Local data storage method of interactive window management system

Abstract

The invention relates to the technical field of data storage, in particular to a local data storage method of an interactive window management system. The method comprises the steps of obtaining initial association strength among data according to a logic spacing distance of any two pieces of data on a cloud server and a page position distance of any two pieces of data on an interactive page, correcting the initial association strength according to an access data set of a user to obtain target association strength, and displaying the target association strength. According to the access interaction page set and the target association strength between each piece of target data of each user and associated non-accessed data in the same interaction page, obtaining a probability value of accessing the non-accessed data by the user; and according to a loading sequence determined according to the probability value, sequentially and locally loading the corresponding unaccessed data. Therefore, the data with higher user access intention is predicted in a deeper level by combining the user access data and the condition of accessing the interactive page, so that the data with higher user access intention is accurately stored, and the data storage efficiency is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data storage, and particularly relates to a method for local data storage of an interactive window management system. Background Art

[0002] An interactive window management system is an interaction that allows users to visually see various visualization interaction methods through a user interface and conveniently implement various functions through various interaction methods. The implementation of the interaction function of the interactive window management system requires multiple types of data for support. Usually, all the data required by the interactive window management system is stored in a cloud server. Generally, when a user operates the interactive window management system, the user-specified data needs to be loaded from the cloud to the user's local device.

[0003] Currently, in the prior art, in order to accelerate the data loading speed, usually not only the access data specified based on the user's interaction behavior is loaded, but also the data in the adjacent area of the location of the access data on the cloud server can be pre-loaded. However, this way of storing data does not take into account the change of the user's access requirements. For example, when the user switches the interactive page or accesses data that is far from the accessed data, it is easy to store data with a low user access intention, making it difficult to cope with the change of the user's access needs. And nowadays, even a single interaction of the user can involve a large amount of data. Storing too much data at one time will consume unnecessary resources and storage space, and thus slow down the response speed of the interactive window management system. Summary of the Invention

[0004] In order to solve the technical problem in the prior art that when storing data locally, the change of the user's access requirements is not taken into account, resulting in storing data with a low user access intention, the purpose of the present invention is to provide a method for local data storage of an interactive window management system, and the specific technical solution adopted is as follows: The present invention proposes a method for local data storage of an interactive window management system, and the method includes: Obtain an access data set and an access interactive page set of at least one user using the interactive window management system; Determine the initial association strength between the data associated with each interactive page according to the logical interval distance and the page position distance between any two data associated with each interactive page in the interactive window management system; wherein, the logical interval distance is determined based on the logical address of the data on the cloud server, and the page position distance is determined based on the coordinate position of the data on the corresponding interactive page; Modify the initial association strength according to each target data in the access data set of each user to obtain the target association strength between each data; Obtain the probability value of a user accessing unaccessed data based on the frequency of the target interaction page in the set of accessed interaction pages and the target association strength between each target data of each user and the unaccessed data associated in the same interaction page; According to the loading sequence determined by the probability value, locally load the corresponding unaccessed data in sequence.

[0005] Furthermore, the process of obtaining the set of accessed data and the set of accessed interaction pages includes: If a user using the interactive window management system is recognized, call the cloud server; Based on the interaction behavior of the recognized user on the interactive window management system, obtain, through the cloud server, the target interaction pages accessed by the user and the target duration of accessing the target interaction pages; Determine the set of accessed interaction pages based on the target interaction pages and the corresponding target duration; Based on the specified data loaded from the cloud server according to the interaction behavior, obtain the target data loaded among the data associated with the target interaction page, and determine the set of accessed data of the user based on the target data.

[0006] Furthermore, the local data storage method of the interactive window management system further includes: If an initial user who is recognized as using the interactive window management system for the first time is recognized, load preset initialization data to the local memory of the initial user through the cloud server; Based on the initialization page pre-built from the initialization data, display the initialization page to the initial user.

[0007] Furthermore, the method for obtaining the initial association strength includes: For each interaction page, determine the logical interval distance between each data associated with the interaction page according to the difference between the logical addresses of any two data on the cloud server respectively; Based on the distance between the positions where the interaction methods corresponding to any two data on the interaction page are located respectively, determine the page position distance between each data associated with the interaction page; According to the logical interval distance and the page position distance, obtain the initial association strength between each data associated with the interaction page, where the logical interval distance is negatively correlated with the initial association strength, and the page position distance is negatively correlated with the initial association strength.

[0008] Furthermore, the method for obtaining the target association strength includes: Analyze any two first target data associated under the same interaction page obtained from the access data sets of each user, and obtain the total number of first users, the total number of second users, and the average interval corresponding to any two first target data; Determine the correction coefficient between any two first target data according to the total number of first users, the total number of second users, and the average interval; According to the correction coefficient, correct the initial association strength between data that are the same as any two first target data respectively to obtain the target association strength.

[0009] Further, the methods for obtaining the total number of first users, the total number of second users, and the average interval include: Based on the number of first access data sets where any two first target data are located respectively determined from all the access data sets, take the maximum value among the numbers of the first access data sets as the total number of first users; Based on the number of second access data sets where any two first target data coexist determined from all the access data sets, take the number of the second access data sets as the total number of second users; Based on the average value of the number of target data separated between any two first target data in the corresponding second access data sets, obtain the average interval.

[0010] Further, the local data storage method of the interactive window management system further includes: If there are two data that are different from any two first target data, take the initial association strength between the two data that are different from any two first target data as the target association strength.

[0011] Further, the method for obtaining the probability value includes: Based on the total number of occurrences and the total duration of the same target interaction page obtained from the access interaction page sets of each user; Sum up the target association strength between each target data of the user and the unaccessed data associated in the same interaction page to obtain the total association strength determined based on the user interaction behavior between the unaccessed data of the user; According to the total number of occurrences, the total duration, and the total association strength, obtain the probability value of the user accessing each unaccessed data, and the total number of occurrences, the total duration, and the total association strength are all positively correlated with the probability value.

[0012] Further, the process of summing up the target association strength between each target data of the user and the unaccessed data associated in the same interaction page includes: Perform a summation operation on the target association strength between all target data and the unaccessed data associated on the same interaction page to determine the first association strength; Perform a summation operation on the target association strength between all associated unaccessed data and the target data from the same interaction page to determine the second association strength; Based on the sum of the first association strength and the second association strength, determine the total association strength of the user.

[0013] Further, the corresponding unaccessed data is locally loaded in sequence according to the loading sequence determined according to the probability value, including: Generate a loading sequence according to the probability values of the user accessing the unaccessed data in descending order; Load each unaccessed data into the user's local device in sequence according to the order of the loading sequence.

[0014] The present invention has the following beneficial effects: The present invention first obtains the user's access data set and access interaction page set to facilitate predicting possible changes in the user's access requirements in combination with the user's own access situation. Secondly, according to the logical distance between any two data associated with each interaction page on the cloud server and the page position distance on the interaction page, the initial association strength between each data is obtained. Therefore, not only the situation where the same type of data can be accessed simultaneously is considered, but also the situation where the data on the same interaction page is accessed simultaneously later is considered, and the initial intention degree of each data to be accessed later is predicted. Then, according to the user's actual access situation, the initial association strength is further corrected to obtain the target association strength, and the target association strength is further calculated in combination with the user's access interaction page situation to obtain the probability value of the user accessing the unaccessed data, where the unaccessed data is the data that has not been locally stored yet. Therefore, in combination with the user's access data and access interaction page situation, from the user's perspective, the data with a higher access intention of the user is predicted more deeply. Thus, it is convenient to narrow the range and quantity of the data required for loading, and then, in the order from high to low of the probability value, the corresponding data is locally stored in sequence, and the data with a higher access intention of the user is accurately stored, significantly increasing the data storage efficiency. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 Flowchart of a local data storage method for an interactive window management system provided by an embodiment of the present invention; Figure 2 Schematic diagram of the acquisition process of an access data set and an access interactive page set provided by an embodiment of the present invention; Figure 3 Example diagram of the duration of a user accessing each interactive page provided by an embodiment of the present invention; Figure 4 Schematic diagram of the process of obtaining the initial association strength provided by an embodiment of the present invention; Figure 5 Schematic diagram of the process of obtaining the target association strength provided by an embodiment of the present invention; Figure 6 Schematic diagram of the process of obtaining the probability value provided by an embodiment of the present invention. Detailed implementation manners

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features and effects of a local data storage method for an interactive window management system proposed according to the present invention. In the following description, different "an embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0019] The following specifically describes the specific solution of a local data storage method for an interactive window management system provided by the present invention with reference to the accompanying drawings.

[0020] Please refer to Figure 1 , which shows a flowchart of a local data storage method for an interactive window management system provided by an embodiment of the present invention. The method includes: S101: Obtain an access data set and an access interactive page set of at least one user using the interactive window management system.

[0021] It should be understood that the interactive window management system includes multiple interactive pages, and various visual interactive methods are provided on the interactive pages to implement the interactive functions that the interactive window management system can provide. Moreover, the implementation of these visual interactive methods requires the support of various types of data. All the data included in the interactive window management system are pre-stored on the cloud server. As the user starts the interactive window management system and performs various interactive behaviors on the intended interactive pages, the specified data can be loaded from the cloud server based on the user's interactive behaviors to provide the corresponding interactive functions. Therefore, the actual access situation of the user's operation of the interactive window management system on the data and interactive pages can be understood through the cloud server.

[0022] Among them, it should be noted that the various visual interactive methods provided on the interactive pages can be set according to actual needs. For example, they can be visual interactive function buttons, or the interactive methods of input boxes and forms. This embodiment does not make specific limitations.

[0023] The acquisition process of the accessed data set and the accessed interactive page set is as Figure 2 shown and includes: S101-1: If a user who is using the interactive window management system is recognized, call the cloud server.

[0024] S101-2: Based on the interactive behaviors of the recognized user on the interactive window management system, obtain the target interactive page accessed by the user and the target duration of accessing the target interactive page through the cloud server.

[0025] S101-3: Determine the accessed interactive page set based on the target interactive page and the corresponding target duration.

[0026] S101-4: Based on the specified data loaded from the cloud server according to the interactive behaviors, obtain the target data loaded in the data associated with the target interactive page, and determine the user's accessed data set based on the target data.

[0027] Among them, it can be understood that for different users, the determined accessed interactive page sets are also different.

[0028] It should be understood that even for the same user, different interactive pages can reflect different demand intentions of the user. Some interactive pages can reflect the user's strong demand intentions. Thus, it is possible to predict the user based on the interactive page with a longer stay duration. According to the user's identity and needs, when the user uses the interactive window management system, the user can also have different stay durations on different interactive pages. The data on the page with a longer stay duration is more likely to be accessed subsequently.

[0029] For example, an example diagram of the duration of a user's access to each interaction page is as follows Figure 3 shown. Among them, interaction page A, interaction page B, and interaction page C are different interaction pages respectively. The length of the graph where the interaction page is located in the example diagram reflects the duration of the interaction page. Through Figure 3 it can be seen that when the user first accesses interaction page B, the stay duration is the longest.

[0030] Among them, it should be noted that Figure 3 the arrangement order of each interaction page in

[0031] is determined according to the access order of the user. It should be understood that due to different user identities, the usage situations and usage habits of the interactive window management system are also different. There may be users who use the interactive window management system for the first time. Among them, when there is no historical interaction data cache established between the user terminal and the cloud server of the interactive window management system, or when there is a user identity identifier without the permission to operate the interactive window management system, it can be determined that the recognized user is a user who uses the interactive window management system for the first time. When the user uses the interactive window management system for the first time, an initialization interface can be provided for the user. At this time, the user has not performed various interaction operations yet, and the data included in the initialization interface is usually some most basic data. In order to ensure that various functions on the initialization interface are available for the user to use normally, the data included in the initialization interface can be downloaded from the cloud server.

[0032] In some implementation manners of the embodiments of the present invention, if an initial user who uses the interactive window management system for the first time is recognized, preset initialization data is loaded from the cloud server to the local memory of the initial user; based on the initialization page pre-built with the initialization data, the initialization page is displayed to the initial user.

[0033] Among them, it should be noted that the specific data of the initialization data can be preset according to the actual situation, and this embodiment does not make a limitation.

[0034] S102: Determine the initial association strength between the various data associated with each interaction page in the interactive window management system according to the logical interval distance and the page position distance between any two data associated with the interaction page.

[0035] Among them, it should be noted that the logical interval distance is determined based on the logical address of the data on the cloud server, and the page position distance is determined based on the coordinate position of the data on the corresponding interaction page.

[0036] It should be understood that in an interactive window management system, there are some connections in the co-access situation among various data. For the same type of data, the logical addresses where these data are stored on the cloud server are relatively close. For example, after the data on interactive page A is accessed, the possibility that other data included in interactive page A will be accessed by the user subsequently is relatively high. And after a certain data is accessed, the possibility that the data on the same interactive page as it is co-accessed is also relatively high. Moreover, the same type of data is reflected on the interactive page and is also used to implement the same type of interactive function. Therefore, in an actual scenario, for the sake of aesthetics and convenience, the positions of the same type of data on the interactive page are also relatively close. Therefore, by analyzing the logical interval distance and page position distance between data, the possibility of co-access between each data can be further understood.

[0037] The process of obtaining the initial association strength is as Figure 4 shown and includes: S102-1: For each interactive page, determine the logical interval distance between the various data associated with the interactive page according to the difference between the logical addresses of any two data on the cloud server respectively.

[0038] Among them, it can be understood that there are multiple interactive pages in the interactive window management system, and there are multiple pieces of data associated with the interactive page.

[0039] The logical address, through machine language instructions, is used to indicate the address of a piece of data.

[0040] For example, assume that the logical address is represented by a hexadecimal number. Taking a 32-bit operating system as an example, among them, the logical address range of the 32-bit operating system is from 0x00000000 to 0xFFFFFFFF. Assume that data 1 is stored at logical address A (0x1000), and data 2 is stored at logical address B (0x1020). The logical interval distance between data 1 and data 2 = the difference between logical address A and logical address B = 0x1020 - 0x1000 = 0x20 (hexadecimal subtraction).

[0041] S102-2: Based on the distance between the positions where the interaction methods corresponding to any two data on the interactive page are located respectively, determine the page position distance between the various data associated with the interactive page.

[0042] Among them, it should be noted that since the representation forms of the interaction methods are different, and the interactive functions that can be realized are also different, the positions where the interaction methods are located will change accordingly according to actual needs. The means of obtaining the positions where the interaction methods are located are well-known technical means to those skilled in the art, and will not be elaborated in this embodiment.

[0043] S102-3: Obtain the initial association strength between the various data associated with the interactive page according to the logical interval distance and the page position distance. The logical interval distance is negatively correlated with the initial association strength, and the page position distance is negatively correlated with the initial association strength.

[0044] Since the closer the logical addresses stored on the cloud server are, the smaller the logical interval, and the higher the possibility that the subsequent data adjacent to them will be accessed by the user, the logical interval distance is negatively correlated with the initial association strength. The closer the positions of the interaction methods corresponding to the two data on the interactive page are, the greater the possibility that the other data will be accessed after one data is accessed, so the page position distance is negatively correlated with the initial association strength. Therefore, the initial association strength can be expressed by the following formula: Among them, assume that there are pages in the interactive window management system, and each page contains pieces of data; are respectively used to represent the th and th data under the th interactive page in the interactive window management system, ; is used to represent the logical interval distance between the th and th and th data under the th interactive page; is used to represent the page position distance between the th and th data under the th interactive page; is used to represent the initial association strength between the th and th data under the

[0045] S103: Modify the initial association strength according to each target data in the data set accessed by each user to obtain the target association strength between the various data.

[0046] It should be noted that the initial association strength only analyzes the association situation of data access between data through the logical interval distance and the page position distance on the interactive page. However, the usage habits of different users are not the same, and the needs of users are also constantly changing. Therefore, the initial association strength can also be modified according to the access situation of users to the interactive window management system, so as to more deeply predict the data with a higher access intention from the perspective of users.

[0047] The process of obtaining the target association strength is asFigure 5 As shown in the figure, it includes: S103-1: Analyze any two first target data associated under the same interaction page obtained from the access data sets of each user, and obtain the total number of first users, the total number of second users, and the average interval corresponding to the any two first target data.

[0048] Among them, it can be understood that for different users, the obtained access data sets are also different.

[0049] In order to accurately obtain the total number of first users, as an example, based on the number of the first access data sets where any two first target data are located determined from all the access data sets, the maximum value among the numbers of the first access data sets is used as the total number of first users.

[0050] In order to accurately obtain the total number of second users, as an example, based on the number of the second access data sets where any two first target data coexist determined from all the access data sets, the number of the second access data sets is used as the total number of second users.

[0051] In order to accurately obtain the average interval, as an example, based on the average value of the number of target data intervals between any two first target data in the corresponding second access data sets, the average interval is obtained.

[0052] For example, assume that there are user A, user B, and user C. The access data set A of user A is { , , }, the access data set B of user B is { , }, and the access data set C of user C is { , , }. Then, taking and as the first target data respectively, in the access data set A, access data set B, and access data set C, is in the first access data sets including access data set A and access data set B, a total of two sets, is in the first access data sets including access data set A and access data set C, a total of two sets; then and each have 2 first access data sets, and the total number of first users is 2; in the access data set A, access data set B, and access data set C, and The second set of accessed data that appears together includes the accessed data set A and the accessed data set C, a total of two sets, so the number of second users is 2; and both exist in the accessed data set A and the accessed data set C. The interval between these two data and these two data, so the average interval is 1.

[0053] S103-2: Determine the correction coefficient between any two first target data according to the total number of first users, the total number of second users, and the average interval.

[0054] According to the user's own access situation, it can be known that if there are two data that have been accessed by the user together, there must be a further connection between these two data. Moreover, for all users who are using the interactive window management system, the access situations of all users can be used as analysis data for digging deep into the user's access intention. The larger the number of first users of two data, the higher the probability that one of the two data appears in other accessed data sets, which further indicates that the user is more likely to access these two data. Similarly, the larger the number of second users of two data, the higher the probability that the two data appear in other accessed data sets together, which further proves that the possibility of these two data being accessed together is higher. Therefore, the larger the ratio of the number of second users to the number of first users, the higher the possibility that the two data are accessed together, which is positively correlated with the correction coefficient. Since the more data there is between the two data, it means that after the user accesses one of the data, the time interval for accessing the other data is longer, and it is not continuous in time. This reflects to a certain extent that the user's enthusiasm for accessing these two data together is lower, that is, the possibility of these two data being accessed together is reduced. Therefore, the average interval is negatively correlated with the correction coefficient.

[0055] S103-3: According to the correction coefficient, correct the initial association strength between the data that are the same as any two first target data respectively to obtain the target association strength.

[0056] The target association strength can be expressed by the following formula: where is used to represent the number of first users of the th data under the th interactive page and the th data; is used to represent the number of second users of the th data under the th interactive page and the th data; is for all data accessed simultaneously at the The average number of interval data between the and the th data; Used to represent the th on the and the th data correction coefficient; Used to represent the th on the and the th data target association strength.

[0057] It should be noted that on the same interactive page, there can also be multiple data. Even if the user accesses the data on the same interactive page, there can be two data that exist and can be jointly accessed. Therefore, these data that have not been jointly accessed reflect the user's low intention for these data and do not need to be corrected.

[0058] In this embodiment, if there are two data that are different from any two first target data, the initial association strength between the two data that are different from any two first target data is used as the target association strength.

[0059] S104: Obtain the probability value of the user accessing the unaccessed data according to the frequency of the target interactive page in the accessed interactive page set and the target association strength between each user's target data and the unaccessed data associated in the same interactive page.

[0060] It should be noted that when the user uses the interactive window management system, the user can also have different residence times on different interactive pages, and the user can switch between different interactive pages. Then, the interactive page with more residence times can show the user's strong demand intention. Therefore, it is possible to further predict the data with a higher subsequent access intention of the user from the interactive page with more residence times, so as to further narrow the range and quantity of the data to be loaded.

[0061] The process of obtaining the probability value is as Figure 6 shown, including: S104-1: Based on the total number of times and total duration of the same target interactive page obtained from the accessed interactive page sets of each user.

[0062] S104-2: Sum the target association strengths between each user's target data and the unaccessed data associated in the same interactive page to obtain the total association strength determined based on the user's interaction behavior among the unaccessed data.

[0063] Among them, it can be understood that the unaccessed data is used to represent the data among the various data associated with the interactive page that has not been locally loaded into the user's local device yet.

[0064] To obtain the total association strength completely, as an example, a summation operation is performed on the target association strength between all target data and the unaccessed data associated with it on the same interactive page to determine the first association strength; a summation operation is performed on the target association strength between all associated unaccessed data and the target data from the same interactive page to determine the second association strength; based on the sum of the first association strength and the second association strength, the total association strength of the user is determined.

[0065] Suppose there are interactive pages in the interactive window management system, and each interactive page contains pieces of unaccessed data. The access data set of a certain user k is , , and the total association strength can be expressed by the following formula: Among them, is used to return the number of data contained in the access data set ; the data with the subscript must be included in the access data set ; ; or is used to represent the target association strength between the data and the unaccessed data ; is used to represent the total association strength between the data that has been accessed in the access data set of user k on the th interactive page and the unaccessed data ; is used to represent the first association strength; is used to represent the second association strength.

[0066] S104-3: According to the total number of times, the total duration, and the total association strength, obtain the probability value for the user to access each unaccessed data, and the total number of times, the total duration, and the total association strength are all positively correlated with the probability value.

[0067] Since the more times a user switches to a certain interactive page when using the interactive window management system, it indicates that the user has the habit of using this interactive page multiple times, which means that the probability of the subsequent user accessing the data on this interactive page is higher. Therefore, the total number of times is positively correlated with the probability value. And the longer the user stays on a certain interactive page, it also means that the probability of the subsequent user accessing the data on this interactive page is higher, so the total duration is positively correlated with the probability value. Therefore, the probability value can be expressed by the following formula: Among them, used to represent the total duration that user k stays on the th interactive page where the data is located when using the interactive window management system; used to represent the total number of times that user k stays on the th interactive page where the data is located when using the interactive system.

[0068] S105: According to the loading sequence determined by the probability value, sequentially locally load the corresponding unaccessed data.

[0069] It should be noted that the probability value is used to indicate the possibility of the unaccessed data being accessed subsequently. Among different unaccessed data, the obtained probability values are also different, representing different intensities of the user's access intention. Since data synchronization with the cloud server is required during the interaction process and data loading also takes some time, in order to be able to respond to the user's interaction needs in a timely manner, the data can be locally loaded one by one according to the level of the probability value.

[0070] In order to synchronize the data with a relatively high predicted user access intention with the cloud server in a timely manner, as a possible implementation manner, according to the descending order of the probability values of the unaccessed data, the corresponding unaccessed data is loaded into the local device.

[0071] As an example, a loading sequence is generated according to the descending order of the probability values of the user accessing the unaccessed data; according to the order of the loading sequence, each unaccessed data is sequentially loaded into the user's local device.

[0072] Among them, it can be understood that the local device includes devices such as user terminals and edge computing nodes that perform local storage and processing.

[0073] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the advantages or disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the differences between each embodiment and other embodiments are emphasized.

Claims

1. A local data storage method for an interactive window management system, characterized in that, The method includes: Obtaining an access data set and an accessed interactive page set of at least one user using the interactive window management system; Determining an initial association strength between each data associated with an interactive page according to the logical interval distance and the page position distance between any two data associated with each interactive page in the interactive window management system; wherein, the logical interval distance is determined based on the logical address of the data on the cloud server, and the page position distance is determined based on the coordinate position of the data on the corresponding interactive page; Correcting the initial association strength according to each target data in the access data set of each user to obtain a target association strength between each data; Obtaining a probability value of a user accessing unaccessed data according to the frequency of the target interactive page in the accessed interactive page set and the target association strength between each target data of each user and the unaccessed data associated with the same interactive page; Sequentially locally loading the corresponding unaccessed data according to the loading sequence determined by the probability value.

2. The local data storage method of the interactive window management system according to claim 1, characterized in that, The process of obtaining the access data set and the accessed interactive page set includes: If a user using the interactive window management system is recognized, calling the cloud server; Based on the interactive behavior of the recognized user on the interactive window management system, obtaining, through the cloud server, the target interactive page accessed by the user and the target duration of accessing the target interactive page; Determining the accessed interactive page set based on the target interactive page and the corresponding target duration; Obtaining the target data loaded among the data associated with the target interactive page based on the specified data loaded from the cloud server according to the interactive behavior, and determining the access data set of the user based on the target data.

3. The local data storage method of the interactive window management system according to claim 2, wherein The method includes: If an initial user who uses the interactive window management system for the first time is recognized, loading preset initialization data to the local memory of the initial user through the cloud server; Displaying the initialization page to the initial user based on the initialization page pre-built based on the initialization data.

4. The local data storage method of the interactive window management system according to claim 1, characterized in that, The method for obtaining the initial association strength includes: For each interactive page, determining the logical interval distance between each data associated with the interactive page according to the difference between the logical addresses of any two data on the cloud server; Determining the page position distance between each data associated with the interactive page based on the distance between the positions where the corresponding interaction methods of any two data are located on the interactive page; Obtaining the initial association strength between each data associated with the interactive page according to the logical interval distance and the page position distance, where the logical interval distance is negatively correlated with the initial association strength, and the page position distance is negatively correlated with the initial association strength.

5. The local data storage method of the interactive window management system according to claim 1, characterized in that, The method for obtaining the target association strength includes: Analyzing any two first target data according to any two first target data obtained in the access data set of each user and associated under the same interactive page to obtain the total number of the first users, the total number of the second users, and the average interval corresponding to the any two first target data; Determine a correction coefficient between any two first target data according to the total number of the first users, the total number of the second users, and the average interval; Correct the initial association strength between data that are the same as any two first target data respectively according to the correction coefficient to obtain the target association strength.

6. The local data storage method of the interactive window management system according to claim 5, characterized in that, The methods for obtaining the total number of the first users, the total number of the second users, and the average interval include: Based on the number of first access data sets where any two first target data are respectively located determined from all the access data sets, use the maximum value among the numbers of the first access data sets as the total number of the first users; Based on the number of second access data sets where any two first target data coexist determined from all the access data sets, use the number of the second access data sets as the total number of the second users; Based on the average value of the number of target data between any two first target data in the corresponding second access data set, obtain the average interval.

7. The local data storage method of the interactive window management system according to claim 5 or 6, characterized in that, The method includes: If there are two data that are different from any two first target data, use the initial association strength between the two data that are different from any two first target data as the target association strength.

8. The local data storage method of the interactive window management system according to claim 1, characterized in that, The method for obtaining the probability value includes: Based on the total number of occurrences and the total duration of the same target interaction page obtained from the access interaction page sets of each user; Sum up the target association strengths between each target data of the user and the unaccessed data associated with the same interaction page to obtain the total association strength determined based on the user interaction behavior among the unaccessed data of the user; According to the total number of occurrences, the total duration, and the total association strength, obtain the probability value for the user to access each unaccessed data, and the total number of occurrences, the total duration, and the total association strength are all positively correlated with the probability value.

9. The local data storage method of the interactive window management system according to claim 8, characterized in that The process of summing up the target association strengths between each target data of the user and the unaccessed data associated with the same interaction page includes: Perform a summation operation on the target association strengths between all target data and the unaccessed data associated with them on the same interaction page to determine the first association strength; Perform a summation operation on the target association strengths between all associated unaccessed data and the target data from the same interaction page to determine the second association strength; Based on the sum of the first association strength and the second association strength, determine the total association strength of the user.

10. The local data storage method of the interactive window management system according to claim 1, characterized in that, Loading the corresponding unaccessed data locally in sequence according to the loading sequence determined according to the probability value includes: Generate a loading sequence by arranging the probability values of the user accessing the unaccessed data in descending order; According to the order of the loading sequence, load each unaccessed data into the local device of the user in sequence.

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