Client intelligent upgrade guide system based on application store state awareness

Abstract

The application discloses a client intelligent upgrade guiding system based on application store state sensing, and comprises the following modules: an acquisition module, which is used for calling a version detection interface to acquire configuration information when a client starts or logs in; a first determination module, which is used for determining the upgrade time of the client according to the configuration information; an application store setting module, which is used for setting an application store list and acquiring application store state sensing information based on the upgrade time; and an upgrade guiding module, which is used for guiding the upgrade of the client according to the application store state sensing information. The application fully considers different application store states, guides the upgrade of the client, avoids the centralized upgrade and version upgrade rollback, facilitates the improvement of the upgrade efficiency of the client and the reduction of the risk of upgrade failure.

Description

Technical Field

[0001] This invention relates to the field of upgrade guidance technology, and in particular to a client-side intelligent upgrade guidance system based on app store status awareness. Background Technology

[0002] Currently, there is an issue of inconsistent versions available in app stores when upgrading Android clients. However, existing technologies simply compare versions and prompt for updates without fully considering factors such as app store status and user scenarios. They cannot provide intelligent upgrade guidance based on different app store statuses and user needs. This can easily lead to high server concurrency pressure during centralized upgrades, resulting in slow upgrade file transfer speeds and even upgrade failures. It can also easily cause version upgrade rollbacks, leading to low client upgrade efficiency and a high risk of upgrade failure. Summary of the Invention

[0003] This invention aims to at least partially solve one of the technical problems in the aforementioned technologies. Therefore, the purpose of this invention is to propose a client-side intelligent upgrade guidance system based on app store status awareness. This system fully considers the different app store statuses, guides client upgrades accordingly, avoids centralized upgrades and version upgrade rollbacks, improves client upgrade efficiency, and reduces the risk of upgrade failure.

[0004] To achieve the above objectives, embodiments of the present invention propose a client-side intelligent upgrade guidance system based on app store status awareness, comprising:

[0005] The acquisition module is used to call the version detection interface to obtain configuration information when the client starts up or logs in;

[0006] The first determining module is used to determine the client's upgrade time based on the configuration information;

[0007] The app store settings module is used to set the app store list and obtain app store status awareness information based on the upgrade time.

[0008] The upgrade guidance module is used to guide clients through the upgrade process based on app store status information.

[0009] According to some embodiments of the present invention, the acquisition module includes:

[0010] The server-side component provides a version detection interface.

[0011] The management platform is used to configure upgrade tasks and upgrade packages; the upgrade tasks include forced upgrades, normal upgrade strategies, and upgrade times; the upgrade packages include version numbers, upgrade packages uploaded to different clients, and upgrade instructions;

[0012] The second determination module calls the version detection interface when the client starts or logs in to determine the client's current version information and the corresponding upgrade task and upgrade package, which are used as configuration information.

[0013] According to some embodiments of the present invention, an app store settings module includes:

[0014] The configuration module is used to pre-configure the list of app stores available on the client on the Portal. The list of app stores contains several app stores, and each app store is configured with attribute information, including name, package name, app store logo, client version number, and remarks.

[0015] The sorting module is used for:

[0016] A dynamic update mechanism for app store ranking is built, which adjusts the display order in real time according to the configured version effective time and app store listing status. The latest client version number of each app store is obtained based on attribute information within a preset time period before the upgrade time.

[0017] Sort the applications by latest client version number from largest to smallest to determine the sorted list, which will serve as status awareness information for the app store.

[0018] According to some embodiments of the present invention, the upgrade guidance module is used to determine and display the first corresponding application store in the sorted list of application store status awareness information; and guide the client to upgrade based on the display result.

[0019] According to some embodiments of the present invention, the upgrade boot module is used for:

[0020] When it is determined that no app store is available based on the app store status awareness information, the browser download fallback strategy will automatically trigger HTTPS download and verify the integrity of the downloaded installation package through file verification code.

[0021] Once the verification is successful, the client will be guided to upgrade based on the downloaded installation package.

[0022] According to some embodiments of the present invention, the upgrade guidance module guides the client to upgrade based on the display results, including:

[0023] The extraction module is used to extract the upgrade tags of the upgrade package from the app store corresponding to the displayed results based on the extraction window;

[0024] The verification module is used to verify the validity of the extracted upgrade tag. When the verification is successful, the client is guided to upgrade based on the upgrade tag.

[0025] According to some embodiments of the present invention, the verification module includes:

[0026] The third determining module is used for:

[0027] Obtain the extraction parameters for extracting upgrade tags; the extraction parameters include the number of times the extraction window successfully reads upgrade tags within a unit data volume, the data rate of the upgrade package, the extraction range radius of the extraction window, and the time interval for extracting upgrade tags;

[0028] The first effectiveness coefficient is determined based on the extracted parameters and the preset first weight coefficient;

[0029] The fourth determination module is used to determine the accuracy rate of the upgrade label verified by manual annotation, and to determine the second validity coefficient based on the accuracy rate and the preset second weighting coefficient.

[0030] The fifth determination module is used to determine the validity coefficient of the extracted upgrade label based on the first validity coefficient and the second validity coefficient, and compare it with the preset validity threshold; if the validity coefficient is greater than the preset validity threshold, it means that the validity verification of the upgrade label has passed; otherwise, it means that the validity verification of the upgrade label has not passed.

[0031] According to some embodiments of the present invention, the verification module further includes:

[0032] The filtering module is used to identify the type of upgrade tags, determine the type of each sub-tag within the upgrade tags, and perform cluster analysis to obtain several cluster sets. It then performs numerical processing on the sub-tags in each cluster set to determine the tag value of each sub-tag. The module calculates the distance between the tag value of each sub-tag and the tag values ​​of other sub-tags in the same cluster set. Based on the distance values, it calculates the variance and compares it with a preset variance value. Sub-tags with variance values ​​greater than the preset variance value are filtered out as problem tags and removed, resulting in the target cluster set.

[0033] The associated module is used for:

[0034] Determine the central label in each target cluster set, and determine the first association between other labels and the central label; determine the second association between the central labels of each target cluster set; and determine the label association graph based on the first and second associations.

[0035] The upgrade order is determined based on the tag association diagram, and the client is guided to upgrade based on the upgrade order.

[0036] According to some embodiments of the present invention, it further includes: a monitoring module, used to monitor the upgrade process during the upgrade guidance module's upgrade guidance of the client based on the application store status awareness information, obtain monitoring results and display them.

[0037] According to some embodiments of the present invention, a monitoring module includes:

[0038] The first monitoring module is used to monitor upgrade failure information and determine the upgrade failure ratio based on the upgrade failure information; the upgrade failure information includes the total number of components involved in the upgrade process, the number of component categories that failed in the upgrade, the weight of the i-th type of failed component, and the number of the i-th type of failed component.

[0039] The second monitoring module is used to monitor when the total upgrade time exceeds the expected time and determine the impact of the upgrade time.

[0040] The calculation module is used to calculate the upgrade impact coefficient based on the upgrade failure rate and the impact of upgrade time.

[0041] The upgrade impact coefficient is used as a monitoring result and displayed. When the upgrade impact coefficient is determined to be greater than the preset impact threshold, an alarm is issued.

[0042] This invention proposes a client intelligent upgrade guidance system based on app store status awareness. It fully considers the different app store statuses and guides the client upgrade accordingly, avoiding centralized upgrades and version upgrade rollbacks, thereby improving the client upgrade efficiency and reducing the risk of upgrade failure.

[0043] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0044] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0045] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0046] Figure 1 This is a block diagram of a client-side intelligent upgrade guidance system based on application store status awareness according to an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of application store configuration attribute information according to an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram illustrating how to guide a client to upgrade based on application store status awareness information according to an embodiment of the present invention. Detailed Implementation

[0049] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0050] like Figure 1 As shown in the figure, this invention proposes a client-side intelligent upgrade guidance system based on app store status awareness, comprising:

[0051] The acquisition module is used to call the version detection interface to obtain configuration information when the client starts up or logs in;

[0052] The first determining module is used to determine the client's upgrade time based on the configuration information;

[0053] The app store settings module is used to set the app store list and obtain app store status awareness information based on the upgrade time.

[0054] The upgrade guidance module is used to guide clients through the upgrade process based on app store status information.

[0055] The working principle of the above technical solution is as follows: The acquisition module calls the version detection interface to obtain configuration information when the client starts or logs in; the first determination module determines the client's upgrade time based on the configuration information; the app store settings module sets the app store list, including Tencent App Store, Xiaomi App Store, Huawei App Store, Baidu App Store, etc. App store status awareness information is obtained based on the upgrade time; this facilitates determining the latest version information of each app store before the upgrade, and sorting them as app store status awareness information. The upgrade guidance module guides the client through the upgrade process based on the app store status awareness information.

[0056] The beneficial effects of the above technical solution are: it fully considers the status of different app stores, guides clients to upgrade, avoids centralized upgrades and version upgrade rollbacks, improves client upgrade efficiency, and reduces the risk of upgrade failure.

[0057] According to some embodiments of the present invention, the acquisition module includes:

[0058] The server-side component provides a version detection interface.

[0059] The management platform is used to configure upgrade tasks and upgrade packages; the upgrade tasks include forced upgrades, normal upgrade strategies, and upgrade times; the upgrade packages include version numbers, upgrade packages uploaded to different clients, and upgrade instructions;

[0060] The second determination module calls the version detection interface when the client starts or logs in to determine the client's current version information and the corresponding upgrade task and upgrade package, which are used as configuration information.

[0061] The working principle of the above technical solution is as follows: Forced upgrades are for incompatible versions, while compatible versions support normal upgrade strategies, namely "later," "skip," and selection. The second determination module calls the version detection interface when the client starts up or logs in to determine the client's current version information and the corresponding upgrade task and upgrade package, which are used as configuration information.

[0062] The beneficial effects of the above technical solution are: it facilitates the accurate determination of configuration information, upgrade strategies, upgrade times, and other information.

[0063] like Figure 2 As shown, according to some embodiments of the present invention, the app store settings module includes:

[0064] The configuration module is used to pre-configure the list of app stores available on the client on the Portal. The list of app stores contains several app stores, and each app store is configured with attribute information, including name, package name, app store logo, client version number, and remarks.

[0065] The sorting module is used for:

[0066] A dynamic update mechanism for app store ranking is built, which adjusts the display order in real time according to the configured version effective time and app store listing status. The latest client version number of each app store is obtained based on attribute information within a preset time period before the upgrade time.

[0067] Sort the applications by latest client version number from largest to smallest to determine the sorted list, which will serve as status awareness information for the app store.

[0068] The working principle of the above technical solution is as follows: A list of app stores listed on the client is pre-configured on the Portal. Specifically, the administrator logs into the Portal management backend, finds the option to configure the app store list on the application management page, and clicks the "Add" or "Edit" button to configure the app store list. Each app store is configured with attribute information, including name, package name, app store logo, client version number, and remarks. The package name is a unique identifier for the app store, such as com.tencent.android.qqdownloader. The sorting module constructs a dynamic update mechanism for app store sorting. It adjusts the display order in real time based on the configured version effective time and the app store's listing status. A preset time period before the upgrade time is used to obtain the latest client version number of each app store based on the attribute information. The app stores are then sorted from largest to smallest according to their latest client version numbers to determine the sorted list, which serves as the app store status awareness information.

[0069] The beneficial effects of the above technical solution are: it facilitates obtaining and sorting the latest client version number of each app store before the upgrade time, and makes it easier to accurately determine the app store status awareness information.

[0070] According to some embodiments of the present invention, the upgrade guidance module is used to determine and display the first corresponding application store in the sorted list of application store status awareness information; and guide the client to upgrade based on the display result.

[0071] The working principle of the above technical solution is as follows: The upgrade guidance module determines and displays the first corresponding app store in the sorted list of app store status awareness information; based on the displayed result, it guides the client to upgrade. For example: Because different app stores have different release times, such as Tencent App Store having released the latest version of Netskyper 3.7, while Google Play Store still has Netskyper 3.6, and the client version installed on the phone is 3.5, during the upgrade, the client is informed of the app store corresponding to the latest version. That is, only Tencent App Store is displayed. If all stores were displayed, the user might need to upgrade again after upgrading, causing inconvenience.

[0072] The beneficial effects of the above technical solution are: to achieve precise upgrade guidance, which facilitates the improvement of the efficiency and accuracy of client upgrades.

[0073] like Figure 3 As shown, the sorted list in the App Store status awareness information is determined and displayed to facilitate users in choosing which upgrade method to use, thereby improving the user experience.

[0074] According to some embodiments of the present invention, the upgrade boot module is used for:

[0075] When it is determined that no app store is available based on the app store status awareness information, the browser download fallback strategy will automatically trigger HTTPS download and verify the integrity of the downloaded installation package through file verification code.

[0076] Once the verification is successful, the client will be guided to upgrade based on the downloaded installation package.

[0077] The working principle of the above technical solution is as follows: When no app store is available based on app store status awareness information, an HTTPS download is automatically triggered via a browser download fallback strategy, and the integrity of the downloaded installation package is verified using a file verification code. It supports differentiated processing for multiple platforms (Windows, macOS, Linux, iOS, Android). Upon successful verification, the client is guided to upgrade based on the downloaded installation package.

[0078] The beneficial effects of the above technical solution are: it facilitates upgrading and verifying the installation package through the browser when it is determined that there is no available app store based on the app store status awareness information, which facilitates providing redundant support for upgrades and enriches the upgrade methods.

[0079] According to some embodiments of the present invention, the upgrade guidance module guides the client to upgrade based on the display results, including:

[0080] The extraction module is used to extract the upgrade tags of the upgrade package from the app store corresponding to the displayed results based on the extraction window;

[0081] The verification module is used to verify the validity of the extracted upgrade tag. When the verification is successful, the client is guided to upgrade based on the upgrade tag.

[0082] The working principle of the above technical solution is as follows: The extraction module extracts the upgrade tags of the upgrade package from the app store corresponding to the displayed results based on the extraction window; the upgrade tags include the upgrade type, content determination, upgrade time, order, etc. The verification module verifies the validity of the extracted upgrade tags, and when the verification is successful, the client is guided to upgrade based on the upgrade tags.

[0083] The beneficial effects of the above technical solution are: upgrading clients based on upgrade tags facilitates improved efficiency and accuracy of upgrades.

[0084] According to some embodiments of the present invention, the verification module includes:

[0085] The third determining module is used for:

[0086] Obtain the extraction parameters for extracting upgrade tags; the extraction parameters include the number of times the extraction window successfully reads upgrade tags within a unit data volume, the data rate of the upgrade package, the extraction range radius of the extraction window, and the time interval for extracting upgrade tags;

[0087] The first effectiveness coefficient is determined based on the extracted parameters and the preset first weight coefficient;

[0088] The fourth determination module is used to determine the accuracy rate of the upgrade label verified by manual annotation, and to determine the second validity coefficient based on the accuracy rate and the preset second weighting coefficient.

[0089] The fifth determination module is used to determine the validity coefficient of the extracted upgrade label based on the first validity coefficient and the second validity coefficient, and compare it with the preset validity threshold; if the validity coefficient is greater than the preset validity threshold, it means that the validity verification of the upgrade label has passed; otherwise, it means that the validity verification of the upgrade label has not passed.

[0090] The working principle of the above technical solution is as follows: The sum of the preset first weighting coefficient and the preset second weighting coefficient is 1. Based on the extraction parameters of the upgrade label and the preset first weighting coefficient, a first validity coefficient is determined; based on the accuracy rate of the upgrade label verified by manual annotation, a second validity coefficient is determined according to the accuracy rate and the preset second weighting coefficient; based on the first validity coefficient and the second validity coefficient, the validity coefficient of the extracted upgrade label is accurately determined, and the validity coefficient is compared with a preset validity threshold; based on the comparison result, the validity verification result of the upgrade label is determined. The validity coefficient of the extracted upgrade label is determined as follows:

[0091]

[0092] Where λ is the effectiveness coefficient for extracting upgrade tags; G is the number of times the extraction window successfully reads upgrade tags within a unit data volume; V is the data rate of the upgrade package; T is the time interval for extracting upgrade tags; R is the extraction range radius of the extraction window; a is the preset first weight coefficient; β is the preset second weight coefficient; and A is the accuracy verified by manual annotation. β represents the effectiveness of the automated extraction process. β·A represents the accuracy of the manual annotation verification. λ is a comprehensive reflection of the effectiveness of the automated extraction process and the accuracy of the manual annotation verification.

[0093] The beneficial effects of the above technical solution are as follows: The verification module calculates the total validity coefficient by combining the effectiveness of the automatic extraction process and the accuracy of manual annotation verification, and compares it with a preset threshold, thereby verifying the validity of the upgraded label and improving the accuracy and efficiency of verification.

[0094] According to some embodiments of the present invention, the verification module further includes:

[0095] The filtering module is used to identify the type of upgrade tags, determine the type of each sub-tag within the upgrade tags, and perform cluster analysis to obtain several cluster sets. It then performs numerical processing on the sub-tags in each cluster set to determine the tag value of each sub-tag. The module calculates the distance between the tag value of each sub-tag and the tag values ​​of other sub-tags in the same cluster set. Based on the distance values, it calculates the variance and compares it with a preset variance value. Sub-tags with variance values ​​greater than the preset variance value are filtered out as problem tags and removed, resulting in the target cluster set.

[0096] The associated module is used for:

[0097] Determine the central label in each target cluster set, and determine the first association between other labels and the central label; determine the second association between the central labels of each target cluster set; and determine the label association graph based on the first and second associations.

[0098] The upgrade order is determined based on the tag association diagram, and the client is guided to upgrade based on the upgrade order.

[0099] The working principle of the above technical solution is as follows: The screening module identifies the type of each sub-label in the upgrade label, determines the type of each sub-label, and performs cluster analysis to obtain several cluster sets; the sub-labels in each cluster set are numerically processed to determine the label value of each sub-label; the distance value between the label value of each sub-label and the label values ​​of other sub-labels in the same cluster set is calculated; the variance value is calculated based on the distance value, which reflects the dispersion of the sub-label in the cluster set. This variance value is compared with a preset variance value; sub-labels with variance values ​​greater than the preset variance value are selected as problem labels and removed to obtain an accurate cluster set, i.e., the target cluster set. The association module determines the central label: Method 1: By analyzing the attributes and frequency of occurrence of the labels, the representativeness of each label in the cluster set is evaluated. The label with the highest representativeness is selected as the central label. Method 2: The distance between each label and other labels is calculated, and the label with the smallest sum of distances to other labels is selected as the central label. The distance between other labels and the central label is determined, thereby determining the first association relationship between other labels and the central label. The first association relationship represents the association between different labels within the same target cluster set. The second association relationship represents the degree of association between the central labels of different target cluster sets. Association rule mining is used to learn the association relationships between central labels. Based on the first and second association relationships, a label association graph is determined; the upgrade order is determined based on the label association graph, and the client is guided to upgrade according to the upgrade order.

[0100] The beneficial effects of the above technical solution are as follows: the upgrade tags are screened, which improves the accuracy of the upgrade tags. At the same time, the upgrade tags are divided into sets, and a tag association diagram is determined based on the tags within the set and the relationship between tags between sets. The tag association diagram makes it easier to accurately determine the upgrade order, thereby improving the efficiency and accuracy of upgrade guidance.

[0101] According to some embodiments of the present invention, it further includes: a monitoring module, used to monitor the upgrade process during the upgrade guidance module's upgrade guidance of the client based on the application store status awareness information, obtain monitoring results and display them.

[0102] The working principle and beneficial effects of the above technical solution are as follows: The monitoring module is used to monitor the upgrade process during the upgrade guidance module's upgrade guidance of the client based on the application store status awareness information, obtain and display the monitoring results, so as to determine the specific situation of the upgrade in a timely and accurate manner, and facilitate timely handling when upgrade anomalies occur.

[0103] According to some embodiments of the present invention, a monitoring module includes:

[0104] The first monitoring module is used to monitor upgrade failure information and determine the upgrade failure ratio based on the upgrade failure information; the upgrade failure information includes the total number of components involved in the upgrade process, the number of component categories that failed in the upgrade, the weight of the i-th type of failed component, and the number of the i-th type of failed component.

[0105] The second monitoring module is used to monitor when the total upgrade time exceeds the expected time and determine the impact of the upgrade time.

[0106] The calculation module is used to calculate the upgrade impact coefficient based on the upgrade failure rate and the impact of upgrade time.

[0107] The upgrade impact coefficient is used as a monitoring result and displayed. When the upgrade impact coefficient is determined to be greater than the preset impact threshold, an alarm is issued.

[0108] The working principle of the above technical solution is as follows: The first monitoring module monitors upgrade failure information to accurately determine the upgrade failure rate. The second monitoring module monitors when the total upgrade time exceeds the expected time, determining the impact of upgrade time consumption. The calculation module calculates the upgrade impact coefficient based on the upgrade failure rate and the upgrade time consumption impact. The upgrade impact coefficient is used as the monitoring result and displayed. An alarm is issued when the upgrade impact coefficient exceeds a preset impact threshold. The preset impact threshold is a preset threshold at which the task upgrade impact is acceptable. The upgrade impact coefficient is:

[0109]

[0110] Where y is the upgrade impact coefficient; The weighting coefficient for the upgrade failure rate; N is the total number of components involved in the upgrade process; n1 is the number of component categories that failed the upgrade; s i f represents the weight of the i-th type of failed component; i Let i be the number of failed components of type i. Here, ΔT represents the weighting coefficient for the impact of upgrade time. A larger upgrade impact coefficient indicates a stronger negative impact of the upgrade process on system stability. The sum of the weighting coefficients for the upgrade failure rate and the upgrade time impact is 1.

[0111] The beneficial effects of the above technical solution are: it facilitates accurate monitoring of the upgrade process, quantifies the upgrade impact coefficient, and issues an alarm when the upgrade impact coefficient is determined to be greater than the preset impact threshold, so as to facilitate timely interruption of the upgrade and re-determining the upgrade method.

[0112] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A client-side intelligent upgrade guidance system based on app store status awareness, characterized in that, include: The acquisition module is used to call the version detection interface to obtain configuration information when the client starts up or logs in; The first determining module is used to determine the client's upgrade time based on the configuration information; The app store settings module is used to set the app store list and obtain app store status awareness information based on the upgrade time. The upgrade guidance module is used to guide the client through the upgrade process based on app store status awareness information. The app store settings module includes: The configuration module is used to pre-configure the list of app stores available on the client on the Portal. The list of app stores contains several app stores, and each app store is configured with attribute information, including name, package name, app store logo, client version number, and remarks. Pre-configure the app store list for the client on the Portal. Specifically: Log in to the Portal management backend with the administrator account, find the option to configure the app store list on the application management page, and click the "Add" or "Edit" button to configure the app store list; configure attribute information for each app store; the attribute information includes name, package name, app store logo, client version number and remarks; the package name is the unique identifier of the app store; The sorting module is used for: A dynamic update mechanism for app store ranking is built, which adjusts the display order in real time according to the configured version effective time and app store listing status. The latest client version number of each app store is obtained based on attribute information within a preset time period before the upgrade time. Sort the applications by latest client version number from largest to smallest to determine the sorted list, which will serve as status awareness information for the app store.

2. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 1, characterized in that, The acquisition module includes: The server-side component provides a version detection interface. The management platform is used to configure upgrade tasks and upgrade packages; the upgrade tasks include forced upgrades, normal upgrade strategies, and upgrade times; the upgrade packages include version numbers, upgrade packages uploaded to different clients, and upgrade instructions; The second determination module is used to call the version detection interface when the client starts or logs in to determine the client's current version information and the corresponding upgrade task and upgrade package as configuration information.

3. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 1, characterized in that, The upgrade guidance module is used to identify and display the first corresponding app store in the sorted list of app store status awareness information; and guide the client to upgrade based on the display result.

4. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 3, characterized in that, Upgrade the boot module for: When it is determined that no app store is available based on the app store status awareness information, the browser download fallback strategy will automatically trigger HTTPS download and verify the integrity of the downloaded installation package through file verification code. Once the verification is successful, the client will be guided to upgrade based on the downloaded installation package.

5. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 3, characterized in that, The upgrade guidance module guides the client through the upgrade process based on the displayed results, including: The extraction module is used to extract the upgrade tags of the upgrade package from the app store corresponding to the displayed results based on the extraction window; The verification module is used to verify the validity of the extracted upgrade tag. When the verification is successful, the client is guided to upgrade based on the upgrade tag.

6. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 5, characterized in that, The verification module includes: The third determining module is used for: Obtain the extraction parameters for extracting upgrade tags; the extraction parameters include the number of times the extraction window successfully reads upgrade tags within a unit data volume, the data rate of the upgrade package, the extraction range radius of the extraction window, and the time interval for extracting upgrade tags; The first effectiveness coefficient is determined based on the extracted parameters and the preset first weight coefficient; The fourth determination module is used to determine the accuracy rate of the upgrade label verified by manual annotation, and to determine the second validity coefficient based on the accuracy rate and the preset second weighting coefficient. The fifth determination module is used to determine the validity coefficient of the extracted upgrade label based on the first validity coefficient and the second validity coefficient, and compare it with the preset validity threshold; if the validity coefficient is greater than the preset validity threshold, it means that the validity verification of the upgrade label has passed; otherwise, it means that the validity verification of the upgrade label has not passed.

7. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 6, characterized in that, The verification module also includes: The filtering module is used to identify the type of upgrade tags, determine the type of each sub-tag within the upgrade tags, and perform cluster analysis to obtain several cluster sets. It then performs numerical processing on the sub-tags in each cluster set to determine the tag value of each sub-tag. The module calculates the distance between the tag value of each sub-tag and the tag values ​​of other sub-tags in the same cluster set. Based on the distance values, it calculates the variance and compares it with a preset variance value. Sub-tags with variance values ​​greater than the preset variance value are filtered out as problem tags and removed, resulting in the target cluster set. The associated module is used for: Determine the central label in each target cluster set, and determine the first association between other labels and the central label; determine the second association between the central labels of each target cluster set; and determine the label association graph based on the first and second associations. The upgrade order is determined based on the tag association diagram, and the client is guided to upgrade based on the upgrade order.

8. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 1, characterized in that, Also includes: The monitoring module is used to monitor the upgrade process during the upgrade guidance module's upgrade guidance of the client based on the app store status awareness information, obtain monitoring results, and display them.

9. The client-side intelligent upgrade guidance system based on app store status awareness as described in claim 8, characterized in that, The monitoring module includes: The first monitoring module is used to monitor upgrade failure information and determine the upgrade failure ratio based on the upgrade failure information; the upgrade failure information includes the total number of components involved in the upgrade process, the number of component categories that failed in the upgrade, the weight of the i-th type of failed component, and the number of the i-th type of failed component. The second monitoring module is used to monitor when the total upgrade time exceeds the expected time and determine the impact of the upgrade time. The calculation module is used to calculate the upgrade impact coefficient based on the upgrade failure rate and the impact of upgrade time. The upgrade impact coefficient is used as a monitoring result and displayed. When the upgrade impact coefficient is determined to be greater than the preset impact threshold, an alarm is issued.

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