Client intelligent upgrade guiding system based on application store state perception

Abstract

The invention discloses a client intelligent upgrade guide system based on application store state awareness, comprising: an acquisition module used for calling a version detection interface when a client is started or logged in to acquire configuration information; the first determination module is used for determining the upgrading time of the client according to the configuration information; the application store setting module is used for setting an application store list and acquiring application store state sensing information based on the upgrading time; and the upgrading guiding module is used for performing upgrading guiding on the client according to the application store state sensing information. According to the method, different application store states are fully considered, upgrading guidance is carried out on the client, the conditions of centralized upgrading and version upgrading rollback are avoided, the upgrading efficiency of the client is conveniently improved, and the risk of upgrading failure is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of upgrade booting, in particular to a client intelligent upgrade booting system based on application store state sensing. BACKGROUND

[0002] At present, there is an inconsistency problem of application store on-shelf version when upgrading the Android client, but the existing technology only performs simple version comparison and prompts the update without fully considering the application store state and user use scenarios and other factors, cannot intelligently upgrade booting according to different application store states and user needs, and is prone to cause centralized upgrade to cause large server concurrent pressure, slow upgrade file transmission speed, and even upgrade failure phenomenon, and is also prone to version upgrade rollback situation, resulting in low client upgrade efficiency and high upgrade failure risk. SUMMARY

[0003] The present application aims to at least solve one of the above technical problems in the technical field. To this end, the present application aims to propose a client intelligent upgrade booting system based on application store state sensing, fully consider different application store states, and upgrade boot the client to avoid centralized upgrade and version upgrade rollback situation, facilitate to improve the upgrade efficiency of the client, and reduce the risk of upgrade failure.

[0004] To achieve the above-mentioned purpose, the embodiment of the present application proposes a client intelligent upgrade booting system based on application store state sensing, comprising:

[0005] An acquisition module configured to call a version detection interface when the client is started or logged in to acquire configuration information;

[0006] A first determination module configured to determine the upgrade time of the client according to the configuration information;

[0007] An application store setting module configured to set an application store list and acquire application store state sensing information based on the upgrade time;

[0008] An upgrade booting module configured to upgrade boot the client according to the application store state sensing information.

[0009] According to some embodiments of the present application, the acquisition module comprises:

[0010] A server configured to provide a version detection interface;

[0011] A management platform configured to configure an upgrade task and an upgrade package; the upgrade task comprises a forced upgrade, a normal upgrade strategy and an upgrade time; the upgrade package comprises a version number, an upgrade package uploaded to different clients and an upgrade instruction;

[0012] A second determining module determines current version information of the client and corresponding upgrade tasks and upgrade packages as configuration information by calling a version detection interface when the client is started or logged in.

[0013] According to some embodiments of the application, the application store setting module comprises:

[0014] A configuration module is configured to pre-configure an application store list of the client on the Portal, wherein the application store list comprises a plurality of application stores, each of which is configured with attribute information; and the attribute information comprises a name, a package name, an application store logo, a client version number and a note.

[0015] A sorting module is configured to:

[0016] A sorting module is configured to:

[0017] The sorting module sorts the application stores according to the latest client version numbers from large to small to determine a sorting list as application store state sensing information.

[0018] According to some embodiments of the application, an upgrade guiding module is configured to determine and display a first application store corresponding to the sorting list in the application store state sensing information, and guide the client to upgrade according to the display result.

[0019] According to some embodiments of the application, the upgrade guiding module is configured to:

[0020] When no available application store is determined according to the application store state sensing information, the upgrade guiding module automatically triggers HTTPS download through a backup strategy of browsing and verifies the integrity of the downloaded installation package through a file verification code.

[0021] When the verification is passed, the upgrade guiding module guides the client to upgrade based on the downloaded installation package.

[0022] According to some embodiments of the application, the upgrade guiding module guides the client to upgrade according to the display result, comprising:

[0023] An extraction module is configured to extract an upgrade label of the upgrade package from the application store corresponding to the display result based on an extraction window.

[0024] A verification module is configured to verify the validity of the extracted upgrade label, and guide the client to upgrade based on the upgrade label when the verification is passed.

[0025] According to some embodiments of the application, the verification module comprises:

[0026] The third determining module is used for:

[0027] The extraction parameter of the extraction upgrade label is acquired; the extraction parameter comprises the number of times of successful reading of the upgrade label in the unit data amount, the data rate of the upgrade package, the extraction range radius of the extraction window and the time interval of the extraction upgrade label;

[0028] The first validity coefficient is determined according to the extraction parameter and the preset first weight coefficient;

[0029] The fourth determining module is used for determining the accuracy rate of the upgrade label passing the artificial annotation verification, and determining the second validity coefficient according to the accuracy rate and the preset second weight coefficient;

[0030] The fifth determining module is used for determining the validity coefficient of the extraction upgrade label according to the first validity coefficient and the second validity coefficient, and comparing the validity coefficient with the preset validity threshold; when it is determined that the validity coefficient is greater than the preset validity threshold, it is indicated that the validity verification of the upgrade label passes; otherwise, it is indicated that the validity verification of the upgrade label does not pass.

[0031] According to some embodiments of the present application, the verification module further comprises:

[0032] The screening module is used for type identification on the upgrade label, determining the type of each sub-label in the upgrade label, and performing cluster analysis to obtain a plurality of cluster sets; the sub-labels in each cluster set are subjected to numerical value processing to determine the label values of the sub-labels; the distance values of the label values of each sub-label and the label values of other sub-labels in the same cluster set are calculated respectively; the variance value is calculated according to the distance values, and compared with the preset variance value; the sub-labels with the variance value greater than the preset variance value are screened out as problem labels and removed to obtain a target cluster set;

[0033] The association module is used for:

[0034] The center label in each target cluster set is determined, the first association relationship between the other labels and the center label is determined, the second association relationship between the center labels of the target cluster sets is determined, and the label association graph is determined according to the first association relationship and the second association relationship;

[0035] The upgrade order is determined according to the label association graph, and the client is guided for upgrade based on the upgrade order.

[0036] According to some embodiments of the present application, the monitoring module is used for monitoring the upgrade process to obtain a monitoring result and display the monitoring result when the upgrade guiding module guides the client for upgrade according to the application store state sensing information.

[0037] According to some embodiments of the present application, the monitoring module comprises:

[0038] The first monitoring module is used for monitoring upgrade failure information, determining an upgrade failure ratio according to the upgrade failure information, wherein the upgrade failure information comprises a total component number involved in an upgrade process, a component category number of upgrade failure, a weight of the i-th category of failed components and a quantity of the i-th category of failed components;

[0039] The second monitoring module is used for monitoring that a total upgrade time consumption exceeds an expected time, and determining an upgrade time consumption influence.

[0040] The calculation module is used for calculating an upgrade influence coefficient according to the upgrade failure ratio and the upgrade time consumption influence.

[0041] The upgrade influence coefficient is taken as a monitoring result and displayed, and an alarm prompt is sent when the upgrade influence coefficient is greater than a preset influence threshold.

[0042] The application provides a client intelligent upgrade guiding system based on application store state sensing, which 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 upgrade failure risk.

[0043] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the application. The objects and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims.

[0044] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0045] The accompanying drawings are included to provide a further understanding of the application, and constitute a part of the specification, illustrate the application, and are used to explain the application together with the embodiments of the application, and do not constitute a limitation on the application. In the drawings:

[0046] Figure 1 is a block diagram of a client intelligent upgrade guiding system based on application store state sensing according to an embodiment of the present application;

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

[0048] Figure 3 is a schematic diagram of guiding the upgrade of the client according to the application store state sensing information according to an embodiment of the present application. DETAILED DESCRIPTION

[0049] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, in which it is understood that the preferred embodiments described below are merely used to illustrate and explain the present application, and are not used to limit the present application.

[0050] As shown in Figure 1 The application embodiment proposes a client intelligent upgrade guiding system based on application store state perception, which comprises:

[0051] The acquisition module is configured to call a version detection interface when the client is started or logged in, and acquire configuration information.

[0052] The first determination module is configured to determine the upgrade time of the client according to the configuration information.

[0053] The application store setting module is configured to set an application store list, and acquire application store state perception information based on the upgrade time.

[0054] The upgrade guiding module is configured to guide the upgrade of the client according to the application store state perception information.

[0055] The working principle of the above technical solution is as follows: the acquisition module is configured to call a version detection interface when the client is started or logged in, and acquire configuration information; the first determination module is configured to determine the upgrade time of the client according to the configuration information; the application store setting module is configured to set an application store list, and acquire application store state perception information based on the upgrade time; the application stores include application treasure, Xiaomi, Huawei, Baidu, etc. The latest version information of each application store before the upgrade is determined based on the upgrade time, and is sorted as the application store state perception information. The upgrade guiding module guides the upgrade of the client according to the application store state perception information.

[0056] The above technical solution has the following beneficial effects: the upgrade of the client is guided by fully considering the state of different application stores, so that the centralized upgrade and version upgrade rollback can be avoided, the upgrade efficiency of the client is improved, and the risk of upgrade failure is reduced.

[0057] According to some embodiments of the present application, the acquisition module comprises:

[0058] The server is configured to provide a version detection interface.

[0059] The management platform is configured to configure an upgrade task and an upgrade package; the upgrade task comprises a forced upgrade, a normal upgrade strategy and an upgrade time; the upgrade package comprises a version number, an upgrade package uploaded by different clients and an upgrade instruction.

[0060] The second determination module is configured to call the version detection interface when the client is started or logged in, and determine the current version information of the client and the corresponding upgrade task and upgrade package as the configuration information.

[0061] The above technical solution works as follows: Forced upgrades are targeted at incompatible versions, while standard upgrade strategies are supported for compatible versions, including "later," "skip," and selection. The second determination module calls the version detection interface upon client startup or login to determine the client's current version information, the corresponding upgrade task, and the upgrade package, which serve as configuration information.

[0062] The beneficial effects of the above technical solution are: facilitating accurate determination of configuration information, and determining information such as upgrade strategy and upgrade time.

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

[0064] The configuration module is used to pre-configure the application store list on the client on the portal. The application store list contains several application stores, and each application store is configured with attribute information; the attribute information includes the name, package name, application store logo, client version number and remarks;

[0065] Sorting module for:

[0066] Build a dynamic update mechanism for app store sorting, adjust the display order in real time based on the configured version effective time and app store listing status, and obtain the latest client version number of each app store based on attribute information in a preset time period before the upgrade time;

[0067] Sort the latest client version numbers from large to small to determine the sorted list, which serves as the app store status perception information.

[0068] The working principle of the above technical solution is: pre-configure the list of application stores on the client on the Portal, specifically: log in to the Portal management backend based on the administrator account, find the option to configure the application store list on the application management page, click the "Add" or "Edit" button to configure the application store list. Each application store is configured with attribute information; the attribute information includes the name, package name, application store logo, client version number and remarks; the package name is the unique identifier of the application store, such as com.tencent.android.qqdownloader. The sorting module constructs a dynamic update mechanism for application store sorting, adjusts the display order in real time according to the effective time of the configured version and the application store listing status, obtains the latest client version number of each application store based on the attribute information in a preset time period before the upgrade time, sorts from large to small according to the latest client version number, and determines the sorting list as application store status perception information.

[0069] The technical scheme has the beneficial effects that: the latest client version number of each application store before the upgrade time is obtained conveniently, and is sorted, so that the application store state sensing information can be determined accurately.

[0070] According to some embodiments of the application, the upgrade guide module is used to determine the first application store corresponding to the sorted list in the application store state sensing information and display the first application store, and guide the client to upgrade according to the display result.

[0071] The technical scheme has the beneficial effects that: the latest client version number of each application store before the upgrade time is obtained conveniently, and is sorted, so that the application store state sensing information can be determined accurately.

[0072] The technical scheme has the beneficial effects that: the latest client version number of each application store before the upgrade time is obtained conveniently, and is sorted, so that the application store state sensing information can be determined accurately.

[0073] As shown in the figure, the sorted list in the application store state sensing information is determined and displayed, so that the user can select an upgrade mode, and the user experience is improved. Figure 3

[0074] According to some embodiments of the application, the upgrade guide module is used to:

[0075] When no available application store is determined according to the application store state sensing information, the fallback strategy is triggered automatically to download the HTTPS download through the browser, and the integrity of the downloaded installation package is verified through the file verification code.

[0076] When the verification is passed, the client is guided to upgrade based on the downloaded installation package.

[0077] The technical scheme has the beneficial effects that: the latest client version number of each application store before the upgrade time is obtained conveniently, and is sorted, so that the application store state sensing information can be determined accurately.

[0078] ​The technical scheme has the beneficial effects that: when it is determined that there is no available application store according to the application store state sensing information, the verification of the upgrade and installation package is performed through the browser, the redundant support of the upgrade is provided, and the upgrade mode is enriched.

[0079] According to some embodiments of the application, the upgrade guiding module performs upgrade guiding on the client according to the display result, including:

[0080] The extraction module extracts the upgrade label of the upgrade package from the application store corresponding to the display result based on the extraction window;

[0081] The verification module verifies the validity of the extracted upgrade label, and performs upgrade guiding on the client based on the upgrade label when it is determined that the verification is passed.

[0082] The technical scheme has the beneficial effects that: when it is determined that there is no available application store according to the application store state sensing information, the verification of the upgrade and installation package is performed through the browser, the redundant support of the upgrade is provided, and the upgrade mode is enriched.

[0083] The technical scheme has the beneficial effects that: when it is determined that there is no available application store according to the application store state sensing information, the verification of the upgrade and installation package is performed through the browser, the redundant support of the upgrade is provided, and the upgrade mode is enriched.

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

[0085] The third determination module is configured to:

[0086] The extraction parameter of the extracted upgrade label is obtained, and the extraction parameter includes the number of times that the extraction window successfully reads the upgrade label in a unit data amount, the data rate of the upgrade package, the extraction range radius of the extraction window, and the time interval of the extracted upgrade label;

[0087] The first validity coefficient is determined according to the extraction parameter and a preset first weight coefficient;

[0088] The fourth determination module is configured to determine the accuracy rate of the upgrade label verified by manual annotation, and determine a second validity coefficient according to the accuracy rate and a preset second weight coefficient;

[0089] The fifth determination module is configured to determine the validity coefficient of the extracted upgrade label according to the first validity coefficient and the second validity coefficient, and compare the validity coefficient with a preset validity threshold; when it is determined that the validity coefficient is greater than the preset validity threshold, it is indicated that the validity verification of the upgrade label is passed; otherwise, it is indicated that the validity verification of the upgrade label is not passed.

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

[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 of 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 rate verified by manual annotation. is the effectiveness of the automatic extraction process. β·A is the accuracy of manual annotation verification. λ is a comprehensive reflection of the effectiveness of the automatic extraction process and the accuracy of 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 the 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 screening module is used to identify the type of the upgrade tag, determine the type of each subtag in the upgrade tag, and perform cluster analysis to obtain several cluster sets; perform numerical processing on the subtags in each cluster set to determine the label value of each subtag; calculate the distance between the label value of each subtag and the label values ​​of other subtags in the same cluster set; calculate the variance value based on the distance value and compare it with the preset variance value; screen out subtags with variance values ​​greater than the preset variance value as problem labels and eliminate them to obtain the target cluster set;

[0096] Association modules for:

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

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

[0099] The working principle of the above technical solution is as follows: The screening module identifies the type of the upgrade tag, determines the type of each subtag within the upgrade tag, and performs cluster analysis to obtain several cluster sets. The subtags within each cluster set are numerically processed to determine the label value of each subtag. The distance between the label value of each subtag and the label values ​​of other subtags in the same cluster set is calculated. The variance value is calculated based on the distance value, which reflects the degree of dispersion of the subtags within the cluster set. This variance value is then compared with a preset variance value. Subtags with variance values ​​greater than the preset variance value are screened as problematic labels and removed, thereby obtaining an accurate cluster set, namely the target cluster set. The association module determines the central label: Method 1: By analyzing the label attributes and frequency of occurrence, the representativeness of each label within 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 total distance to other labels is selected as the central label. The distances between the other labels and the central label are determined, thereby determining the first association relationship between the other labels and the central label. The first association relationship represents the association between different tags within the same target cluster. The second association relationship represents the degree of association between the central tags of different target clusters. Association rule mining is used to learn the association between central tags. Based on the first and second association relationships, a tag association graph is determined. The tag association graph determines the upgrade sequence, and client upgrade guidance is provided based on the upgrade sequence.

[0100] The beneficial effects of the above technical solution are: the upgrade tags are screened to improve the accuracy of the upgrade tags, and the upgrade tags are divided into sets. According to the association between the tags within the set and the tags between the sets, a tag association graph is determined. The tag association graph facilitates the accurate determination of the upgrade order, thereby improving the efficiency and accuracy of the upgrade guidance.

[0101] According to some embodiments of the present invention, it further includes: a monitoring module for monitoring the upgrade process during the process in which the upgrade guidance module guides the client to upgrade according to the application store status perception information, obtaining and displaying the monitoring results.

[0102] The working principle and beneficial effects of the above technical solution: The monitoring module is used to monitor the upgrade process during the process in which the upgrade guidance module guides the client to upgrade according to the application store status perception information, obtain the monitoring results and display them, so as to facilitate timely and accurate determination of the specific situation of the upgrade, and facilitate timely processing when an upgrade anomaly occurs.

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

[0104] A first monitoring module is configured to monitor upgrade failure information and determine an 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 to upgrade, the weight of the i-th category of failed components, and the number of the i-th category of failed components;

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

[0106] A calculation module is used to calculate the upgrade impact coefficient based on the upgrade failure ratio and the upgrade time impact;

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

[0108] The working principle of the above technical solution is as follows: Based on the first monitoring module, the upgrade failure information is monitored to facilitate the accurate determination of the upgrade failure ratio. Based on the second monitoring module, it is used to monitor the total upgrade time exceeding the expected time and determine the impact of the upgrade time; the calculation module calculates the upgrade impact coefficient based on the upgrade failure ratio and the upgrade time impact; the upgrade impact coefficient is used as the monitoring result and displayed, and when it is determined that the upgrade impact coefficient is greater than the preset impact threshold, an alarm prompt is issued. The preset impact threshold is the threshold value of the preset task upgrade impact that is acceptable. The upgrade impact coefficient is:

[0109]

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

[0111] The beneficial effects of the above technical solution are: it is convenient to accurately monitor the upgrade process, quantify it based on the upgrade impact coefficient, and issue an alarm when it is determined that the upgrade impact coefficient is greater than the preset impact threshold, so as to facilitate timely interruption of the upgrade and re-determination of the upgrade method.

[0112] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A client intelligent upgrade guidance system based on application store status perception, characterized in that: include: The acquisition module is used to call the version detection interface when the client is started or logged in to obtain configuration information; A first determining module, configured to determine an upgrade time of the client according to the configuration information; The app store setting module is used to set the app store list and obtain app store status perception information based on the upgrade time; The upgrade guidance module is used to guide the client to upgrade based on the application store status perception information.

2. The client intelligent upgrade guidance system based on application store status perception according to claim 1, characterized in that: The acquisition module includes: The server is used to provide a version detection interface; Management platform, used to configure upgrade tasks and upgrade packages; the upgrade tasks include mandatory upgrades, common upgrade strategies and upgrade times; the upgrade packages include version numbers, upgrade packages for uploading different clients and upgrade instructions; The second determination module is used to call the version detection interface when the client is started or logged in, and determine the current version information of the client and the corresponding upgrade task and upgrade package as configuration information.

3. The client intelligent upgrade guidance system based on application store status perception according to claim 1, characterized in that: App store settings module, including: The configuration module is used to pre-configure the application store list on the client on the portal. The application store list contains several application stores, and each application store is configured with attribute information; the attribute information includes the name, package name, application store logo, client version number and remarks; Sorting module for: Build a dynamic update mechanism for app store sorting, adjust the display order in real time based on the configured version effective time and app store listing status, and obtain the latest client version number of each app store based on attribute information in a preset time period before the upgrade time; Sort the latest client version numbers from large to small to determine the sorted list, which serves as the app store status perception information.

4. The client intelligent upgrade guidance system based on application store status perception according to claim 3, characterized in that: The upgrade guidance module is used to determine the first corresponding application store in the sorted list in the application store status perception information and display it; and guide the client to upgrade according to the displayed result.

5. The client intelligent upgrade guidance system based on application store status perception according to claim 4, characterized in that: Upgrade the boot module for: When no app store is available based on app store status awareness, the browser download fallback policy automatically triggers HTTPS downloads and verifies the integrity of the downloaded installation package using a file verification code. When the verification is confirmed to be successful, the client is guided to upgrade based on the downloaded installation package.

6. The client intelligent upgrade guidance system based on application store status perception according to claim 4, characterized in that: The upgrade guidance module guides the client to upgrade according to the displayed results, including: An extraction module, configured to extract the upgrade tag of the upgrade package from the application store corresponding to the displayed result based on the extraction window; The verification module is used to verify the validity of the extracted upgrade tag, and when it is determined that the verification is passed, the client is guided to upgrade based on the upgrade tag.

7. The client intelligent upgrade guidance system based on application store status perception according to claim 6, characterized in that: Verification modules, including: The third determining module is configured to: Obtaining extraction parameters for extracting upgrade tags; the extraction parameters include the number of times the extraction window successfully reads the upgrade tag 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 the upgrade tag; Determining a first validity coefficient based on the extraction parameters and a preset first weight coefficient; a fourth determination module, configured to determine an accuracy rate of the upgrade tag verified by manual annotation, and determine a second validity coefficient based on the accuracy rate and a preset second weight coefficient; The fifth determination module is used to determine the validity coefficient of the extracted upgrade tag based on the first validity coefficient and the second validity coefficient, and compare it with the preset validity threshold; when it is determined that the validity coefficient is greater than the preset validity threshold, it indicates that the validity verification of the upgrade tag has passed; otherwise, it indicates that the validity verification of the upgrade tag has failed.

8. The client intelligent upgrade guidance system based on application store status perception according to claim 7, characterized in that: The verification module also includes: The screening module is used to identify the type of the upgrade tag, determine the type of each subtag in the upgrade tag, and perform cluster analysis to obtain several cluster sets; perform numerical processing on the subtags in each cluster set to determine the label value of each subtag; calculate the distance between the label value of each subtag and the label values ​​of other subtags in the same cluster set; calculate the variance value based on the distance value and compare it with the preset variance value; screen out subtags with variance values ​​greater than the preset variance value as problem labels and eliminate them to obtain the target cluster set; Association modules for: Determine the central label in each target cluster set, determine a first association relationship between other labels and the central label; determine a second association relationship between the central labels of each target cluster set; and determine a label association graph based on the first association relationship and the second association relationship; The upgrade sequence is determined according to the tag association diagram, and the client is guided to upgrade based on the upgrade sequence.

9. The client intelligent upgrade guidance system based on application store status perception according to claim 1, characterized in that: Also includes: The monitoring module is used to monitor the upgrade process, obtain the monitoring results and display them when the upgrade guidance module guides the client to upgrade according to the application store status perception information.

10. The client intelligent upgrade guidance system based on application store status perception according to claim 9, characterized in that: Monitoring module, including: A first monitoring module is configured to monitor upgrade failure information and determine an 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 to upgrade, the weight of the i-th category of failed components, and the number of the i-th category of failed components; The second monitoring module is used to monitor the time when the total upgrade time exceeds the expected time and determine the impact of the upgrade time; A calculation module is used to calculate the upgrade impact coefficient based on the upgrade failure ratio and the upgrade time impact; The upgrade impact coefficient is used as a monitoring result and displayed. When it is determined that the upgrade impact coefficient is greater than a preset impact threshold, an alarm prompt is issued.

Images