset from low to high;

[0176] The priority sorting unit is further used to prioritize all user preference weights according to the priority sorting results of the same user preference weights.

[0177] It can be seen that the implementation of this optional implementation method can sort the user preference weights according to the weight size and the target interactive content offset size, so as to determine the priority order of the interactive content that the user prefers to use, which is conducive to personalized adjustment of the display method of the interactive content, so as to improve the user experience and enhance the user's usage stickiness.

[0178] As another exemplary embodiment, the display mode updating unit 403 updates the display modes of various interactive contents in the target application according to the user preference weight and the interactive content offset in a specific manner as follows:

[0179] The display mode updating unit 403 determines the target user preference weight that is higher than a preset threshold in the priority ranking result of the user preference weight;

[0180] The display mode updating unit 403 updates the display modes of various interactive contents in the target application according to the target user preference weight and the interactive content offset corresponding to the target user preference weight.

[0181] The display mode updating unit 403 updates the display modes of various interactive contents in the target application according to the target user preference weight and the interactive content offset corresponding to the target user preference weight in a specific manner as follows:

[0182] The display mode updating unit 403 displays the non-primary display interactive content in the target application corresponding to the target user preference weight in a primary display according to the interactive content offset corresponding to the target user preference weight;

[0183] The display mode updating unit 403 adjusts the display mode of other interactive contents in the target application according to the primary display result.

[0184] It can be seen that the implementation of this optional implementation can personalize the application according to the preferences of different users and improve the user stickiness.

[0185] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0186] Since the various functional modules of the device for updating the interactive content display method of the example embodiment of the present disclosure correspond to the steps of the example embodiment of the method for updating the interactive content display method described above, for details not disclosed in the device embodiment of the present disclosure, please refer to the embodiment of the method for updating the interactive content display method described above in the present disclosure.

[0187] Figure 5 A schematic diagram of a system architecture of an exemplary application environment to which an updating method for an interactive content display mode and an updating device for an interactive content display mode according to an embodiment of the present disclosure can be applied is shown.

[0188] like Figure 5 As shown, the system architecture 500 may include one or more of terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 is used to provide a medium for communication links between the terminal devices 501, 502, 503 and the server 505. The network 504 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc. The terminal devices 501, 502, 503 may be various electronic devices with display screens, including but not limited to desktop computers, portable computers, smart phones, tablet computers, etc. It should be understood that Figure 5 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 505 may be a server cluster composed of multiple servers.

[0189] The updating method of the interactive content display mode provided in the embodiment of the present disclosure is generally executed by the server 505, and accordingly, the updating device of the interactive content display mode is generally set in the server 505. However, it is easy for those skilled in the art to understand that the updating method of the interactive content display mode provided in the embodiment of the present disclosure can also be executed by the terminal devices 501, 502, and 503, and accordingly, the updating device of the interactive content display mode can also be set in the terminal devices 501, 502, and 503, which is not particularly limited in this exemplary embodiment. For example, in an exemplary embodiment, the terminal devices 501, 502, 503 or the server 505 can collect user behavior data in each application of the same category; and, the user preference weights and interactive content offsets corresponding to each type of interactive content in the application of the same category can be determined based on the user behavior data; and, the display mode of each type of interactive content in the target application can be updated based on the user preference weights and interactive content offsets.

[0190] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present disclosure is shown.

[0191] It should be noted that Figure 6 The computer system 600 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0192] like Figure 6 As shown, computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. Various programs and data required for system operation are also stored in RAM 603. CPU 601, ROM 602 and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to bus 604.

[0193] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage section 608 as needed.

[0194] In particular, according to an embodiment of the present disclosure, the process described below with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, various functions defined in the method and apparatus of the present application are executed. In some embodiments, the computer system 600 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0195] It should be noted that the computer-readable medium shown in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0196] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0197] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, and the units described may also be arranged in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0198] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the following embodiment. For example, the electronic device may implement the following method. Figure 1 to Figure 3 The various steps shown, etc.

[0199] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0200] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for updating an interactive content display mode, characterized in that: The method comprises: Collect user behavior data from various applications of the same category; Determine the user preference weight and interactive content offset corresponding to each type of interactive content in the same category of application programs according to the user behavior data; updating the display mode of each type of interactive content in the target application according to the user preference weight and the interactive content offset; wherein the target application is included in the applications of the same category; Wherein, updating the display mode of each type of interactive content in the target application according to the user preference weight and the interactive content offset includes: Determine the target user preference weights that are above a preset threshold in the priority ranking results of the user preference weights; Determine the first interactive content in the target application that is not displayed at the first level and corresponds to the target user preference weight, and determine the second interactive content in the first-level interactive content that does not correspond to the target user preference weight, delete the element corresponding to the second interactive content from the first-level display interface, and display the element corresponding to the first interactive content at the position of the second interactive content according to the interactive content offset.

2. The method according to claim 1, characterized in that Collect user behavior data from various applications of the same category, including: Determine globally each application program including a navigation function as the application program of the same category; wherein the navigation function includes at least one of object search, object classification, recommended information, and user collection; Collecting user behavior data for applications using the system application programming interface among the same category of applications; User interface collection is performed on application programs in the same category that use custom application programming interfaces.

3. The method according to claim 2, characterized in that Collecting user behavior data for applications in the same category that use the system application programming interface, including: Performing data analysis on interface elements of applications using the system application programming interface among the applications of the same category; The data analysis results are filtered according to preset rules, and the filtered results are stored as the user behavior data.

4. The method according to claim 1, characterized in that Determining user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of applications according to the user behavior data includes: Input the sample data into the prediction model to calculate the loss function between the prediction result output by the prediction model and the result corresponding to the sample, and update the parameters of the prediction model according to the loss function; The user behavior data is input into the prediction model after parameter update, and the user preference weight and the interaction content offset corresponding to each type of interaction content in the same category of application programs are determined by the prediction model after parameter update.

5. The method according to claim 4, characterized in that The method further comprises: If there are target interaction contents with the same user preference weight, determining the target interaction content offsets respectively corresponding to the target interaction contents; Prioritizing the same user preference weights in descending order of the target interactive content offsets; All the user preference weights are prioritized according to the priority ranking result of the same user preference weight.

6. A device for updating an interactive content display mode, characterized in that: The device comprises: A data collection unit, used to collect user behavior data from various applications of the same category; A weight determination unit, configured to determine, based on the user behavior data, user preference weights and interactive content offsets corresponding to various types of interactive content in the same category of application programs; A display mode updating unit, configured to update the display modes of the various types of interactive content in the target application according to the user preference weight and the interactive content offset; wherein the target application is included in the applications of the same category; The display mode updating unit updates the display modes of the various interactive contents in the target application according to the user preference weight and the interactive content offset, including: Determine the target user preference weights that are above a preset threshold in the priority ranking results of the user preference weights; Determine the first interactive content in the target application that is not displayed at the first level and corresponds to the target user preference weight, and determine the second interactive content in the first-level interactive content that does not correspond to the target user preference weight, delete the element corresponding to the second interactive content from the first-level display interface, and display the element corresponding to the first interactive content at the position of the second interactive content according to the interactive content offset.

7. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for updating the interactive content display mode according to any one of claims 1 to 5 is implemented.

8. An electronic device, characterized in that: include: one or more processors; A storage device, used to store one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the method for updating the interactive content display mode according to any one of claims 1 to 5.

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