Page content display method and device, storage medium and computer equipment

Abstract

The invention discloses a page content display method and device, a storage medium and computer equipment, and the method comprises the steps: responding to a page content obtaining signal of a target user for a target application program; acquiring real-time position information and user feature information of a target user, and equipment attribute information, historical behavior information and real-time position attribute information of mobile equipment; based on the real-time position information, determining a display content type, and determining a target shop corresponding to the display content type; obtaining dynamic value information and content feature information of reserve page content corresponding to the target shop; based on the user feature information, the historical behavior information, the real-time position attribute information, the dynamic value information and the content feature information, target page content interested by the target user is determined in the reserve page content, and based on the equipment attribute information, a personalized page corresponding to the target page content is dynamically displayed to the target user.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a method, device, storage medium and computer equipment for displaying page content. Background Art

[0002] Stores or shopping malls build professional e-commerce platforms to enable users to browse products intuitively. In order for users to find the products they want more quickly, it is necessary to display product pages to users.

[0003] Currently, the same page is usually displayed to all users based on promotional activities or product popularity. However, this page display method does not display the page that the user is interested in, resulting in low accuracy of page display and failure to meet the specific needs of different users. Summary of the invention

[0004] The present invention provides a method, device, storage medium and computer equipment for displaying page content, which are mainly capable of enabling the displayed page to meet the personalized needs of different users, that is, capable of improving the display accuracy of the page.

[0005] According to a first aspect of the present invention, a method for displaying page content is provided, comprising:

[0006] In response to a target user acquiring a page content acquisition signal for a target application, acquiring the target user's real-time location information, user feature information, device attribute information of a mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the target user's real-time location;

[0007] Based on the real-time location information, determining a display content type corresponding to the target application, and determining a target store corresponding to the display content type;

[0008] Obtaining dynamic value information and content feature information of the reserve page content corresponding to the target store;

[0009] Based on the user characteristic information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content characteristic information, the target page content that the target user is interested in is determined in the reserve page content, and based on the device attribute information, a personalized page corresponding to the target page content is dynamically displayed to the target user.

[0010] Optionally, acquiring the real-time location information of the target user includes:

[0011] Acquire the real-time location information of the target user by using multiple positioning methods, wherein the multiple positioning methods include at least two positioning methods selected from the group consisting of GPS positioning method, WiFi positioning method, IP address positioning method, base station positioning method, Bluetooth positioning method, geomagnetic positioning method, and inertial navigation positioning method;

[0012] The method of obtaining the real-time location information of the target user by using multiple positioning methods includes:

[0013] Based on various positioning methods, respectively send a real-time location information acquisition request to the target user;

[0014] A target positioning method for obtaining consent information returned by the target user is determined among various positioning methods, and real-time location information of the target user is obtained based on the target positioning method.

[0015] Optionally, the display content types include: single-store content type, multi-store content type, domestic multi-store duty-paid content type, and overseas content type;

[0016] The determining, based on the real-time location information, a display content type corresponding to the target application program includes:

[0017] Based on the real-time location information, determining whether there is a short-distance store involved in the target application within a preset distance corresponding to the target user;

[0018] If the short-distance store exists within the preset distance, determining a single-store content type of the target application for the short-distance store;

[0019] If there is no store within the preset distance, determining whether the target user is within the target area based on the real-time location information;

[0020] If the target user is in the target area, then determining multiple regional stores in the target area involved by the target application, and determining multiple store content types that the target application corresponds to in common with each of the regional stores;

[0021] If the target user is not in the target area, determining whether the target user is in the country based on the real-time location information;

[0022] If the target user is in China, then determine the domestic stores involved in the target application, and determine the domestic multi-store tax-paid content type that the target application corresponds to for each of the domestic stores;

[0023] If the target user is not in China, determining the cross-border commodity information involved in the target application, and determining the overseas content type that the target application corresponds to for each cross-border commodity information;

[0024] The determining of a target store corresponding to the display content type includes:

[0025] determining a short-distance store corresponding to the single-store content type; or,

[0026] Determine each of the regional stores corresponding to the multi-store content type; or,

[0027] Determine each of the domestic stores corresponding to the domestic multiple stores tax-paid content type; or,

[0028] Determine a cross-border commodity supply store to which each cross-border commodity information corresponding to the overseas content type belongs.

[0029] Optionally, the determining the target page content that the target user is interested in from the reserve page content based on the user feature information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content feature information includes:

[0030] Determining predicted content of interest to the target user based on the user feature information, the historical behavior information, and the real-time location attribute information;

[0031] Performing similarity matching between the predicted interesting content and the reserved page content, and determining the actual interesting page content of the target user in the reserved page content based on the matching result;

[0032] Based on the dynamic value information and content feature information of the actual page content of interest, target page content whose quality and influence both meet preset conditions is determined in the actual page content of interest.

[0033] Optionally, the determining the predicted content of interest of the target user based on the user feature information, the historical behavior information, and the real-time location attribute information includes:

[0034] Respectively determining a user feature vector corresponding to the user feature information, a behavior feature vector corresponding to the historical behavior information, and a location feature vector corresponding to the real-time location attribute information;

[0035] Cross-processing the user feature vector, the behavior feature vector, and the position feature vector to obtain a content cross-feature vector;

[0036] The content cross feature vector is input into a preset content prediction model to perform content prediction, so as to obtain the predicted content of interest to the target user.

[0037] Optionally, the performing similarity matching between the predicted interesting content and the reserved page content includes:

[0038] Determining a content feature vector corresponding to each of the reserve page contents;

[0039] Based on each of the content feature vectors, clustering processing is performed on the content of each of the reserve pages to obtain the reserve page content under different clustering categories;

[0040] Based on the different cluster categories, the predicted interesting content is classified to obtain the target cluster category to which the predicted interesting content belongs, and the predicted interesting content is matched with the reserve page content under the target cluster category by similarity;

[0041] The clustering process of each of the reserve page contents based on each of the content feature vectors to obtain reserve page contents under different clustering categories includes:

[0042] Initialize the centroid vectors corresponding to different clusters;

[0043] Calculating the distance between the content feature vector and the centroid vectors corresponding to the different clusters, and dividing the contents of each of the reserve pages into the different clusters based on the distance;

[0044] Based on the content feature vectors corresponding to the reserve page contents in the different clusters, obtaining updated centroid vectors corresponding to the different clusters;

[0045] Based on the updated centroid vector, each of the reserve page contents is re-divided into the different clusters until the updated centroid vector does not change, and the reserve page contents finally divided into the different clusters are determined as reserve page contents under different clustering categories.

[0046] Optionally, the device attribute information includes: screen size information, screen resolution information, pixel density, and operating system information of the mobile device used by the target user;

[0047] The dynamically displaying a personalized page corresponding to the target page content to the target user based on the device attribute information includes:

[0048] Based on the screen size information and the screen resolution information, determine the page layout and content area size of the target page content in the page to be displayed;

[0049] Based on the pixel density, determining a display resolution of the page to be displayed;

[0050] Based on the operating system information, determining an interactive adaptation mode of the page to be displayed;

[0051] Based on the page layout, content area size, display resolution, and interactive adaptation method, the target page content is configured in the page to be displayed, a personalized page for the target user is obtained, and the personalized page is displayed to the target user.

[0052] According to a second aspect of the present invention, there is provided a device for displaying page content, comprising:

[0053] A first acquisition unit is used to acquire, in response to a target user's page content acquisition signal for a target application, the target user's real-time location information, user feature information, device attribute information of a mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the target user's real-time location;

[0054] a determination unit, configured to determine, based on the real-time location information, a display content type corresponding to the target application, and determine a target store corresponding to the display content type;

[0055] A second acquisition unit is used to acquire dynamic value information and content feature information of the reserve page content corresponding to the target store;

[0056] A display unit is used to determine the target page content that the target user is interested in from the reserve page content based on the user characteristic information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content characteristic information, and dynamically display a personalized page corresponding to the target page content to the target user based on the device attribute information.

[0057] According to a third aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned method for displaying page content when executed by a processor.

[0058] According to a fourth aspect of the present invention, there is provided a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for displaying page content when executing the program.

[0059] According to a method, device, storage medium and computer device for displaying page content provided by the present invention, compared with the current method of displaying the same page to all users based on promotional activities or product popularity, the present invention can determine the display content type corresponding to the target application and the target store corresponding to the display content type through the real-time location information of the target user, and determine the page content of interest to the target user based on the user feature information, historical behavior information, real-time location attribute information, dynamic value information and content feature information of the reserved page content in the target store, and display a personalized page containing the page content of interest to the target user based on the device attribute information of the mobile device used by the target user, thereby determining the page content of interest to the target user by comprehensively analyzing the real-time location information, user feature information, device attribute information, historical behavior information, real-time location attribute information of the real-time location, dynamic value information and content feature information of the reserved page content, which can improve the accuracy of determining the page content, thereby ensuring that the page content displayed to the user is the content that the user actually needs and is interested in, thereby improving the user experience and meeting the personalized needs of different users. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0061] Figure 1 A flow chart of a method for displaying page content provided by an embodiment of the present invention is shown;

[0062] Figure 2 A flow chart of another method for displaying page content provided by an embodiment of the present invention is shown;

[0063] Figure 3 A schematic diagram showing the structure of a device for displaying page content provided by an embodiment of the present invention is shown;

[0064] Figure 4 A schematic diagram showing the structure of another device for displaying page content provided by an embodiment of the present invention is shown;

[0065] Figure 5 A schematic diagram of the physical structure of a computer device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0066] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0067] Currently, the method of displaying the same page to all users based on promotional activities or product popularity means that the page displayed is not the page that the user is interested in, resulting in low accuracy of page display and failure to meet the specific needs of different users.

[0068] In order to solve the above problems, an embodiment of the present invention provides a method for displaying page content, such as Figure 1 As shown, the method includes:

[0069] 101. In response to a target user acquiring a signal for page content of a target application, the target user's real-time location information, user feature information, device attribute information of the mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the target user's real-time location are acquired.

[0070] Among them, the target application involves multiple stores in multiple cities, where the multiple stores can be any stores such as commodity stores, the target application can be any application such as commodity sales application, and the page can be any page such as commodity content page; the real-time location information can be the latitude and longitude information, IP location information, etc. of the target user; user feature information refers to the interests, hobbies, age, gender, occupation, income, etc. of the target user; the mobile device can be a mobile phone, tablet, computer and other devices; the device attribute information refers to the screen size information, screen resolution information, pixel density, operating system information (such as Android operating system, iOS (Internetworking Operating System, a mobile operating system) operating system, Hongmeng operating system, etc.) of the mobile device; historical behavior information refers to the browsing behavior link information of the target user on the target application (such as frequently browsed page content, dwell time, click frequency, etc.); the real-time location attribute information refers to the real-time network status information, real-time environmental information (such as real-time temperature, real-time dryness, etc.) and other information of the real-time location of the target user.

[0071] For the embodiment of the present invention, when the target user logs in to the target application, a page content acquisition signal is triggered. When the system receives the page content acquisition signal, it will acquire all information that affects the personalized page display, including the target user's real-time location information, user feature information, device attribute information of the mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the real-time location of the target user. After that, all the above information is comprehensively analyzed to determine the page content that the user is interested in, and a personalized page containing the page content that the user is interested in is displayed to the user. By comprehensively analyzing all the information that affects the personalized page display, the page content that the user is interested in is determined, which can improve the accuracy of determining the page content, so that the determined page content meets the user's specific needs and improves the user experience. It should be noted that the above information is information obtained with the user's authorization, or information filled in by the user when registering the target application, and is not user privacy information.

[0072] 102. Based on the real-time location information, determine a display content type corresponding to the target application, and determine a target store corresponding to the display content type.

[0073] Among them, the display content types include: single-store content type, multi-store content type, domestic multi-store duty-paid content type, and overseas content type. The single-store content type means that only the product information, activity information, etc. of a certain store that meets the conditions are displayed in the corresponding interface corresponding to the target application. The multi-store content type means that the product information, activity information, etc. of multiple stores that meet the conditions are displayed in the corresponding interface corresponding to the target application. The domestic multi-store duty-paid content type means that the duty-paid product information, activity information, etc. of multiple stores that meet the conditions are displayed in the corresponding interface corresponding to the target application. The overseas content type means that the overseas product information, etc. of multiple stores that meet the conditions are displayed in the corresponding interface corresponding to the target application.

[0074] For the embodiment of the present invention, the display content type of the target application, that is, the display page type, can be determined based on the real-time location of the target user. For example, if there is a store within 5 kilometers from the user, the display content type of the target application should be a single-store content type, that is, only the product information of the store is displayed in the corresponding interface of the target application. At this time, the store is the target store corresponding to the display content type. Therefore, the real-time location of the user is different, and the display content type about the product displayed to the user will also be different, which can meet the personalized needs of different users and enhance the user experience. The embodiment of the present invention dynamically determines the display content through the real-time location of the user, which can ensure the timely update and localization of the content, thereby ensuring the timeliness and relevance of the content. It also pushes information about related stores to users in a specific area, shortening the purchase distance of users for products, thereby improving the purchase efficiency of users for products.

[0075] 103. Obtain dynamic value information and content feature information of the reserve page content corresponding to the target store.

[0076] Among them, the reserve page content refers to the pre-configured content, such as the description information, price information, activity information, etc. of product A; dynamic value information refers to the information such as the popularity, popularity, relevance, influence, etc. of the reserve page content that reflects the dynamic changes of the content; content feature information refers to the theme, style, emotion, quality, length, format, type, label, etc. of the reserve page content.

[0077] For the embodiment of the present invention, the database corresponding to the target application stores the pre-configured reserve page content under different stores. It should be noted that the reserve page content is not static and will be updated in real time with market conditions, product information, etc. After determining the target store corresponding to the display content type, the reserve page content corresponding to the target store is obtained in the database, and the dynamic value information and content feature information of the reserve page content are obtained. Then, based on the dynamic value information and content feature information of the reserve page content, as well as the user feature information, historical behavior information, and real-time location attribute information of the target user, the personalized page required by the user is displayed to the target user, thereby determining the personalized page by comprehensively analyzing various influencing factors (including user feature information, the historical behavior information, real-time location attribute information, dynamic value information, and content feature information) that affect the generation of personalized pages, and being able to generate accurate pages for different users, ensuring that the generated pages can meet the personalized needs of users, thereby improving the user experience.

[0078] 104. Based on user feature information, historical behavior information, real-time location attribute information, dynamic value information, and content feature information, determine the target page content that the target user is interested in from the reserve page content, and based on the device attribute information, dynamically display the personalized page corresponding to the target page content to the target user.

[0079] For the embodiment of the present invention, the target page content that the target user is interested in is determined in the reserve page content by comprehensively analyzing the user feature information, historical behavior information, real-time location attribute information, dynamic value information, and content feature information. Then, according to the device attribute information of the mobile device used by the user, such as the screen size, resolution, and operating system, the target page content is configured into the personalized page required by the user, thereby ensuring that the generated page meets the user's personalized needs and improves the user experience. At the same time, configuring the page according to the device attribute information of the mobile device used by the user, such as the screen size, resolution, and operating system, helps to optimize the display effect of the page on the mobile device, so that the user can see the page content more clearly, further improving the user experience.

[0080] According to a method for displaying page content provided by the present invention, compared with the current method of displaying the same page to all users based on promotional activities or product popularity, the present invention can determine the display content type corresponding to the target application and the target store corresponding to the display content type through the real-time location information of the target user, and determine the page content of interest to the target user based on the user feature information, historical behavior information, real-time location attribute information, dynamic value information and content feature information of the reserved page content in the target store, and display a personalized page containing the page content of interest to the target user based on the device attribute information of the mobile device used by the target user, thereby determining the page content of interest to the target user by comprehensively analyzing the real-time location information, user feature information, device attribute information, historical behavior information, real-time location attribute information of the real-time location, dynamic value information and content feature information of the reserved page content, thereby improving the accuracy of determining the page content, thereby ensuring that the page content displayed to the user is the content that the user actually needs and is interested in, thereby improving the user experience and meeting the personalized needs of different users.

[0081] Further, in order to better illustrate the above process of displaying the page content, as a refinement and extension of the above embodiment, the embodiment of the present invention provides another method for displaying the page content, such as Figure 2 As shown, the method includes:

[0082] 201. In response to a target user acquiring a page content signal for a target application, the target user's real-time location information, user feature information, device attribute information of the mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the target user's real-time location are acquired.

[0083] For the embodiment of the present invention, after receiving the page content acquisition signal triggered by the target user for the target application, it is first necessary to obtain the real-time location information of the target user. Based on this, step 201 specifically includes: using multiple positioning methods to obtain the real-time location information of the target user, wherein the multiple positioning methods include at least two positioning methods selected from the group consisting of GPS positioning method, WiFi positioning method, IP address positioning method, base station positioning method, Bluetooth positioning method, geomagnetic positioning method, and inertial navigation positioning method; wherein the method for obtaining the real-time location information of the target user using multiple positioning methods includes: based on various positioning methods, sending real-time location information acquisition requests to the target user respectively; determining the target positioning method for obtaining the consent information returned by the target user among the various positioning methods, and obtaining the real-time location information of the target user based on the target positioning method.

[0084] Specifically, the present invention can realize the acquisition of the user's real-time location based on LBS (Location Based Services) technology. When receiving a page content acquisition signal triggered by the target user for the target application, a location acquisition request such as GPS positioning method, WiFi positioning method, IP address positioning method, base station positioning method, etc. is sent to the target user respectively. If the user agrees to the location acquisition request of a certain target positioning method, an agreement signal will be triggered, and the user's location will be acquired for the target positioning method at this time. For example, if the user agrees to the location acquisition request of GPS positioning method, WiFi positioning method, and base station positioning method, the system will use GPS positioning method, WiFi positioning method, and base station positioning method to respectively acquire the real-time location of the target user, and then comprehensively judge and determine the accurate real-time location information of the target user based on the real-time location acquired by the above-mentioned various positioning methods. The real-time location acquired by the above-mentioned methods is the latitude and longitude of the target user. If the user refuses the location acquisition request of GPS positioning method, WiFi positioning method, and base station positioning method, the system will determine the IP home place of the target user as the real-time location information of the target user. The embodiment of the present invention uses various positioning methods to obtain the user's real-time location time, and can obtain the location API (Application Programming Interface) at the bottom of each terminal and encapsulate it into a cross-platform positioning API calling method, and solve the problem of using the IP positioning method when the location acquisition fails. Furthermore, in order to recommend personalized pages to users, it is also necessary to obtain user feature information of the target user, device attribute information of the mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the real-time location.

[0085] 202. Determine a display content type corresponding to the target application based on the real-time location information, and determine a target store corresponding to the display content type.

[0086] For the embodiment of the present invention, in order to display a personalized page to the user, it is first necessary to determine the display content type corresponding to the target application according to the user's real-time location information. Based on this, step 202 specifically includes: based on the real-time location information, judging whether there is a short-distance store involved in the target application within the preset distance corresponding to the target user; if the short-distance store exists within the preset distance, determining the single-store content type of the target application for the short-distance store; if there is no store within the preset distance, judging whether the target user is within the target area based on the real-time location information; if the target user is within the target area, determining the target application The target application program includes multiple regional stores in the target area, and determines the multi-store content type that the target application corresponds to for each of the regional stores; if the target user is not in the target area, then based on the real-time location information, it is determined whether the target user is in China; if the target user is in China, then the domestic stores involved in the target application are determined, and the domestic multi-store tax-paid content type that the target application corresponds to for each of the domestic stores is determined; if the target user is not in China, then the cross-border commodity information involved in the target application is determined, and the overseas content type that the target application corresponds to for each of the cross-border commodity information is determined. Wherein, determining the target store corresponding to the display content type includes: determining a short-distance store corresponding to the single-store content type; or, determining each of the regional stores corresponding to the multi-store content type; or, determining each of the domestic stores corresponding to the domestic multi-store tax-paid content type; or, determining the cross-border commodity supply store to which each of the cross-border commodity information corresponding to the overseas content type belongs.

[0087] Among them, the preset distance is set according to actual needs, and the target area is the main jurisdiction involved in the target application. Specifically, if the preset distance is 5 kilometers and the target area is within Hainan Island, then if there is a store within 5 kilometers from the target user, that is, a short-distance store, then the display content type is determined to be a single-store content type, that is, the target application only displays information such as goods in the short-distance store, and the target store corresponding to the display content type at this time is the short-distance store. Similarly, if there is no store within 5 kilometers from the target user, but the target user is on Hainan Island, then all stores involved in the target application on Hainan Island, that is, multiple regional stores, are determined. At this time, the display content type is determined to be a multi-store content type, that is, the product information in each regional store is displayed on the target application, and the target store corresponding to the display content type at this time is each regional store. Similarly, if the target user is not in Hainan Island, but in China, then all domestic stores involved in the target application are determined, that is, each domestic store. At this time, the display content type is determined to be a multi-store tax-paid content type, that is, the tax-paid commodity information and other information of each domestic store are displayed on the target application. At this time, the target store corresponding to the display content type is each domestic store. Similarly, if the target user is not in China, that is, overseas, then the cross-border commodity information involved in the target application is determined, that is, the cross-border commodity can be displayed and purchased overseas. At this time, the display content type is determined to be an overseas content type. At this time, the target store corresponding to the display content type is the store to which each cross-border commodity belongs. Therefore, according to the user's location information, the appropriate display content type is determined for the user, which can meet the user's personalized needs, ensure that the user can buy goods from a store that is close to him, and save the user's purchase time.

[0088] 203. Obtain dynamic value information and content feature information of the reserve page content corresponding to the target store.

[0089] Specifically, the database corresponding to the target application stores the dynamic value information and content feature information of each reserve page content, and the dynamic value information and content feature information of the reserve page content can be obtained in the database.

[0090] 204. Determine the predicted content of interest to the target user based on the user feature information, historical behavior information, and real-time location attribute information.

[0091] For the embodiment of the present invention, in order to display the personalized page required by the user to the user, it is first necessary to determine the predicted content of interest to the user. Based on this, step 204 specifically includes: respectively determining the user feature vector corresponding to the user feature information, the behavior feature vector corresponding to the historical behavior information, and the location feature vector corresponding to the real-time location attribute information; cross-processing the user feature vector, the behavior feature vector, and the location feature vector to obtain a content cross-feature vector; inputting the content cross-feature vector into a preset content prediction model for content prediction to obtain the predicted content of interest to the target user. Among them, the method of cross-processing the user feature vector, the behavior feature vector, and the location feature vector to obtain the content cross-feature vector includes: cross-processing the user feature vector, the behavior feature vector, and the location feature vector at the feature level to obtain a feature cross-feature vector; performing element-level cross-processing on the user feature vector, the behavior feature vector, and the location feature vector to obtain an element cross-feature vector; performing low-order cross-processing on the user feature vector, the behavior feature vector, and the location feature vector to obtain a low-order cross-feature vector; fusing the feature cross-feature vector, the element cross-feature vector, and the low-order cross-feature vector to obtain a content cross-feature vector.

[0092] Specifically, since user feature information, historical behavior information, and real-time location attribute information are different fields, the processing method is to embed the data of the three fields into vectors of the same latitude. For example, if the user feature vector is (a1, a2), the behavior feature vector is (b1, b2), and the location feature vector is (c1, c2), the specific cross-processing method includes: performing feature-level crossover between different feature vectors, that is, performing Hadamard products on all elements between vectors, and then performing convolution transformation under certain weights to obtain a feature crossover vector of f(w*(a1*b1*c1,a2*b2*c2,a3*b3*c3)); at the same time, performing element-level crossover on all feature vector data, that is, performing Hadamard products on each element between vectors, and giving each product The results are assigned different weight values, and then a linear transformation is performed, and the obtained element cross vector is f(w1*a1*b1*c1,w2*a2*b2*c2,w3*a3*b3*c3); in addition, all feature vectors are subjected to low-order cross processing, and weight coefficients are assigned to the results after the cross processing, and then a linear transformation is performed, and the obtained low-order cross vector is f(w2(a1,a2,b1,b2,c1,c2)); finally, the above feature cross vectors, element cross vectors, and low-order cross vectors are combined together, and the preset function is used for transformation processing to obtain the content cross feature vector. The preset function here can be set according to the actual situation, and this embodiment does not limit this. It should be noted that the above examples are only illustrative and do not limit the embodiments of the present application. Therefore, by cross-processing the user feature vector, behavior feature vector, and position feature vector, different features can be automatically or explicitly combined to generate new feature combinations. These combined features may contain complex nonlinear relationships between the original features, so that the model can capture more detailed and rich information in the data, that is, it can make full use of the relationship between various data, extract more implicit features, and take into account both high-order and low-order processing, so that data utilization is more complete, and the content of the user's interested page obtained later is more accurate, meeting the needs of actual application scenarios.

[0093] Furthermore, in order to improve the prediction accuracy of the preset content prediction model, it is first necessary to train and construct the preset content prediction model. Based on this, the method includes: constructing at least one initial model, wherein the model structures of each initial model can be the same or different; obtaining a sample data set, wherein the sample data set includes sample user feature information of the sample user, sample historical behavior information for the target application, and sample real-time location attribute information corresponding to the real-time location of the sample user when the target application triggers a content acquisition signal, wherein the sample user feature information includes: sample user's interests, hobbies, age, gender, occupation, income and other information, and the sample historical behavior information is Refers to the historical browsing behavior link information of sample users on the target application (such as frequently browsed page content, dwell time, click frequency, etc.), and the sample real-time location attribute information refers to the real-time network status information, real-time environmental information (such as real-time temperature, real-time dryness, etc.) and other information of the real-time location of the sample user; based on the number of the initial models, the sample data set is divided into multiple groups of training data and multiple groups of test data; the corresponding initial model is trained using each group of training data, and the corresponding trained initial model is tested using each group of test data, and based on the test results, the preset content prediction model with the required prediction accuracy is selected from each trained initial model. Finally, the content cross feature vector is input into the preset content prediction model for content prediction, and the preset content prediction model can output the predicted content of interest to the target user. For example, the predicted content of interest can be a certain brand of air cushion, essence water in a certain price range, etc.

[0094] 205. Perform similarity matching between the predicted content of interest and the reserved page content, and based on the matching result, determine the actual page content of interest to the target user in the reserved page content.

[0095] For the embodiment of the present invention, since the predicted content of interest only expresses the user's interested products, etc., and is not standard content information, it is necessary to perform similarity matching between the predicted content of interest and the reserve page content, so as to determine the target user's actual page content of interest in the reserve page content. Based on this, step 205 specifically includes: determining the content feature vector corresponding to each of the reserve page contents; clustering each of the reserve page contents based on each of the content feature vectors to obtain reserve page contents under different clustering categories; classifying the predicted content of interest based on the different clustering categories to obtain the target clustering category to which the predicted content of interest belongs, and performing similarity matching between the predicted content of interest and the reserve page content under the target clustering category; and In the method, based on each of the content feature vectors, each of the reserve page contents is clustered to obtain the reserve page contents under different clustering categories, including: initializing the centroid vectors corresponding to different clusters; calculating the distance between the content feature vector and the centroid vector corresponding to the different clusters, and based on the distance, dividing each of the reserve page contents into the different clusters; based on the content feature vectors corresponding to the reserve page contents in the different clusters, obtaining the updated centroid vectors corresponding to the different clusters; based on the updated centroid vectors, re-dividing each of the reserve page contents into the different clusters until the updated centroid vectors do not change, and determining the reserve page contents finally divided into the different clusters as the reserve page contents under different clustering categories.

[0096] Specifically, in order to improve the efficiency of similarity matching and thus improve the display efficiency of personalized pages, it is first necessary to cluster the contents of each reserve page. During the clustering process, first select the centroid vectors corresponding to the initial centroids corresponding to the K clusters, and for the content feature vectors corresponding to the contents of each reserve page (wherein the content feature vectors corresponding to the contents of each reserve page can be determined by word embedding and other methods), calculate the distance between each content feature vector and the K centroid vectors, and assign each content feature vector to the cluster corresponding to the centroid vector closest to it. Then, for each cluster, recalculate the centroid of each cluster and its corresponding centroid vector, and re-divide the contents of each reserve page into different clusters, so as to continuously divide the contents of each reserve page until the position of the centroid does not change, that is, the centroid vector does not change, and finally determine the reserve page contents divided into different clusters as reserve page contents under different clustering categories.

[0097] Furthermore, after determining different clustering categories, the predicted content of interest is classified according to the centroid vectors corresponding to different clustering categories, that is, the predicted feature vector corresponding to the predicted content of interest is first determined, and the distances between the predicted feature vector and the centroid vectors corresponding to different clustering categories are calculated, and the predicted content of interest is divided into the target clustering category with the nearest distance. Then, the predicted content of interest is matched with the reserve page content in the target clustering category for similarity, so as to find the actual page content of interest that matches the predicted content of interest in the reserve page content in the target clustering category. For example, if different clustering categories include: lotion, essence, liquid foundation, etc., and the predicted content of interest is a spray with a price range of 100-200, then the target clustering category it belongs to is lotion, and then the actual page content of interest that matches the predicted content of interest is found in the reserve page contents corresponding to the lotion, such as a spray of a certain brand with a price range of 100-200. Therefore, by clustering the contents of each reserve page and then classifying the predicted content of interest, it is possible to avoid wasting time on similarity matching of predicted content of interest with irrelevant reserve page content, thereby improving the efficiency of similarity matching and further improving the display efficiency of personalized pages.

[0098] 206. Based on the dynamic value information and content feature information of the actual page content of interest, determine the target page content whose quality and influence meet the preset conditions in the actual page content of interest.

[0099] Among them, the preset conditions are set according to actual needs. Specifically, there are multiple pages of actual interest. In order to further ensure that the displayed page content is what the user needs and to ensure the quality of the page content, it is necessary to determine the target page content with high popularity, high influence, high quality and unique style in each page of actual interest based on the dynamic value information such as the popularity and influence of the actual page of interest, as well as the content feature information such as quality and style, so as to make the displayed page content more attractive to users, meet the personalized needs of users, and enhance the user experience. At the same time, high popularity, high influence, high quality and other content are often easy to resonate with users and share desires. Through the dissemination of social media, it can quickly expand the audience range of the content and enhance the popularity and influence of the platform.

[0100] 207. Based on the device attribute information, dynamically display a personalized page corresponding to the target page content to the target user.

[0101] For the embodiment of the present invention, in order to improve the display effect of the personalized page, it is necessary to configure the target page content in the page according to the device attribute information such as the screen size information, screen resolution information, pixel density, operating system information, etc. of the mobile device used by the user, so as to form a personalized page. Based on this, step 207 specifically includes: based on the screen size information and screen resolution information, determining the page layout and content area size of the target page content in the page to be displayed; based on the pixel density, determining the display resolution of the page to be displayed; based on the operating system information, determining the interactive adaptation method of the page to be displayed; based on the page layout, content area size, display resolution, and interactive adaptation method, configuring the target page content in the page to be displayed, obtaining the personalized page of the target user, and displaying the personalized page to the target user.

[0102] Specifically, screen size is usually measured in inches, which indicates the diagonal length of the screen, and determines the size of the visible area that users can see; screen resolution refers to the number of pixels on the screen, usually expressed as the pixel value of "width × height", which determines the fineness and clarity of the content that the screen can display. For example, if the screen resolution is 1024x768, 1366x768 or 1920x1080, etc., according to the design requirements and the content characteristics of the target page content, choose a suitable ratio to plan the page layout, such as the golden ratio (1:1.618), equal ratio (such as 1:1, 4:3, 16:9, etc.) or a custom ratio based on the target content. Then, the page is divided into multiple areas through the grid system, each of which has a clear width and height. The grid system helps to keep the page layout neat and consistent. According to the planning of the page layout and the grid system, determine the specific area size of the target page content in the page to be displayed, including the width and height of the content and the spacing with other page elements. At the same time, responsive design technology can also be used to enable the page to automatically adjust the layout and content area size according to different screen sizes and resolutions, such as flexible layout (Flexbox) and other technologies. Furthermore, pixel density refers to the number of pixels per inch of the screen, which determines the fineness of the screen display content. The higher the pixel density, the finer the image displayed on the screen and the richer the details. After determining the pixel density of the mobile device, the display resolution can be set by calculating or querying the standard resolution of the mobile device. Furthermore, the page layout is designed according to the layout specifications of the operating system (such as the height of the navigation bar, the height of the status bar, etc.) to ensure that a good layout effect can be maintained on different operating systems. At the same time, the interactive adaptation method is designed according to the interactive habits of the operating system (such as sliding, clicking, long pressing, etc.) to improve the user experience. Therefore, by configuring and displaying personalized pages according to the device attribute information of the mobile device used by the user, it can be ensured that the page content can be clearly and completely displayed to the user under different screen sizes, resolutions, operating systems, etc., thereby improving the user experience.

[0103] According to another method for displaying page content provided by the present invention, compared with the current method of displaying the same page to all users based on promotional activities or product popularity, the present invention can determine the display content type corresponding to the target application and the target store corresponding to the display content type through the real-time location information of the target user, and determine the target user's page content of interest based on the target user's user characteristic information, historical behavior information, real-time location attribute information, dynamic value information and content characteristic information of the reserved page content in the target store, and display a personalized page containing the page content of interest to the target user based on the device attribute information of the mobile device used by the target user, thereby determining the target user's page content of interest by comprehensively analyzing the target user's real-time location information, user characteristic information, device attribute information, historical behavior information, real-time location attribute information of the real-time location, dynamic value information and content characteristic information of the reserved page content, which can improve the accuracy of determining the page content, thereby ensuring that the page content displayed to the user is the user's actual need and content of interest, thereby improving the user experience and meeting the personalized needs of different users.

[0104] Further, as Figure 1 In a specific implementation, an embodiment of the present invention provides a device for displaying page content, such as Figure 3 As shown, the device includes: a first acquisition unit 31, a determination unit 32, a second acquisition unit 33, and a display unit 34.

[0105] The first acquisition unit 31 can be used to respond to a page content acquisition signal from a target user for a target application, and acquire the target user's real-time location information, user feature information, device attribute information of the mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the target user's real-time location.

[0106] The determining unit 32 may be configured to determine the display content type corresponding to the target application based on the real-time location information, and determine the target store corresponding to the display content type.

[0107] The second acquisition unit 33 may be used to acquire dynamic value information and content feature information of the reserve page content corresponding to the target store.

[0108] The display unit 34 can be used to determine the target page content that the target user is interested in from the reserve page content based on the user characteristic information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content characteristic information, and dynamically display the personalized page corresponding to the target page content to the target user based on the device attribute information.

[0109] In a specific application scenario, in order to obtain the real-time location information of the target user, the first acquisition unit 31 can be specifically used to obtain the real-time location information of the target user using multiple positioning methods, wherein the multiple positioning methods include at least two positioning methods selected from the group consisting of GPS positioning method, WiFi positioning method, IP address positioning method, base station positioning method, Bluetooth positioning method, geomagnetic positioning method, and inertial navigation positioning method.

[0110] The first acquisition unit 31 can be specifically used to send real-time location information acquisition requests to the target user based on various positioning methods; determine the target positioning method for obtaining the consent information returned by the target user among the various positioning methods, and acquire the real-time location information of the target user based on the target positioning method.

[0111] In a specific application scenario, the display content types include: single-store content type, multi-store content type, domestic multi-store duty-paid content type, and overseas content type; Figure 4 As shown, in order to determine the display content type corresponding to the target application, the determination unit 32 includes a judgment module 321 and a first determination module 322 .

[0112] The determination module 321 may be configured to determine, based on the real-time location information, whether there is a short-distance store involved in the target application within a preset distance corresponding to the target user.

[0113] The first determination module 322 may be configured to determine a single-store content type of the target application for the short-distance store if the short-distance store exists within the preset distance.

[0114] The determination module 321 may also be configured to determine whether the target user is within a target area based on the real-time location information if there is no store within the preset distance.

[0115] The first determination module 322 may also be used to determine multiple regional stores in the target area involved by the target application if the target user is in the target area, and determine the multiple store content types that the target application corresponds to in common for each of the regional stores.

[0116] The determination module 321 may also be used to determine whether the target user is in the country based on the real-time location information if the target user is not in the target area.

[0117] The first determination module 322 may also be used to determine the domestic stores involved in the target application if the target user is in China, and to determine the domestic multi-store tax-paid content type corresponding to each of the domestic stores that the target application corresponds to.

[0118] The first determination module 322 may also be used to determine the cross-border commodity information involved in the target application if the target user is not in China, and determine the overseas content type that the target application corresponds to for each cross-border commodity information.

[0119] In a specific application scenario, in order to determine the target store corresponding to the display content type, the first determination module 322 can also be used to determine the short-distance store corresponding to the single-store content type; or, determine the regional stores corresponding to the multi-store content type; or, determine the domestic stores corresponding to the domestic multi-store duty-paid content type; or, determine the cross-border commodity supply store to which the cross-border commodity information corresponding to the overseas content type belongs.

[0120] In a specific application scenario, in order to determine the target page content that the target user is interested in, the display unit 34 includes a second determination module 341 and a matching module 342 .

[0121] The second determination module 341 may be configured to determine the predicted content of interest of the target user based on the user feature information, the historical behavior information, and the real-time location attribute information.

[0122] The matching module 342 may be used to perform similarity matching between the predicted content of interest and the reserved page content, and determine the actual page content of interest to the target user in the reserved page content based on the matching result.

[0123] The second determination module 341 may be specifically configured to determine target page content whose quality and influence meet preset conditions in the actual interest page content based on the dynamic value information and content feature information of the actual interest page content.

[0124] In a specific application scenario, in order to determine the predicted content of interest to the target user, the second determination module 341 can be specifically used to respectively determine the user feature vector corresponding to the user feature information, the behavior feature vector corresponding to the historical behavior information, and the location feature vector corresponding to the real-time location attribute information; cross-process the user feature vector, the behavior feature vector, and the location feature vector to obtain a content cross-feature vector; input the content cross-feature vector into a preset content prediction model to perform content prediction to obtain the predicted content of interest to the target user.

[0125] In a specific application scenario, in order to perform similarity matching between the predicted content of interest and the reserve page content, the matching module 342 can be specifically used to determine the content feature vector corresponding to each of the reserve page contents; based on each of the content feature vectors, cluster the content of each of the reserve pages to obtain the reserve page content under different clustering categories; based on the different clustering categories, classify the predicted content of interest to obtain the target clustering category to which the predicted content of interest belongs, and perform similarity matching between the predicted content of interest and the reserve page content under the target clustering category.

[0126] In a specific application scenario, in order to cluster the contents of each reserve page, the matching module 342 can also be used to initialize the centroid vectors corresponding to different clusters; calculate the distance between the content feature vector and the centroid vectors corresponding to the different clusters, and based on the distance, divide the contents of each reserve page into the different clusters; based on the content feature vectors corresponding to the reserve page contents in the different clusters, obtain the updated centroid vectors corresponding to the different clusters; based on the updated centroid vectors, re-divide the contents of each reserve page into the different clusters until the updated centroid vector does not change, and determine the reserve page contents finally divided into the different clusters as reserve page contents under different clustering categories.

[0127] In a specific application scenario, the device attribute information includes: screen size information, screen resolution information, pixel density, and operating system information of the mobile device used by the target user; in order to display the personalized page, the display unit 34 also includes a display module 343.

[0128] The second determination module 341 may also be used to determine the page layout and content area size of the target page content in the page to be displayed based on the screen size information and the screen resolution information.

[0129] The second determination module 341 may also be configured to determine a display resolution of the to-be-displayed page based on the pixel density.

[0130] The second determination module 341 may also be used to determine the interaction adaptation mode of the to-be-displayed page based on the operating system information.

[0131] The display module 343 can be used to configure the target page content in the page to be displayed based on the page layout, content area size, display resolution, and interactive adaptation method, obtain a personalized page for the target user, and display the personalized page to the target user.

[0132] It should be noted that for other corresponding descriptions of the functional modules involved in the device for displaying page content provided in the embodiment of the present invention, reference can be made to Figure 1 The corresponding description of the method shown will not be repeated here.

[0133] Based on the above Figure 1 The method shown, accordingly, an embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are implemented: in response to a target user's page content acquisition signal for a target application, the target user's real-time location information, user characteristic information, device attribute information of the mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the real-time location of the target user are acquired; based on the real-time location information, the display content type corresponding to the target application is determined, and the target store corresponding to the display content type is determined; the dynamic value information and content feature information of the reserve page content corresponding to the target store are acquired; based on the user characteristic information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content feature information, the target page content of interest to the target user is determined in the reserve page content, and based on the device attribute information, the personalized page corresponding to the target page content is dynamically displayed to the target user.

[0134] Based on the above Figure 1 The method shown and Figure 3 The embodiment of the device shown in the figure, the embodiment of the present invention also provides a physical structure diagram of a computer device, such as Figure 5As shown, the computer device includes: a processor 41, a memory 42, and a computer program stored in the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43, and the processor 41 implements the following steps when executing the program: in response to a target user acquiring a page content acquisition signal for a target application, acquiring the target user's real-time location information, user feature information, device attribute information of the mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the real-time location of the target user; based on the real-time location information, determining the display content type corresponding to the target application, and determining the target store corresponding to the display content type; acquiring the dynamic value information and content feature information of the reserve page content corresponding to the target store; based on the user feature information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content feature information, determining the target page content of interest to the target user in the reserve page content, and dynamically displaying the personalized page corresponding to the target page content to the target user based on the device attribute information.

[0135] Through the technical solution of the present invention, the present invention can determine the display content type corresponding to the target application and the target store corresponding to the display content type through the real-time location information of the target user, and determine the target user's page content of interest based on the target user's user feature information, historical behavior information, real-time location attribute information, dynamic value information and content feature information of the reserve page content in the target store, and display a personalized page containing the page content of interest to the target user based on the device attribute information of the mobile device used by the target user, thereby determining the target user's page content of interest through comprehensive analysis of the target user's real-time location information, user feature information, device attribute information, historical behavior information, real-time location attribute information of the real-time location, dynamic value information and content feature information of the reserve page content, which can improve the accuracy of determining the page content, thereby ensuring that the page content displayed to the user is the user's actual needs and content of interest, thereby improving the user experience and meeting the personalized needs of different users.

[0136] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0137] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for displaying page content, characterized in that: include: In response to a target user acquiring a page content acquisition signal for a target application, acquiring the target user's real-time location information, user feature information, device attribute information of a mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the target user's real-time location; Based on the real-time location information, determining a display content type corresponding to the target application, and determining a target store corresponding to the display content type; Obtaining dynamic value information and content feature information of the reserve page content corresponding to the target store; Based on the user characteristic information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content characteristic information, the target page content that the target user is interested in is determined in the reserve page content, and based on the device attribute information, a personalized page corresponding to the target page content is dynamically displayed to the target user.

2. The method according to claim 1, characterized in that The obtaining of the real-time location information of the target user includes: Acquire the real-time location information of the target user by using multiple positioning methods, wherein the multiple positioning methods include at least two positioning methods selected from the group consisting of GPS positioning method, WiFi positioning method, IP address positioning method, base station positioning method, Bluetooth positioning method, geomagnetic positioning method, and inertial navigation positioning method; The method of obtaining the real-time location information of the target user by using multiple positioning methods includes: Based on various positioning methods, respectively send a real-time location information acquisition request to the target user; A target positioning method for obtaining consent information returned by the target user is determined among various positioning methods, and real-time location information of the target user is obtained based on the target positioning method.

3. The method according to claim 1, characterized in that The display content types include: single-store content type, multi-store content type, domestic multi-store duty-paid content type, and overseas content type; The determining, based on the real-time location information, a display content type corresponding to the target application program includes: Based on the real-time location information, determining whether there is a short-distance store involved in the target application within a preset distance corresponding to the target user; If the short-distance store exists within the preset distance, determining a single-store content type of the target application for the short-distance store; If there is no store within the preset distance, determining whether the target user is within the target area based on the real-time location information; If the target user is in the target area, then determining multiple regional stores in the target area involved by the target application, and determining multiple store content types that the target application corresponds to in common with each of the regional stores; If the target user is not in the target area, determining whether the target user is in the country based on the real-time location information; If the target user is in China, then determine the domestic stores involved in the target application, and determine the domestic multi-store tax-paid content type that the target application corresponds to for each of the domestic stores; If the target user is not in China, determining the cross-border commodity information involved in the target application, and determining the overseas content type that the target application corresponds to for each cross-border commodity information; The determining of a target store corresponding to the display content type includes: determining a short-distance store corresponding to the single-store content type; or, Determine each of the regional stores corresponding to the multi-store content type; or, Determine each of the domestic stores corresponding to the domestic multiple stores tax-paid content type; or, Determine a cross-border commodity supply store to which each cross-border commodity information corresponding to the overseas content type belongs.

4. The method according to claim 1, characterized in that: The determining, based on the user characteristic information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content characteristic information, the target page content that the target user is interested in from the reserve page content includes: Determining predicted content of interest to the target user based on the user feature information, the historical behavior information, and the real-time location attribute information; Performing similarity matching between the predicted interesting content and the reserved page content, and determining the actual interesting page content of the target user in the reserved page content based on the matching result; Based on the dynamic value information and content feature information of the actual page content of interest, target page content whose quality and influence both meet preset conditions is determined in the actual page content of interest.

5. The method according to claim 4, characterized in that The determining the predicted content of interest to the target user based on the user feature information, the historical behavior information, and the real-time location attribute information includes: Respectively determining a user feature vector corresponding to the user feature information, a behavior feature vector corresponding to the historical behavior information, and a location feature vector corresponding to the real-time location attribute information; Cross-processing the user feature vector, the behavior feature vector, and the position feature vector to obtain a content cross-feature vector; The content cross feature vector is input into a preset content prediction model to perform content prediction, so as to obtain the predicted content of interest to the target user.

6. The method according to claim 4, characterized in that The similarity matching of the predicted interesting content with the reserved page content includes: Determining a content feature vector corresponding to each of the reserve page contents; Based on each of the content feature vectors, clustering processing is performed on the content of each of the reserve pages to obtain the reserve page content under different clustering categories; Based on the different cluster categories, the predicted interesting content is classified to obtain the target cluster category to which the predicted interesting content belongs, and the predicted interesting content is matched with the reserve page content under the target cluster category by similarity; The clustering process of each of the reserve page contents based on each of the content feature vectors to obtain reserve page contents under different clustering categories includes: Initialize the centroid vectors corresponding to different clusters; Calculating the distance between the content feature vector and the centroid vectors corresponding to the different clusters, and dividing the contents of each of the reserve pages into the different clusters based on the distance; Based on the content feature vectors corresponding to the reserve page contents in the different clusters, obtaining updated centroid vectors corresponding to the different clusters; Based on the updated centroid vector, each of the reserve page contents is re-divided into the different clusters until the updated centroid vector does not change, and the reserve page contents finally divided into the different clusters are determined as reserve page contents under different clustering categories.

7. The method according to claim 1, characterized in that The device attribute information includes: screen size information, screen resolution information, pixel density, and operating system information of the mobile device used by the target user; The dynamically displaying a personalized page corresponding to the target page content to the target user based on the device attribute information includes: Based on the screen size information and the screen resolution information, determine the page layout and content area size of the target page content in the page to be displayed; Based on the pixel density, determining a display resolution of the page to be displayed; Based on the operating system information, determining an interactive adaptation mode of the page to be displayed; Based on the page layout, content area size, display resolution, and interactive adaptation method, the target page content is configured in the page to be displayed, a personalized page for the target user is obtained, and the personalized page is displayed to the target user.

8. A device for displaying page content, characterized in that: include: A first acquisition unit is used to acquire, in response to a target user's page content acquisition signal for a target application, the target user's real-time location information, user feature information, device attribute information of a mobile device used, historical behavior information for the content in the target application, and real-time location attribute information of the target user's real-time location; a determination unit, configured to determine, based on the real-time location information, a display content type corresponding to the target application, and determine a target store corresponding to the display content type; A second acquisition unit is used to acquire dynamic value information and content feature information of the reserve page content corresponding to the target store; A display unit is used to determine the target page content that the target user is interested in from the reserve page content based on the user characteristic information, the historical behavior information, the real-time location attribute information, the dynamic value information, and the content characteristic information, and dynamically display a personalized page corresponding to the target page content to the target user based on the device attribute information.

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

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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