Application upgrade method, device, electronic device and computer readable storage medium

Abstract

The embodiments of the present application disclose an application upgrade method, device, electronic device and computer-readable storage medium, including: obtaining reference scoring data of at least one application to be upgraded after the upgrade, the reference scoring data including scoring data of the upgraded application on at least one evaluation dimension by a reference user; collecting historical scoring records of users for at least one reference application; extracting historical scoring data on at least one evaluation dimension from the historical scoring records; determining a target application preferred by the user from at least one application to be upgraded based on the historical scoring data and the reference scoring data; sending upgrade data of the target application to a terminal device of the user, so that the terminal device upgrades the target application based on the upgrade data; by obtaining and referring to the scoring data of at least one evaluation dimension, the accuracy of selecting the application to be upgraded is improved, the user experience is improved, and the risk of application complaints is reduced.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an application upgrading method, device, electronic device and computer-readable storage medium. Background Art

[0002] With the rapid development of computer technology, there are more and more types of applications on terminal devices, and each application is constantly updated and iterated, and new functions are constantly generated. Therefore, it is necessary to update the applications on terminal devices;

[0003] However, due to different levels of users' acceptance of new features, the upgrade of some application functions may cause negative feedback from users, such as user complaints, low ratings, etc. Therefore, if users upgrade every application, some applications may easily cause poor user experience after the upgrade, and even affect the brand's reputation. Summary of the invention

[0004] The embodiments of the present application provide an application upgrade method, device, electronic device, and computer-readable storage medium, which can improve the accuracy of selecting applications to be upgraded.

[0005] The present application embodiment provides an application upgrade method, including:

[0006] Acquire reference rating data of at least one application to be upgraded after upgrading, wherein the reference rating data includes rating data of the upgraded application by a reference user in at least one evaluation dimension;

[0007] Collecting historical rating records of users for at least one reference application;

[0008] Extracting historical scoring data on the at least one evaluation dimension from the historical scoring records;

[0009] Determining a target application preferred by the user from the at least one application to be upgraded according to the historical rating data and the reference rating data;

[0010] The upgrade data of the target application is sent to the terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data.

[0011] Accordingly, the embodiment of the present application also provides an application upgrade device, including:

[0012] An acquisition module, configured to acquire reference rating data of at least one application to be upgraded after upgrading, wherein the reference rating data includes rating data of a reference user on at least one evaluation dimension of the upgraded application;

[0013] A collection module, used to collect historical rating records of users for at least one reference application;

[0014] An extraction module, configured to extract historical scoring data on at least one evaluation dimension from the historical scoring records;

[0015] A determination module, configured to determine the target application preferred by the user from the at least one application to be upgraded according to the historical rating data and the reference rating data;

[0016] The push module is used to send the upgrade data of the target application to the terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data.

[0017] Optionally, in some embodiments of the present application, the determining module includes:

[0018] A first determining unit, configured to determine the user's dimension attention level for each evaluation dimension according to the historical rating data;

[0019] A second determining unit is configured to determine a target application preferred by the user from among the at least one application to be upgraded according to the dimension attention level and the reference scoring data.

[0020] Optionally, in some embodiments of the present application, the second determining unit includes:

[0021] A first determining subunit, configured to determine at least one target evaluation dimension that the user is concerned about according to the dimension attention level;

[0022] A first acquisition subunit is used to respectively acquire dimension reference scoring data of each target evaluation dimension from the reference scoring data;

[0023] The second determining subunit is used to determine, for each of the target evaluation dimensions, when the dimension reference score data is greater than or equal to a preset score threshold, the upgraded application corresponding to the dimension reference score data as the target application preferred by the user.

[0024] Optionally, in some embodiments of the present application, the first determining unit includes:

[0025] A third determining subunit is used to determine the complaint probability of the user in each evaluation dimension according to the scoring data of the user in each evaluation dimension;

[0026] A fourth determining subunit, configured to determine the user's dimension attention level in each evaluation dimension according to the complaint probability;

[0027] Based on the third determining subunit and the fourth determining subunit, the first determining subunit is specifically configured to:

[0028] Used to determine the complaint probability of the user in each evaluation dimension according to the dimension attention level;

[0029] When the complaint probability is greater than or equal to a preset probability threshold, the evaluation dimension corresponding to the complaint probability is determined as the target evaluation dimension.

[0030] Optionally, in some embodiments of the present application, the first determining unit further includes:

[0031] A first acquisition subunit is used to acquire, from the historical rating data, the number of complaints made by the user in each evaluation dimension;

[0032] A fifth determination subunit, configured to determine a complaint risk value of each evaluation dimension according to the number of complaints;

[0033] The sixth determination subunit is used to determine the dimension attention level of the user in each evaluation dimension according to the complaint risk value.

[0034] Optionally, in some embodiments of the present application, the sixth determining subunit is specifically used to:

[0035] It is used to determine the dimension attention level corresponding to each complaint risk value for each evaluation dimension, and to determine the complaint quantity range corresponding to each complaint risk value;

[0036] When the number of complaints for an evaluation dimension reaches any of the complaint number intervals, the dimension attention level corresponding to any of the complaint number intervals is determined as the dimension attention level of the user for the evaluation dimension.

[0037] Optionally, in some embodiments of the present application, the determination module includes:

[0038] The third determining unit is used to determine, for each evaluation dimension, when the scoring data in the reference scoring data are all greater than the scoring data in the historical scoring data, the upgraded application corresponding to the reference scoring data as the target application preferred by the user.

[0039] The embodiment of the present application determines a target application to be upgraded that is preferred by the user based on reference rating data of the application to be upgraded after the upgrade and historical rating data of the reference application by the user, so that the acquired target application is more acceptable to the user or more in line with the user's needs after the update, wherein the accuracy of the selection of the application to be upgraded is improved by acquiring and referring to the rating data of at least one evaluation dimension. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 It is a scenario diagram of the application upgrade method provided in the embodiment of the present application;

[0042] Figure 2 It is a flowchart of the application upgrade method provided in the embodiment of the present application;

[0043] Figure 3 is a structural diagram of an application upgrade device provided in an embodiment of the present application;

[0044] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in this application to clearly and completely describe the technical solutions in this application. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0046] The embodiments of the present application provide an application upgrade method, device, electronic device and computer-readable storage medium. Specifically, the application upgrade method provided in the embodiments of the present application can be executed by an electronic device, wherein the electronic device includes a terminal device or a server; wherein the terminal device can be a television, a mobile phone, a notebook, a desktop or a tablet computer, etc.; the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks (CDN, Content Delivery Network), and big data and artificial intelligence platforms, etc. The server can be directly or indirectly connected via wired or wireless communication.

[0047] Specifically, the embodiment of the present application takes the terminal device and the server jointly executing the application upgrade method as an example, and the terminal device or the server separately executing the application upgrade solution can be understood by taking the terminal device and the server jointly executing the application upgrade method as an example, wherein, refer to Figure 1The specific process of the terminal device and the server jointly executing the application upgrade method is as follows:

[0048] Terminal device A sends application information of at least one application to be upgraded to server B. After server B obtains the information of at least one application that needs to be upgraded on terminal device A, it obtains the scoring data of at least one evaluation dimension of the above-mentioned application after the upgrade, and forms reference scoring data corresponding to each application. Then, server B collects historical scoring records of the user holding terminal device A for at least one reference application, and divides and extracts the historical scoring records according to the above-mentioned at least one evaluation dimension to obtain the user's historical scoring data. Subsequently, server B determines the upgraded application preferred by the user based on the reference scoring data and the historical scoring data, and determines the application to be upgraded (target application) preferred by the user based on the upgraded application preferred by the user. Subsequently, the upgrade data corresponding to the target application is sent to terminal device A, prompting terminal device A to upgrade the application.

[0049] Among them, the applications to be upgraded may include applications for silent upgrade. For the applications for silent upgrade, after the terminal device A receives the upgrade data, the upgraded application can automatically complete the upgrade according to the set value of the scheduled upgrade without disturbing the user (without displaying the upgrade program interface).

[0050] Among them, for silent upgrade applications, since users are not aware of or it is difficult to detect the upgrade process, after the relevant applications in the user's terminal device A are updated through silent upgrades, when there are some new versions or new functions that users do not want to use, it is easy for users to complain about the new functions or new versions, reducing user experience and even affecting the reputation of the brand corresponding to the application.

[0051] Therefore, in an embodiment of the present application, based on silent upgrade applications, the above-mentioned application upgrade method can be used to screen out user-preferred applications, and silent upgrades can be performed on the screened user-preferred applications, which can effectively reduce user complaints about new versions or new functions and facilitate user acceptance.

[0052] The embodiment of the present application determines a target application to be upgraded that is preferred by the user based on reference rating data of the application to be upgraded after the upgrade and historical rating data of the reference application by the user, so that the acquired target application is more acceptable to the user or more in line with the user's needs after the update, wherein the accuracy of the selection of the application to be upgraded is improved by acquiring and referring to the rating data of at least one evaluation dimension.

[0053] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0054] See also Figure 2 , Figure 2 A schematic diagram of a process flow of an application upgrade method provided in an embodiment of the present application. The specific process flow of the application upgrade method may be as follows:

[0055] 101. Obtain reference rating data of at least one application to be upgraded after upgrading, wherein the reference rating data includes rating data of a reference user on at least one evaluation dimension of the upgraded application.

[0056] The reference users may be internal test users of the application upgrade or ordinary public users who have completed the corresponding application upgrade. The reference users' rating data on the upgraded application can indicate the overall satisfaction of most users with the upgraded application.

[0057] Among them, the evaluation dimensions may include the operation fluency, ease of use, interface aesthetics or functionality of the application. By obtaining the rating data of the application from multiple evaluation dimensions, the reference rating data can be more specific and targeted. The rating data of each evaluation dimension can be used to obtain various aspects of the performance of the upgraded application, such as the operation fluency, ease of operation, and aesthetics of the interface.

[0058] In the embodiment of the present application, as shown in Table 1, the score data of each evaluation dimension of the upgraded application (application A, B or C) includes 5 gradients, for example, score data 1-5, wherein the higher the score, the better the performance of the corresponding evaluation dimension, for example, in terms of operation fluency, an application with a score of 5 operates more smoothly than an application with a score of 3. In order to ensure the accuracy and validity of the data, the average score data corresponding to each evaluation dimension can be obtained by using the average value.

[0059] Operation Fluency Ease of use Interface aesthetics Functional Application A 5 5 2 3 Application B 3 1 5 5 Application C 5 4 4 4

[0060] Table 1

[0061] Among them, by obtaining rating data of multiple evaluation dimensions, users' ratings of upgraded applications from multiple angles can be obtained, which is convenient for comprehensively understanding the performance data of the application and facilitating the recommendation of applications to be upgraded to users based on a certain evaluation dimension.

[0062] 102. Collect historical rating records of users for at least one reference application.

[0063] The reference applications include other applications in the user terminal device, or applications of the same type as the application to be upgraded, for example, all of them are game competition applications, or all of them are quiz applications, or all of them are film and television applications, etc.

[0064] The historical rating records of the reference application indicate the user's expectations of the application. For example, if the user gives more comments on the fluency of the application, or the fluency ratings are often low, it indicates that the user has higher requirements for the fluency of the application.

[0065] Among them, by obtaining rating data of applications of the same type, the user's expected satisfaction with the current application to be upgraded can be more accurately obtained, thereby improving the accuracy of subsequent target application selection.

[0066] 103. Extract historical scoring data on the at least one evaluation dimension from the historical scoring records.

[0067] Among them, by obtaining historical rating data on each evaluation dimension, it is convenient to make recommendations for applications to be upgraded based on the rating data of each evaluation dimension.

[0068] Among them, in the embodiments of the present application, the extraction of scoring data on each evaluation dimension can be carried out by manually classifying and determining the scoring data on each evaluation dimension, and the comment data can be identified and extracted based on a text recognition algorithm or an image recognition algorithm, and the scoring data of the comment data can be determined by a machine learning method or a sentiment analysis algorithm. The specific method is not limited here.

[0069] Among them, for the scoring data of each evaluation dimension, the user's scoring data for each evaluation dimension can be obtained by taking an average value (for example, for each evaluation dimension, the average value of multiple scoring data in the historical scoring records is taken as the final scoring data of the evaluation dimension), and the scoring data of each evaluation dimension is taken as the user's basic requirement value for each evaluation dimension. That is, for each evaluation dimension, when the scoring data is greater than the basic requirement value, it is considered that the user can accept the current upgrade of the current application, thereby improving the accuracy of the recommendation of applications to be upgraded.

[0070] 104. Determine a target application preferred by the user from the at least one application to be upgraded according to the historical rating data and the reference rating data.

[0071] Among them, the historical rating data shows the user's expectations for each evaluation dimension of the application, and the reference rating data shows the comprehensive objective performance data of the target application in each evaluation dimension. Based on the objective performance data of the application and the user's expectations, it is determined whether the application meets the user's expectations and whether the application is the user's preferred application, so as to select the target application.

[0072] Among them, based on historical rating data and reference rating data, the user's preferred applications can be determined, the accuracy of recommendation or selection of applications to be upgraded can be improved, the user experience can be improved, and user complaints can be reduced.

[0073] For example, whether the application meets the user's needs can be determined based on whether the score data of each evaluation dimension in the reference score data is greater than the score data in the historical score data. That is, optionally, in some embodiments, the step of "determining the target application preferred by the user from the at least one application to be upgraded based on the historical score data and the reference score data" can specifically include:

[0074] For each evaluation dimension, when the score data in the reference score data are all greater than the score data in the historical score data, the upgraded application corresponding to the reference score data is determined as the target application preferred by the user.

[0075] Among them, when the score data of each evaluation dimension in the reference score data of the upgraded application is greater than the corresponding score data in the user's historical score data, it means that the score data of the current upgraded application meets the user's needs and can be recommended to the user.

[0076] Among them, by comparing the scoring data of each evaluation dimension, the recommended application can meet the needs of users in all aspects.

[0077] When determining the target application to be recommended, the selection may be made based on the user's level of attention to each evaluation dimension. That is, optionally, in some embodiments, the step of "determining the target application preferred by the user from the at least one application to be upgraded based on the historical rating data and the reference rating data" may specifically include:

[0078] Determining the user's dimension attention level for each evaluation dimension according to the historical rating data;

[0079] According to the dimension attention level and the reference score data, a target application preferred by the user is determined from the at least one application to be upgraded.

[0080] For example, the dimension attention level may include level one, level two, level three, level four or level five, where level one indicates that the user pays the highest attention to the evaluation dimension. Therefore, the target applications may be screened in order according to the level.

[0081] Among them, the dimension attention level obtained through historical scoring data is more accurate, which improves the accuracy of the selection of applications to be upgraded.

[0082] Among them, after determining the user's dimension attention level for each evaluation dimension, several evaluation dimensions that the user focuses on can be determined according to the dimension attention level, and the target application can be selected according to the several evaluation dimensions that the user focuses on. For example, when the rating data of several evaluation dimensions that the user cares about meets the requirements, it can be considered that the corresponding upgraded application can meet the user's needs. That is, optionally, in some embodiments, the step of "determining the target application preferred by the user from the at least one application to be upgraded according to the dimension attention level and the reference rating data" can specifically include:

[0083] Determining at least one target evaluation dimension that the user is concerned about according to the dimension attention level;

[0084] Respectively obtaining dimension reference scoring data of each target evaluation dimension from the reference scoring data;

[0085] For each of the target evaluation dimensions, when the dimension reference score data is greater than or equal to a preset score threshold, the upgraded application corresponding to the dimension reference score data is determined as the target application preferred by the user.

[0086] Among them, by determining the dimension attention level, several evaluation dimensions that users focus on can be obtained. Therefore, when the scoring data of the application in the above-mentioned evaluation dimensions meets the requirements (preset scoring thresholds), it can be determined that these applications meet the user's needs or are within the acceptable range for users.

[0087] For example, please refer to Table 1. If the user has high requirements for the operation fluency of the application (i.e., the operation fluency is the target evaluation dimension), has no requirements for ease of use and interface aesthetics, and has general functional requirements, then application A and application C can be pushed to the user, and application B is not recommended for upgrade due to its low fluency. Alternatively, if the user has no requirements for operation fluency and ease of use, but has high requirements for interface aesthetics and functionality, then application B or application C can be recommended to the user.

[0088] Among them, for each target evaluation dimension, the preset scoring threshold can be determined based on the average value of the scoring data of the corresponding target evaluation dimension in the historical scoring data, and can also be set to a higher value according to actual needs to ensure that it can meet user needs or be accepted by users.

[0089] The dimension attention level of each evaluation dimension may be determined according to the complaint probability, that is, optionally, in some embodiments, the step of "determining the dimension attention level of the user for each evaluation dimension according to the historical rating data" may specifically include:

[0090] Determining the complaint probability of the user in each evaluation dimension according to the scoring data of the user in each evaluation dimension;

[0091] The dimension attention level of the user in each evaluation dimension is determined according to the complaint probability.

[0092] Among them, in the embodiment of the present application, the complaint probability is the ratio of the number of complaints to the total number of evaluations, wherein the higher the complaint probability, the higher the user's requirements for this evaluation dimension, and also the higher the user's attention to this evaluation dimension. Therefore, the complaint probability is used to determine the user's dimension attention level in each evaluation dimension, so as to facilitate the subsequent determination of the target evaluation dimension that the user pays attention to based on the dimension attention level.

[0093] Among them, in the embodiment of the present application, the evaluation with a lower score means a higher risk of user complaint, and therefore, the evaluation with a lower score can be used as a complaint data.

[0094] Among them, a mapping relationship between the complaint probability and the dimension attention level can be established, and based on the mapping relationship, the dimension attention level corresponding to the complaint probability corresponding to the evaluation dimension is determined.

[0095] The target evaluation dimension that the user is concerned about may be determined according to the complaint probability. That is, optionally, in some embodiments, the step of “determining at least one target evaluation dimension that the user is concerned about according to the dimension attention level” may specifically include:

[0096] Determining the complaint probability of the user in each evaluation dimension according to the dimension attention level;

[0097] When the complaint probability is greater than or equal to a preset probability threshold, the evaluation dimension corresponding to the complaint probability is determined as the target evaluation dimension.

[0098] Among them, the preset probability threshold can be determined according to the complaint probability in the corresponding evaluation dimension in the historical rating data, for example, the ratio of the number of complaints to the total number of evaluations, or, according to actual needs, set to a higher value to ensure that the final screened application can be accepted by users.

[0099] Among them, when the complaint probability reaches a certain standard (preset probability threshold), it is considered that the user is more concerned about this evaluation dimension.

[0100] Among them, in the embodiment of the present application, the complaint risk value of the user in each evaluation dimension can be determined according to the number of complaints, and the dimension attention level of each evaluation dimension can be determined according to the complaint risk value. That is, optionally, in some embodiments, the step of "determining the dimension attention level of the user for each evaluation dimension according to the historical scoring data" can specifically include:

[0101] Obtaining the number of complaints made by the user in each evaluation dimension from the historical rating data;

[0102] Determine the complaint risk value of each evaluation dimension according to the number of complaints;

[0103] The dimension attention level of the user in each evaluation dimension is determined according to the complaint risk value.

[0104] Among them, in the embodiment of the present application, for each evaluation dimension, the more complaints there are, the higher the complaint risk value of the evaluation dimension is, and the higher the complaint risk value is, the more attention the user pays to the evaluation dimension. For example, the more complaints the user makes about the operating smoothness of the application, the higher the user's requirements for the operating smoothness of the application are and the higher their attention is.

[0105] The complaint risk value may be determined according to the complaint quantity interval. For example, different complaint risk values ​​may be determined according to different complaint quantity intervals, and different dimensional attention levels may be determined. That is, optionally, in some embodiments, the step of "determining the dimensional attention level of the user in each evaluation dimension according to the complaint risk value" may specifically include:

[0106] For each evaluation dimension, determine the dimension attention level corresponding to each complaint risk value, and determine the complaint quantity range corresponding to each complaint risk value;

[0107] When the number of complaints of the evaluation dimension reaches any of the complaint number intervals, the dimension attention level corresponding to any of the complaint number intervals is determined as the dimension attention level of the user for the evaluation dimension.

[0108] For example, the complaint number interval is set to 0-5, 6-10, 11-15, 16-20, etc., and a complaint risk value is set for each interval, for example, 1 point, 2 points, 3 points, 4 points, 5 points, etc. The higher the score, the higher the complaint risk. For example, if the number of user complaints about the fluency of the application is 18, the complaint risk value is divided into 4 points; if the number of complaints about the functionality of the application is 10, the complaint risk value is divided into 2 points.

[0109] Among them, the complaint risk value is determined by the complaint quantity range, and the dimension attention level is determined according to the complaint risk, which can improve the accuracy of determining the dimension attention level.

[0110] Among them, the dimensional attention levels corresponding to different complaint risk values ​​can be determined according to the mapping relationship between the complaint risk value and the dimensional attention level.

[0111] 105. Send upgrade data of the target application to the terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data.

[0112] Among them, by sending the upgrade data of the selected target application to the user terminal, the user can upgrade the application according to the upgrade data, wherein the upgrade data includes silent upgrade data of the application. When the user terminal receives the silent upgrade data, it can perform a silent upgrade according to the silent upgrade data without the user confirming the upgrade, so that the user can perform the upgrade operation without being aware of it.

[0113] The embodiment of the present application determines the target application to be upgraded of the user's preference based on the reference rating data of the application to be upgraded after the upgrade and the historical rating data of the reference application by the user, so that the acquired target application is more acceptable to the user or more in line with the user's needs after the update, wherein the accuracy of the selection of the application to be upgraded is improved by acquiring and referring to the rating data of at least one evaluation dimension; wherein, by selecting the evaluation dimensions that the user is concerned about, the application that meets the user's specific needs can be selected in a targeted manner, while reducing the performance requirements for the evaluation dimensions that are not concerned about, thereby reducing the risk of the application being complained about.

[0114] In order to better implement the application upgrade method of the present application, the present application also provides an application upgrade device based on the above application upgrade method. The meanings of the terms are the same as those in the above application upgrade method, and the specific implementation details can refer to the description in the method embodiment.

[0115] See also Figure 3 , Figure 3 The schematic diagram of the structure of the application upgrade device provided in the embodiment of the present application, wherein the application upgrade device may include an acquisition module 201, a collection module 202, an extraction module 203, a determination module 204 and a push module 205, which may be specifically as follows:

[0116] The acquisition module 201 is used to acquire reference rating data of at least one application to be upgraded after upgrading, wherein the reference rating data includes rating data of the upgraded application by a reference user in at least one evaluation dimension.

[0117] Among them, by obtaining rating data of multiple evaluation dimensions, users' ratings of upgraded applications from multiple angles can be obtained, which is convenient for comprehensively understanding the performance data of the application and facilitating the recommendation of applications to be upgraded to users based on a certain evaluation dimension.

[0118] The collection module 202 is used to collect historical rating records of users for at least one reference application.

[0119] The reference applications include other applications in the user terminal device, or applications of the same type as the application to be upgraded, for example, all of them are game competition applications, or all of them are quiz applications, or all of them are film and television applications, etc.

[0120] The historical rating records of the reference application indicate the user's expectations of the application. For example, if the user gives more comments on the fluency of the application, or the fluency ratings are often low, it indicates that the user has higher requirements for the fluency of the application.

[0121] Among them, by obtaining rating data of applications of the same type, the user's expected satisfaction with the current application to be upgraded can be more accurately obtained, thereby improving the accuracy of subsequent target application selection.

[0122] The extraction module 203 is used to extract historical scoring data on the at least one evaluation dimension from the historical scoring records.

[0123] Among them, by obtaining historical rating data on each evaluation dimension, it is convenient to make recommendations for applications to be upgraded based on the rating data of each evaluation dimension.

[0124] Among them, for the scoring data of each evaluation dimension, the user's scoring data for each evaluation dimension can be obtained by taking an average value (for example, for each evaluation dimension, the average value of multiple scoring data in the historical scoring records is taken as the final scoring data of the evaluation dimension), and the scoring data of each evaluation dimension is taken as the user's basic requirement value for each evaluation dimension. That is, for each evaluation dimension, when the scoring data is greater than the basic requirement value, it is considered that the user can accept the current upgrade of the current application, thereby improving the accuracy of the recommendation of applications to be upgraded.

[0125] The determination module 204 is configured to determine the target application preferred by the user from the at least one application to be upgraded according to the historical rating data and the reference rating data.

[0126] Among them, the historical rating data shows the user's expectations for each evaluation dimension of the application, and the reference rating data shows the comprehensive objective performance data of the target application in each evaluation dimension. Based on the objective performance data of the application and the user's expectations, it is determined whether the application meets the user's expectations and whether the application is the user's preferred application, so as to select the target application.

[0127] Among them, based on historical rating data and reference rating data, the user's preferred applications can be determined, the accuracy of recommendation or selection of applications to be upgraded can be improved, the user experience can be improved, and user complaints can be reduced.

[0128] Optionally, in some embodiments of the present application, the determination module 204 includes:

[0129] A first determining unit, configured to determine the user's dimension attention level for each evaluation dimension according to the historical rating data;

[0130] A second determining unit is configured to determine a target application preferred by the user from among the at least one application to be upgraded according to the dimension attention level and the reference scoring data.

[0131] Optionally, in some embodiments of the present application, the second determining unit includes:

[0132] A first determining subunit, configured to determine at least one target evaluation dimension that the user is concerned about according to the dimension attention level;

[0133] A first acquisition subunit is used to respectively acquire dimension reference scoring data of each target evaluation dimension from the reference scoring data;

[0134] The second determining subunit is used to determine, for each of the target evaluation dimensions, when the dimension reference score data is greater than or equal to a preset score threshold, the upgraded application corresponding to the dimension reference score data as the target application preferred by the user.

[0135] Among them, by determining the dimension attention level, several evaluation dimensions that users focus on can be obtained. Therefore, when the scoring data of the application in the above-mentioned evaluation dimensions meets the requirements (preset scoring thresholds), it can be determined that these applications meet the user's needs or are within the acceptable range for users.

[0136] For example, please refer to Table 1. If the user has high requirements for the operation fluency of the application (i.e., the operation fluency is the target evaluation dimension), has no requirements for ease of use and interface aesthetics, and has general functional requirements, then application A and application C can be pushed to the user, and application B is not recommended for upgrade due to its low fluency. Alternatively, if the user has no requirements for operation fluency and ease of use, but has high requirements for interface aesthetics and functionality, then application B or application C can be recommended to the user.

[0137] Optionally, in some embodiments of the present application, the first determining unit includes:

[0138] A third determining subunit is used to determine the complaint probability of the user in each evaluation dimension according to the scoring data of the user in each evaluation dimension;

[0139] A fourth determining subunit, configured to determine the user's dimension attention level in each evaluation dimension according to the complaint probability;

[0140] Based on the third determining subunit and the fourth determining subunit, the first determining subunit is specifically configured to:

[0141] Used to determine the complaint probability of the user in each evaluation dimension according to the dimension attention level;

[0142] When the complaint probability is greater than or equal to a preset probability threshold, the evaluation dimension corresponding to the complaint probability is determined as the target evaluation dimension.

[0143] Optionally, in some embodiments of the present application, the first determining unit further includes:

[0144] A first acquisition subunit is used to acquire, from the historical rating data, the number of complaints made by the user in each evaluation dimension;

[0145] A fifth determination subunit, configured to determine a complaint risk value of each evaluation dimension according to the number of complaints;

[0146] The sixth determination subunit is used to determine the dimension attention level of the user in each evaluation dimension according to the complaint risk value.

[0147] Optionally, in some embodiments of the present application, the sixth determining subunit is specifically used to:

[0148] It is used to determine the dimension attention level corresponding to each complaint risk value for each evaluation dimension, and to determine the complaint quantity range corresponding to each complaint risk value;

[0149] When the number of complaints for an evaluation dimension reaches any of the complaint number intervals, the dimension attention level corresponding to any of the complaint number intervals is determined as the dimension attention level of the user for the evaluation dimension.

[0150] Optionally, in some embodiments of the present application, the determination module includes:

[0151] The third determining unit is used to determine, for each evaluation dimension, when the scoring data in the reference scoring data are all greater than the scoring data in the historical scoring data, the upgraded application corresponding to the reference scoring data as the target application preferred by the user.

[0152] Among them, when the score data of each evaluation dimension in the reference score data of the upgraded application is greater than the corresponding score data in the user's historical score data, it means that the score data of the current upgraded application meets the user's needs and can be recommended to the user.

[0153] Among them, by comparing the scoring data of each evaluation dimension, the recommended application can meet the needs of users in all aspects.

[0154] The push module 205 is used to send the upgrade data of the target application to the terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data.

[0155] In the embodiment of the present application, the acquisition module 201 first acquires reference score data of at least one evaluation dimension of at least one application to be upgraded after the upgrade, and then the acquisition module 202 acquires the historical score records of the user, and then the extraction module 203 extracts the score data of each evaluation dimension from the historical score records acquired by the acquisition module 202, and then the determination module 204 screens the applications suitable for the user according to the acquisition result of the acquisition module 201 and the extraction result of the extraction module 203, and selects at least one target application to be upgraded that the user can accept, and finally, the push module 205 sends the upgrade information of the target application determined by the determination module 204 to the terminal device of the user, and the terminal device sends the upgrade information according to the target application to the terminal device. The corresponding application is upgraded according to the upgrade data, wherein the application can be directly upgraded by silent upgrade, wherein the embodiment of the present application determines the target application to be upgraded of the user's preference according to the reference rating data of the application to be upgraded after the upgrade and the historical rating data of the reference application by the user, so that the acquired target application can be more acceptable to the user or more in line with the user's needs after the update, wherein the accuracy of the selection of the application to be upgraded is improved by acquiring and referring to the rating data of at least one evaluation dimension; wherein, by selecting the evaluation dimensions that the user is concerned about, the application that meets the user's specific needs can be selected in a targeted manner, while reducing the performance requirements for the evaluation dimensions that are not concerned about, thereby reducing the risk of the application being complained about.

[0156] In addition, the present application also provides an electronic device, such as Figure 4 As shown, it shows a schematic diagram of the structure of the electronic device involved in this application, specifically:

[0157] The electronic device may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will appreciate that Figure 4 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0158] The processor 401 is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 402, and calling data stored in the memory 402, the processor 401 performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 401.

[0159] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and decoding processes by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.

[0160] The electronic device also includes a power supply 403 for supplying power to each component. Preferably, the power supply 403 can be logically connected to the processor 401 through a power management system, so as to manage charging, discharging, power consumption and other functions through the power management system. The power supply 403 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0161] The electronic device may further include an input unit 404, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0162] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 401 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 402 according to the following instructions, and the processor 401 will run the application programs stored in the memory 402, thereby realizing various functions, as follows:

[0163] Obtain reference scoring data of at least one application to be upgraded after upgrading, the reference scoring data including scoring data of a reference user on the upgraded application on at least one evaluation dimension; collect historical scoring records of users for at least one reference application; extract historical scoring data on the at least one evaluation dimension from the historical scoring records; determine a target application preferred by the user from the at least one application to be upgraded based on the historical scoring data and the reference scoring data; and send upgrade data of the target application to a terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data.

[0164] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0165] Based on the reference rating data of the application to be upgraded after the upgrade and the historical rating data of the reference application by the user, the target application to be upgraded preferred by the user is determined, so that the acquired target application is more acceptable to the user or more in line with the user's needs after the update, wherein the accuracy of the selection of the application to be upgraded is improved by acquiring and referring to the rating data of at least one evaluation dimension; wherein, by selecting the evaluation dimensions that the user is concerned about, the application that meets the user's specific needs can be selected in a targeted manner, while reducing the performance requirements for the evaluation dimensions that are not concerned about, thereby reducing the risk of the application being complained about.

[0166] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0167] To this end, the present application provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any application upgrade method provided in the present application. For example, the instructions can execute the following steps:

[0168] Obtain reference scoring data of at least one application to be upgraded after upgrading, the reference scoring data including scoring data of a reference user on the upgraded application on at least one evaluation dimension; collect historical scoring records of users for at least one reference application; extract historical scoring data on the at least one evaluation dimension from the historical scoring records; determine a target application preferred by the user from the at least one application to be upgraded based on the historical scoring data and the reference scoring data; and send upgrade data of the target application to a terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data.

[0169] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0170] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0171] Since the instructions stored in the computer-readable storage medium can execute the steps in any application upgrade method provided in the present application, the beneficial effects that can be achieved by any application upgrade method provided in the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0172] The above is a detailed introduction to an application upgrade method, device, electronic device and computer-readable storage medium provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An application upgrade method, characterized in that: include: Obtaining reference rating data of at least one application to be upgraded after upgrading, the reference rating data including rating data of the upgraded application by a reference user in at least one evaluation dimension, the application to be upgraded including an application upgraded silently; Collecting historical rating records of users for at least one reference application; Extracting historical scoring data on the at least one evaluation dimension from the historical scoring records; Determining a target application preferred by the user from the at least one application to be upgraded according to the historical rating data and the reference rating data; Sending the upgrade data of the target application to the terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data; The determining, according to the historical scoring data and the reference scoring data, the target application preferred by the user from the at least one application to be upgraded comprises: Determining the user's dimension attention level for each evaluation dimension according to the historical rating data; Determining at least one target evaluation dimension that the user is concerned about according to the dimension attention level; Respectively obtaining dimension reference scoring data of each target evaluation dimension from the reference scoring data; For each of the target evaluation dimensions, when the dimension reference score data is greater than or equal to a preset score threshold, determining the upgraded application corresponding to the dimension reference score data as the target application preferred by the user; Determining the user's dimension attention level for each evaluation dimension according to the historical rating data includes: Determining the complaint probability of the user in each evaluation dimension according to the historical rating data of the user in each evaluation dimension; Determining the user's level of concern in each evaluation dimension according to the complaint probability; The determining, according to the dimension attention level, at least one target evaluation dimension that the user pays attention to comprises: Determining the complaint probability of the user in each evaluation dimension according to the dimension attention level; When the complaint probability is greater than or equal to a preset probability threshold, the evaluation dimension corresponding to the complaint probability is determined as the target evaluation dimension; The determining, according to the historical scoring data and the reference scoring data, the target application preferred by the user from the at least one application to be upgraded comprises: For each evaluation dimension, when the score data in the reference score data are all greater than the score data in the historical score data, the upgraded application corresponding to the reference score data is determined as the target application preferred by the user.

2. The method according to claim 1, characterized in that Determining the user's dimension attention level for each evaluation dimension according to the historical rating data includes: Obtaining the number of complaints made by the user in each evaluation dimension from the historical rating data; Determine the complaint risk value of each evaluation dimension according to the number of complaints; The dimension attention level of the user in each evaluation dimension is determined according to the complaint risk value.

3. The method according to claim 2, characterized in that Determining the user's dimension attention level in each evaluation dimension according to the complaint risk value includes: For each evaluation dimension, determine the dimension attention level corresponding to each complaint risk value, and determine the complaint quantity range corresponding to each complaint risk value; When the number of complaints of the evaluation dimension reaches any of the complaint number intervals, the dimension attention level corresponding to any of the complaint number intervals is determined as the dimension attention level of the user for the evaluation dimension.

4. An application upgrade device, characterized in that: include: An acquisition module, configured to acquire reference rating data of at least one application to be upgraded after upgrading, wherein the reference rating data includes rating data of a reference user on the upgraded application in at least one evaluation dimension, and the application to be upgraded includes an application upgraded silently; A collection module, used to collect historical rating records of users for at least one reference application; An extraction module, configured to extract historical scoring data on at least one evaluation dimension from the historical scoring records; A determination module, configured to determine the target application preferred by the user from the at least one application to be upgraded according to the historical rating data and the reference rating data; A push module, used for sending the upgrade data of the target application to the terminal device of the user, so that the terminal device upgrades the target application according to the upgrade data; The determining, according to the historical scoring data and the reference scoring data, the target application preferred by the user from the at least one application to be upgraded comprises: Determining the user's dimension attention level for each evaluation dimension according to the historical rating data; Determining at least one target evaluation dimension that the user is concerned about according to the dimension attention level; Respectively obtaining dimension reference scoring data of each target evaluation dimension from the reference scoring data; For each of the target evaluation dimensions, when the dimension reference score data is greater than or equal to a preset score threshold, determining the upgraded application corresponding to the dimension reference score data as the target application preferred by the user; Determining the user's dimension attention level for each evaluation dimension according to the historical rating data includes: Determining the complaint probability of the user in each evaluation dimension according to the historical rating data of the user in each evaluation dimension; Determining the user's level of concern in each evaluation dimension according to the complaint probability; The determining, according to the dimension attention level, at least one target evaluation dimension that the user pays attention to comprises: Determining the complaint probability of the user in each evaluation dimension according to the dimension attention level; When the complaint probability is greater than or equal to a preset probability threshold, the evaluation dimension corresponding to the complaint probability is determined as the target evaluation dimension; The determining, according to the historical scoring data and the reference scoring data, the target application preferred by the user from the at least one application to be upgraded comprises: For each evaluation dimension, when the score data in the reference score data are all greater than the score data in the historical score data, the upgraded application corresponding to the reference score data is determined as the target application preferred by the user.

5. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the application upgrade method as claimed in any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium, characterized in that: A computer program is stored thereon, wherein when the computer program is executed by a processor, the steps of the application upgrade method according to any one of claims 1 to 3 are implemented.

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