Data display method and device, electronic equipment and storage medium

Abstract

The invention discloses a data display method and device, electronic equipment and a storage medium. The data display method comprises the steps of obtaining at least one of object information of a target object and browsing information of a browsing scene; based on at least one of the object information and the browsing information, determining a next browsing area adaptive to the target object in a plurality of areas of the browsing scene; and the virtual display data corresponding to the next browsing area is obtained from the cloud, and the virtual display data is displayed on the display equipment of the target object, so that personalized display of the browsing area is realized, and the experience feeling of a user is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a data display method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the recovery and rapid development of the cultural and tourism market, high-quality culture and tourism are becoming increasingly important in people's daily lives. The "Action Plan for the Integration and Development of Virtual Reality and Industry Applications (2022-2026)" issued by the Ministry of Culture and Tourism clearly proposes to combine cultural tourism with virtual reality, accelerate the implementation of multi-scenario applications in the industry, promote the development of interactive and immersive digital experience products in scenic spots, resorts, and districts, and develop new tourism services such as immersive interactive experiences, virtual displays, and smart guides.

[0003] Existing technologies combine physical and virtual environments to provide users with immersive tour areas. However, because different tourists have different preferences, it is impossible to provide immersive tour areas tailored to the actual preferences of each tourist, resulting in a poor user experience. Summary of the Invention

[0004] This invention provides a data display method, apparatus, electronic device, and storage medium to achieve personalized determination of the browsing area and enhance the user's immersive experience.

[0005] According to one aspect of the present invention, a data display method is provided, the method comprising:

[0006] Obtain at least one of the following: object information of the target object and browsing information of the browsing scene;

[0007] Based on at least one of object information and browsing information, determine the next browsing area adapted to the target object within multiple areas of the browsing scene;

[0008] The virtual display data corresponding to the next browsing area is retrieved from the cloud and displayed on the target object's display device.

[0009] According to another aspect of the present invention, a data display device is provided, the device comprising:

[0010] The information acquisition module is used to acquire at least one of the object information of the target object and the browsing information of the browsing scene;

[0011] The browsing area determination module is used to determine the next browsing area adapted to the target object from multiple areas in the browsing scene based on at least one of object information and browsing information.

[0012] The virtual display data display module is used to retrieve the virtual display data corresponding to the next browsing area from the cloud and display the virtual display data on the target object's display device.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] At least one processor; and

[0015] A memory that is communicatively connected to at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the data display method provided in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the data display method provided in any embodiment of the present invention.

[0018] The technical solution of this invention achieves the acquisition of object information and browsing information of the target object by obtaining at least one of the object information and browsing information of the browsing scene, providing accurate and comprehensive data support for subsequent analysis and processing. Based on at least one of the object information and browsing information, the next browsing area adapted to the target object is determined in multiple areas of the browsing scene, achieving accurate determination of the next browsing area adapted to the target object, improving the personalization of the next browsing area, making the next browsing area more in line with the target object's preferences, and thus improving the target object's experience. The virtual display data corresponding to the next browsing area is obtained from the cloud and displayed on the target object's display device, achieving accurate determination of the next browsing area adapted to the target object, improving the personalization of the next browsing area, and thus making the next browsing area more in line with the target object's preferences. This solves the problem in the prior art that it is impossible to provide targeted tour areas according to the actual preferences of tourists, and achieves fast and low-latency transmission of virtual display data, which is conducive to improving the immersive experience of the target object.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a data display method provided in Embodiment 1 of the present invention;

[0022] Figure 2 This is a flowchart of a data display method provided in Embodiment 2 of the present invention;

[0023] Figure 3 This is a schematic diagram of the structure of a data display device provided in Embodiment 3 of the present invention;

[0024] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Example 1

[0028] Figure 1This is a flowchart of a data display method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where personalized prediction and display of a browsing area are performed. The method can be executed by a data display device, which can be implemented in hardware and / or software. This data display device can be configured in the electronic device provided in this embodiment of the invention. The electronic device can be a server, computer, or mobile terminal, such as a mobile phone or tablet computer. Figure 1 As shown, the method includes:

[0029] S110. Obtain at least one of the following: object information of the target object and browsing information of the browsing scene.

[0030] This invention is applicable to providing users with personalized tour areas through virtual devices. Application scenarios include, but are not limited to, scenic area scenarios, resort scenarios, and shopping scenarios. This invention uses a scenic area scenario as an example. The target audience includes, but is not limited to, tourists in scenic areas. The target audience information describes the tour habits and preferences of the target audience. The target audience information can be the same or different for different target audiences. The target audience information includes, but is not limited to, liking shopping, being socially active, and liking to travel. The tour scenario is the environment in which the target audience performs tour behavior. The tour scenario can include virtual tour scenarios and / or real tour scenarios. Depending on the service type, the tour scenario can be divided into different areas, including at least one of display areas, interactive areas, and service areas. Tour information is data describing the tour status and behavioral trajectory of the target audience within the tour scenario. In a virtual tour scenario, the tour information can include the tour status and behavioral trajectory of the target audience in the virtual tour area corresponding to the actual tour area. In a real tour scenario, the tour information can include the tour status and behavioral trajectory of the target audience in the actual tour area. Object information and browsing information can be obtained from the cloud. The cloud has a database that can store object information and browsing information for multiple objects. By matching the unique identification information of the target object in the database, the object information and browsing information of the target object can be determined.

[0031] Specifically, by matching the unique identification information of the target object in the database, the object information and browsing information of the target object are determined, thus realizing the acquisition of the object information and browsing information of the target object and providing accurate and comprehensive data support for subsequent analysis and processing.

[0032] S120. Based on at least one of object information and browsing information, determine the next browsing area adapted to the target object within multiple areas of the browsing scene.

[0033] The next browsing area is defined as a browsing region that matches the browsing habits and preferences of the target audience. The next browsing area can be determined based on object information, browsing information, or both. Taking object information and browsing information as an example, the object information and browsing information are input into a trained browsing area determination model for prediction, resulting in a next browsing area adapted to the target audience. This model includes, but is not limited to, neural network models.

[0034] Specifically, object information and browsing information are input into a trained browsing area determination model for prediction, resulting in the next browsing area adapted to the target object. This achieves personalized determination of the next browsing area and provides accurate data support for subsequent display.

[0035] After obtaining object and browsing information, data cleaning and preprocessing operations can be performed on this information. Data cleaning includes, but is not limited to, handling missing values ​​and removing outliers, while data preprocessing includes, but is not limited to, data format conversion, normalization, and unstructured data conversion. Since unstructured data exists in the object and browsing information, it can be processed. For example, one-hot encoding can be used to convert the unstructured data in the object and browsing information into structured data.

[0036] Optionally, based on at least one of object information and browsing information, determine the next browsing area suitable for the target object in multiple areas of the browsing scene. Specifically, this includes: analyzing the browsing information using the current LSTM model to obtain the next browsing area suitable for the target object, wherein the current LSTM model is obtained by adjusting the model parameters of a pre-trained LSTM model based on the browsing information of the target object.

[0037] The current Long Short-Term Memory (LSTM) model is used to determine the next browsing region suitable for the target object. The next browsing region can be determined based on browsing information. For example, the browsing information of the target object is input into the current LSTM model for analysis to obtain the next browsing region suitable for the target object. The pre-trained LSTM model is a base LSTM model trained using browsing information from different objects. The current LSTM model and the pre-trained LSTM model have the same model structure, but their model parameters differ. The current LSTM model can be derived from the pre-trained LSTM model. For example, the browsing information of the target object and browsing information from multiple different objects are used as multiple training samples to train the pre-trained LSTM model. By adjusting the model parameters of the pre-trained LSTM model, a pre-trained LSTM model with adjusted parameters is obtained, and this adjusted pre-trained LSTM model is used as the current LSTM model.

[0038] Specifically, the browsing information of the target object and browsing information of multiple different objects are used as multiple training samples to train the pre-trained LSTM model. By adjusting the model parameters of the pre-trained LSTM model, a pre-trained LSTM model with adjusted model parameters is obtained. The pre-trained LSTM model with adjusted model parameters is used as the current LSTM model. The browsing information of the target object is input into the current LSTM model for analysis to obtain the next browsing area adapted to the target object. This achieves accurate determination of the next browsing area adapted to the target object, which is beneficial to improving the user experience of the target object.

[0039] Optionally, the data display method may also include: obtaining the browsing information of the target object in the next browsing area, and updating the current LSTM model based on the browsing information of the target object in the next browsing area.

[0040] Specifically, the browsing information of the target object in the next browsing area is obtained from the cloud. The current LSTM model is trained based on the browsing information of the target object in the next browsing area, and the model parameters of the current LSTM model are adjusted to obtain an updated current LSTM model. By updating the current LSTM model, the accuracy of personalized determination of the browsing area can be improved, thereby improving the user experience.

[0041] Optionally, determining the next browsing area adapted to the target object within multiple areas of the browsing scenario based on at least one of object information and browsing information further includes: determining the next browsing area adapted to the target object based on at least two browsing area determination methods, wherein the at least two browsing area determination methods include a determination method based on an LSTM model and a determination method based on browsing information of similar users.

[0042] The determination method based on the LSTM model involves inputting object information and / or browsing information into a trained LSTM model for analysis. The analysis process is as follows: the browsing information of the target object is input into the trained LSTM model to obtain a first predicted next browsing area and its corresponding first probability value. The determination method based on similar user browsing information involves identifying and analyzing similar users who have similar selection patterns to the target object and their corresponding browsing information. Similar users can include one or multiple users. Similar users can be determined by similarity, including but not limited to cosine similarity. For example, browsing information of the target object and browsing information of multiple users can be obtained from the cloud. The cosine similarity between the target object's browsing information and each user's browsing information is calculated, and users with cosine similarity scores greater than or equal to a preset similarity threshold are considered similar users. Taking multiple similar users as an example, the analysis process for determining the browsing information of similar users is as follows: Obtain the browsing information of multiple users from the cloud, calculate the cosine similarity between the browsing information of the target object and the browsing information of each user, and take the users whose cosine similarity is greater than or equal to the preset similarity threshold as similar users. Determine the frequency of each browsing area based on the browsing information of similar users, take the above frequency as the second probability value of each browsing area, and take the browsing area with the largest second probability value as the second predicted next browsing area.

[0043] Specifically, the browsing information of the target object is input into a trained LSTM model to obtain a first predicted next browsing region and its corresponding first probability value. Browsing information from multiple users is obtained from the cloud, and the cosine similarity between the target object's browsing information and each user's browsing information is calculated. Users with cosine similarities greater than or equal to a preset similarity threshold are considered similar users. The frequency of each browsing region is determined based on the browsing information of similar users, and this frequency is used as the second probability value for each browsing region. The browsing region with the largest second probability value is selected as the second predicted next browsing region. The predicted next browsing region corresponding to the largest probability value between the first and second probability values ​​is used as the next browsing region adapted to the target object, thus achieving accurate determination of the next browsing region adapted to the target object.

[0044] For example, the formula for calculating cosine similarity is as follows:

[0045] ;

[0046] Where p represents the user; q represents the target object; and N represents the number of browsing areas; This represents the user's browsing information in the i-th browsing area; This represents the browsing information of the target object in the i-th browsing area.

[0047] Based on the above embodiments, the next browsing area adapted to the target object can be determined solely based on the determination method of the LSTM model, or it can be determined solely based on the determination method of browsing information of similar users. The browsing area determination method can be selected according to the requirements, and there are no restrictions here.

[0048] It should be noted that for the initial browsing area of ​​the target object, the object information and browsing information of the target object do not exist in the cloud. The initial browsing area of ​​the target object can be determined using a clustering algorithm. As the target object browses within the browsing area, the object information and browsing information of the target object can be analyzed using an LSTM model to obtain the next browsing area suitable for the target object.

[0049] Optionally, the data display method may also include: updating the priority of at least two browsing area determination methods based on the next actual browsing area of ​​the target object.

[0050] When the target object selects the next actual browsing area, the accuracy of the determination method based on the LSTM model and the method based on browsing information of similar users are compared. The method with higher accuracy is prioritized for subsequent determination of the target object's browsing area. For example, the first predicted browsing area determined by the LSTM model is area A, with a probability value of 0.85. The second predicted browsing area determined by the method based on browsing information of similar users is area B, with a probability value of 0.88. Since 0.88 is greater than 0.85, area B is chosen as the next browsing area for the target object, and the next actual browsing area for the target object is area A. Area A is the area determined by the LSTM model, indicating that the LSTM model-based method is more accurate than the method based on browsing information of similar users. Therefore, the priority of the LSTM model-based method is higher than that of the method based on browsing information of similar users, which is beneficial to improving the accuracy of subsequent analysis.

[0051] S130. Obtain the virtual display data corresponding to the next browsing area from the cloud and display the virtual display data on the target object's display device.

[0052] The virtual display data refers to the digitized data of the browsing area. This data includes, but is not limited to, 3D models. The display device serves as the medium connecting the target object and the cloud. Virtual display data can be obtained from the cloud. The cloud can store virtual display data for different browsing areas in different browsing scenarios. By matching the unique identifier of the next browsing area in the cloud, the virtual display data corresponding to that area can be retrieved. Display devices include, but are not limited to, virtual reality devices and augmented reality devices. The target object can interact with the virtual display data. For example, taking a product area as an example, the target object can click on a product to view its detailed information, including but not limited to its features, price, and usage instructions. The cloud and the display device can be connected via communication, such as through a 5G network. 5G networks offer high bandwidth and low latency, enabling the rapid and low-latency transmission of the virtual display data for the next browsing area to the target object's display device.

[0053] Specifically, the system matches the unique identifier of the next browsing area in the cloud to obtain the virtual display data corresponding to the next browsing area. The cloud then sends the virtual display data corresponding to the next browsing area to the target object's display device via the 5G network. The target object's display device then displays the virtual display data, achieving fast and low-latency transmission of virtual display data, which helps improve the target object's experience.

[0054] The target object interacts with the virtual display data, and its browsing information can change. Optionally, the browsing information includes interaction information between the target object and the display data of different types of browsing objects in the virtual display data. These different types of browsing objects in the virtual display data are digital units within the virtual display data that can interact with the target object. Browsing objects can be categorized into different types based on their functions. Different types of browsing objects in the virtual display data include, but are not limited to, virtual attractions and virtual shops. Different types of browsing objects correspond to different display data. Taking a virtual shop as an example, a virtual shop includes different virtual products, and the display data of the virtual shop includes, but is not limited to, the shape, color, and position of the virtual products. The interaction information between the target object and the display data of different types of browsing objects in the virtual display data is the data generated when the target object interacts with the display data in the virtual browsing scenario through a display device. Different interactive behaviors correspond to different interaction information. The target object's interaction with the display data in the virtual browsing scenario includes, but is not limited to, viewing attraction introductions, browsing products, and purchasing products. The corresponding interaction information can be attraction viewing interaction information, product browsing interaction information, and product purchasing interaction information.

[0055] The target object interacts within the actual browsing area, and its browsing information may change. Optionally, the browsing information includes the target object's browsing behavior information regarding different types of browsing objects within the actual browsing area of ​​the browsing scene. These different types of browsing objects are objectively existing physical units in the real physical space corresponding to the browsing scene. The browsing behavior information is data generated by the target object's browsing behavior on these objectively existing physical units in the real physical space corresponding to the browsing scene. Browsing behavior includes, but is not limited to, viewing-based browsing behavior, interactive browsing behavior, and path-moving browsing behavior.

[0056] The target object interacts with both virtual display data and the actual browsing area, and its browsing information can change. Optionally, the browsing information includes interaction information between the target object and the display data of different types of browsing objects in the virtual display data, as well as the target object's browsing behavior information on different types of browsing objects in the actual browsing area of ​​the browsing scenario.

[0057] The technical solution of this embodiment achieves the acquisition of object information and browsing information of the target object by obtaining at least one of the object information and browsing information of the browsing scene, providing accurate and comprehensive data support for subsequent analysis and processing; based on at least one of the object information and browsing information, the next browsing area adapted to the target object is determined in multiple areas of the browsing scene, achieving accurate determination of the next browsing area adapted to the target object, improving the personalization of the next browsing area, making the next browsing area more in line with the target object's preferences, and improving the target object's experience; obtaining the virtual display data corresponding to the next browsing area from the cloud and displaying the virtual display data on the target object's display device achieves fast and low-latency transmission of virtual display data, which is conducive to improving the target object's immersive experience.

[0058] Example 2

[0059] Figure 2 This is a flowchart of a data display method provided in Embodiment 2 of the present invention. This embodiment is a refinement of the above embodiments. Based on the foregoing embodiments, it provides a more detailed explanation of determining the next browsing area adapted to the target object within multiple areas of a browsing scene based on at least one of object information and browsing information. Specific implementation methods can be found in the technical solution of this embodiment. Technical terms that are the same as or corresponding to those in the above embodiments will not be repeated here. Figure 2 As shown, the method includes:

[0060] S210. Obtain at least one of the following: object information of the target object and browsing information of the browsing scene.

[0061] S220. Obtain at least one of the object information and historical browsing information of the historical browsing objects in the browsing scene; based on at least one of the object information and browsing information, and at least one of the object information and historical browsing information of the historical browsing objects, determine similar objects of the target object in the historical browsing objects; determine the next browsing area adapted to the target object based on the historical browsing information of the similar objects and the current position of the target object.

[0062] Among them, "historical browsing objects" refers to users who have already viewed the browsing scenarios corresponding to the target object. The object information and historical browsing information of historical browsing objects in a browsing scenario can be obtained through cloud-based matching based on the unique identification information of the browsing scenario. Historical browsing information includes the historical browsing information of historical browsing objects in virtual browsing scenarios and / or the historical browsing information of historical browsing objects in real browsing scenarios.

[0063] Similar objects are historical browsing objects that exhibit similar browsing behavior to the target object. Similar objects can be determined based on the target object's object information and the object information of historical browsing objects, or based on the target object's browsing information and the historical browsing information of historical browsing objects, or based on both the target object's object information, browsing information, and the object and historical browsing information of historical browsing objects. Taking the determination of similar objects based on the target object's object information and the object information of historical browsing objects as an example, historical browsing objects with the same tags are identified as similar objects. Taking the determination of similar objects based on the target object's browsing information and the historical browsing information of historical browsing objects as another example, the browsing information of the target object and the historical browsing information of historical browsing objects are input into a trained clustering model for processing to obtain similar objects. Clustering models include, but are not limited to, neural network models. Taking the determination of similar objects based on object information, browsing information, and the object and historical browsing information of historical browsing objects as another example, the object and browsing information, as well as the object and historical browsing information of historical browsing objects, are input into a trained clustering model for processing to obtain similar objects.

[0064] The current location describes the physical spatial position of the target object within the browsing scene. The current location can include latitude and longitude information. It can be obtained through a positioning system. The next browsing area adapted to the target object can also be determined based on the historical browsing information of similar objects and the current location of the target object. For example, the historical browsing information of similar objects and the current location of the target object can be input into a trained browsing area determination model for analysis to obtain the next browsing area adapted to the target object. This browsing area determination model includes, but is not limited to, neural network models.

[0065] It should be noted that similar objects can also be calculated by measuring similarity. Similarity includes, but is not limited to, the similarity between the object information of the target object and the object information of previously viewed objects, the similarity between the browsing information of the target object and the historical browsing information of previously viewed objects, and the similarity between the object information of the target object and the object information of previously viewed objects, as well as the similarity between the browsing information of the target object and the historical browsing information of previously viewed objects. The method for determining similar objects is chosen according to requirements; no restrictions are imposed here.

[0066] Specifically, based on the unique identification information of the browsing scene, matching is performed in the cloud to obtain the object information and historical browsing information of the historical browsing objects in that browsing scene. The object information and browsing information, as well as the object information and historical browsing information of the historical browsing objects, are input into a trained clustering model for processing to obtain similar objects. The historical browsing information of similar objects and the current position of the target object are input into a trained browsing area determination model for analysis to obtain the next browsing area adapted to the target object, thus achieving accurate determination of the next browsing area adapted to the target object.

[0067] Optionally, the next browsing area adapted to the target object is determined based on the historical browsing information of similar objects and the current location of the target object, including: determining unbrowsed optional areas based on the current location of the target object; determining recommendation indicators for unbrowsed optional areas based on the similarity data between similar objects and the target object and the historical browsing information of similar objects regarding unbrowsed optional areas; and determining the next browsing area adapted to the target object based on the recommendation indicators of each unbrowsed optional area.

[0068] Unbrowsed selectable areas refer to regions within the browsing scene that the target object has not yet explored. Unbrowsed selectable areas can be determined based on the target object's current location and browsing information. For example, the target object's current browsing area is determined based on its current location, its already browsed areas are determined based on its browsing information, and unbrowsed selectable areas are determined based on its already browsed areas. Similarity data describes the degree of similarity between the target object and similar objects in browsing preferences, behavioral habits, and browsing area selection. Similarity data includes, but is not limited to, the similarity between the target object's object information and the object information of previously browsed objects, the similarity between the target object's browsing information and the historical browsing information of previously browsed objects, and the similarity between the target object's object information and the object information of previously browsed objects, as well as the similarity between the target object's browsing information and the historical browsing information of previously browsed objects. Similarity data can be determined using a similarity determination model. Taking the target object's object information and the object information of previously browsed objects as an example, inputting the target object's object information and the object information of previously browsed objects into a trained similarity determination model yields similarity data. Similarity determination models include, but are not limited to, mathematical models and neural network models.

[0069] Recommendation metrics characterize the fit between unviewed optional areas and the target object. Recommendation metrics include, but are not limited to, recommendation scores. Recommendation metrics can be determined based on similarity data between similar objects and the target object, and the historical browsing information of similar objects regarding unviewed optional areas. For example, similarity data between similar objects and the target object, and the historical browsing information of similar objects regarding unviewed optional areas, can be input into a trained metric determination model for processing to obtain recommendation metrics for unviewed optional areas. Metric determination models include, but are not limited to, mathematical models and neural network models. The next browsing area adapted to the target object can also be determined based on the recommendation metrics of each unviewed optional area. For example, the maximum value among the recommendation metrics can be determined, and the unviewed optional area corresponding to the maximum value recommendation metric can be used as the next browsing area adapted to the target object.

[0070] Specifically, the current browsing area of ​​the target object is determined based on its current location; the browsed area of ​​the target object is determined based on its browsing information; and unbrowsed optional areas are determined based on the browsed area. The object information of the target object and the object information of historically browsed objects are input into a trained similarity determination model for processing to obtain similarity data. The similarity data between similar objects and the target object, along with the historical browsing information of similar objects regarding unbrowsed optional areas, are input into a trained index determination model for processing to obtain recommended indices for unbrowsed optional areas. The maximum value among the recommended indices is determined, and the unbrowsed optional area corresponding to the maximum recommended index is used as the next browsing area adapted to the target object. This achieves accurate determination of the next browsing area adapted to the target object, making the next browsing area more in line with the target object's preferences.

[0071] S230: Obtain the virtual display data corresponding to the next browsing area from the cloud, and display the virtual display data on the display device of the target object.

[0072] Optionally, the data display method further includes: during the browsing process of the target object in the current browsing area, judging the location information of the target object based on the electronic fence of the current browsing area; when the distance between the target object and the switching area of ​​the current browsing area meets the set conditions, determining the next browsing area suitable for the target object in multiple areas of the browsing scene, wherein the switching area is the connected area between the current browsing area and other browsing areas.

[0073] In this context, an electronic fence defines the virtual boundary of the browsing area. Each browsing area has a unique electronic fence, which can be obtained from the cloud. The cloud may include an electronic fence database storing electronic fences for different browsing areas in different browsing scenarios. For example, matching the unique identifier of the current browsing area against the electronic fence database yields the electronic fence for that area. A switching area is the connecting region between the current browsing area and other browsing areas. Target objects can move between different browsing areas via switching areas. The next browsing area adapted to the target object can also be determined based on the target object's location information relative to the electronic fence of the current browsing area. For example, the distance between the target object and the switching area of ​​the current browsing area can be determined based on the target object's location information relative to the electronic fence of the current browsing area. When the distance between the target object and the switching area of ​​the current browsing area is less than or equal to a preset threshold, the browsing area corresponding to the switching area is used as the next browsing area adapted to the target object. Furthermore, when the distances between multiple target objects and the switching areas of the current browsing area are less than or equal to the preset threshold, the browsing area corresponding to the smallest of these distances is used as the next browsing area adapted to the target object.

[0074] Specifically, the electronic fence of the current browsing area is obtained by matching the unique identifier of the current browsing area in the electronic fence database. The distance between the target object and the switching area of ​​the current browsing area is determined based on the location information of the target object according to the electronic fence of the current browsing area. When the distance between the target object and the switching area of ​​the current browsing area is less than or equal to a preset threshold, the browsing area corresponding to the switching area is taken as the next browsing area adapted to the target object. This realizes the determination of the next browsing area adapted to the target object, so that the next browsing area of ​​the target object is adapted to the browsing rhythm of the target object.

[0075] The technical solution of this embodiment achieves the acquisition of object information and browsing information of the target object by obtaining at least one of the object information of the target object and browsing information of the browsing scene, providing accurate and comprehensive data support for subsequent analysis and processing; it acquires at least one of the object information and historical browsing information of the historical browsing objects in the browsing scene, and based on at least one of the object information and browsing information, as well as at least one of the object information and historical browsing information of the historical browsing objects, it identifies similar objects of the target object in the historical browsing objects, and determines the next browsing area suitable for the target object based on the historical browsing information of the similar objects and the current position of the target object, thereby improving the personalization of the next browsing area and making the next browsing area more in line with the target object's preferences and choices; it acquires the virtual display data corresponding to the next browsing area from the cloud and displays the virtual display data on the target object's display device, achieving fast and low-latency transmission of virtual display data, which is conducive to improving the immersive experience of the target object.

[0076] Example 3

[0077] Figure 3 This is a schematic diagram of the structure of a data display device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes an information acquisition module 310, a browsing area determination module 320, and a virtual display data display module 330.

[0078] The information acquisition module 310 is used to acquire at least one of the object information of the target object and the browsing information of the browsing scene; the browsing area determination module 320 is used to determine the next browsing area adapted to the target object in multiple areas of the browsing scene based on at least one of the object information and the browsing information; and the virtual display data display module 330 is used to acquire the virtual display data corresponding to the next browsing area from the cloud and display the virtual display data on the display device of the target object.

[0079] The technical solution of this embodiment, through the information acquisition module, acquires at least one of the object information of the target object and the browsing information of the browsing scene, realizing the acquisition of the object information and browsing information of the target object, providing accurate and comprehensive data support for subsequent analysis and processing; through the browsing area determination module, based on at least one of the object information and browsing information, it determines the next browsing area suitable for the target object from multiple areas of the browsing scene, realizing the accurate determination of the next browsing area suitable for the target object, improving the personalization of the next browsing area, making the next browsing area more in line with the target object's preferences, and helping to improve the target object's experience; through the virtual display data display module, it acquires the virtual display data corresponding to the next browsing area from the cloud and displays the virtual display data on the target object's display device, realizing fast and low-latency transmission of virtual display data, which helps to improve the target object's experience.

[0080] Based on the above embodiments, optionally, the browsing area determination module 320 is further configured to: obtain at least one of the object information and historical browsing information of the historical browsing objects in the browsing scene; determine similar objects of the target object in the historical browsing objects based on at least one of the object information and browsing information and at least one of the object information and historical browsing information of the historical browsing objects; and determine the next browsing area adapted to the target object based on the historical browsing information of the similar objects and the current position of the target object.

[0081] Optionally, the browsing area determination module 320 is further configured to: determine unbrowsed optional areas based on the current location of the target object; determine recommendation indicators for unbrowsed optional areas based on the similarity data between similar objects and the target object and the historical browsing information of similar objects regarding the unbrowsed optional areas; and determine the next browsing area suitable for the target object based on the recommendation indicators of each unbrowsed optional area.

[0082] Optionally, the browsing area determination module 320 is also used to: analyze the browsing information through the current LSTM model to obtain the next browsing area adapted to the target object, wherein the current LSTM model is obtained by adjusting the model parameters of a pre-trained LSTM model based on the browsing information of the target object.

[0083] Optionally, the data display device also includes a model update module, used to: obtain browsing information of the target object in the next browsing area, and update the current LSTM model based on the browsing information of the target object in the next browsing area.

[0084] Optionally, the browsing area determination module 320 is further configured to: determine the next browsing area adapted to the target object based on at least two browsing area determination methods, wherein the at least two browsing area determination methods include a determination method based on an LSTM model and a determination method based on browsing information of similar users.

[0085] Optionally, the data display device also includes a priority update module for: updating the priority of at least two browsing area determination methods based on the next actual browsing area of ​​the target object.

[0086] Optionally, the browsing area determination module 320 is also used to: determine the location information of the target object based on the electronic fence of the current browsing area during the browsing process of the target object in the current browsing area; when the distance between the target object and the switching area of ​​the current browsing area meets the set conditions, determine the next browsing area suitable for the target object in multiple areas of the browsing scene, wherein the switching area is the connected area between the current browsing area and other browsing areas.

[0087] Optionally, the browsing information includes interaction information between the target object and the display data of different types of browsing objects in the virtual display data.

[0088] Optionally, the browsing information includes the target object's browsing behavior information on different types of browsing objects in the actual browsing area of ​​the browsing scenario.

[0089] Optionally, the browsing information includes the interaction information between the target object and the display data of different types of browsing objects in the virtual display data, as well as the browsing behavior information of the target object on different types of browsing objects in the actual browsing area of ​​the browsing scene.

[0090] The data display device provided in this embodiment of the invention can execute a data display method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0091] Example 4

[0092] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0093] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0094] Multiple components in electronic device 10 are connected to input / output (I / O) interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0095] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a data visualization method.

[0096] In some embodiments, a data presentation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via read-only memory (ROM) 12 and / or communication unit 19. When the computer program is loaded into random access memory (RAM) 13 and executed by processor 11, one or more steps of a data presentation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform a data presentation method by any other suitable means (e.g., by means of firmware).

[0097] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0098] A computer program for implementing a data display method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer program causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0099] Example 5

[0100] Embodiment 5 of the present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to execute a data display method, the method comprising:

[0101] Obtain at least one of the object information of the target object and the browsing information of the browsing scene; based on at least one of the object information and the browsing information, determine the next browsing area adapted to the target object in multiple areas of the browsing scene; obtain the virtual display data corresponding to the next browsing area from the cloud, and display the virtual display data on the display device of the target object.

[0102] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0103] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0104] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0105] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0106] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0107] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data display method, characterized in that, include: Obtain at least one of the following: object information of the target object and browsing information of the browsing scene; Based on at least one of the object information and the browsing information, determine the next browsing area adapted to the target object within multiple areas of the browsing scene; The virtual display data corresponding to the next browsing area is obtained from the cloud, and the virtual display data is displayed on the display device of the target object.

2. The method according to claim 1, characterized in that, Based on at least one of the object information and the browsing information, determining the next browsing area adapted to the target object within multiple areas of the browsing scene includes: Obtain at least one of the object information and historical browsing information of the historical browsing objects in the browsing scenario; Based on at least one of the object information and the browsing information, and at least one of the object information and the historical browsing information of the historical browsing objects, determine similar objects to the target object in the historical browsing objects; The next browsing area suitable for the target object is determined based on the browsing history of the similar objects and the current location of the target object.

3. The method according to claim 2, characterized in that, The step of determining the next browsing area adapted to the target object based on the historical browsing information of the similar objects and the current position of the target object includes: Based on the current location of the target object, determine the unviewed selectable areas; Based on the similarity data between the similar objects and the target object, and the historical browsing information of the similar objects regarding the unbrowsed optional areas, the recommendation index for the unbrowsed optional areas is determined; Based on the recommendation metrics of each of the unvisited optional areas, the next browsing area suitable for the target object is determined.

4. The method according to claim 1, characterized in that, Based on at least one of the object information and the browsing information, determining the next browsing area adapted to the target object within multiple areas of the browsing scene includes: The browsing information is analyzed by the current LSTM model to obtain the next browsing area adapted to the target object. The current LSTM model is obtained by adjusting the model parameters of a pre-trained LSTM model based on the browsing information of the target object. Furthermore, the method further includes: obtaining browsing information of the target object in the next browsing area, and updating the current LSTM model based on the browsing information of the target object in the next browsing area.

5. The method according to claim 1, characterized in that, Based on at least one of the object information and the browsing information, determining the next browsing area adapted to the target object within multiple areas of the browsing scene includes: Based on at least two browsing area determination methods, the next browsing area adapted to the target object is determined, wherein the at least two browsing area determination methods include a determination method based on an LSTM model and a determination method based on browsing information of similar users; Furthermore, the method further includes: updating the priority of the at least two browsing area determination methods based on the next actual browsing area of ​​the target object.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: During the browsing process of the target object in the current browsing area, the location information of the target object is determined based on the electronic fence of the current browsing area; When the distance between the target object and the switching area of ​​the current browsing area meets a set condition, the next browsing area adapted to the target object is determined in multiple areas of the browsing scene, wherein the switching area is the connected area between the current browsing area and other browsing areas.

7. The method according to any one of claims 1-5, characterized in that, The browsing information includes interaction information between the target object and the display data of different types of browsing objects in the virtual display data; and / or, the browsing behavior information of the target object on different types of browsing objects in the actual browsing area of ​​the browsing scenario.

8. A data display device, characterized in that, include: The information acquisition module is used to acquire at least one of the object information of the target object and the browsing information of the browsing scene; A browsing area determination module is used to determine, based on at least one of the object information and the browsing information, the next browsing area adapted to the target object within multiple areas of the browsing scene; The virtual display data display module is used to obtain the virtual display data corresponding to the next browsing area from the cloud and display the virtual display data on the display device of the target object.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the data display method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the data display method according to any one of claims 1-7.

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