Desktop management method and device, equipment, storage medium and program product

Abstract

The invention discloses a desktop management method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring operation data of a user on the electronic equipment and current environment information, and determining a user behavior according to the operation data; inputting the user behavior into a first adjustment model to obtain a first adjustment scheme; the first adjustment model is obtained by training according to historical operation data of a user and desktop display parameters corresponding to the historical operation data; the desktop display parameters comprise icon positions, window layout and system parameters; inputting the current environment information into a second adjustment model to obtain a second adjustment scheme; the second adjustment model is obtained through training according to historical environment information and desktop display parameters corresponding to the historical environment information; and adjusting desktop display parameters of the electronic equipment according to the first adjustment scheme and the second adjustment scheme. By adopting the method, a user can be prevented from manually performing adjustment operation on the desktop of a large number of application programs or icons, and the desktop management efficiency is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a desktop management method, device, equipment, storage medium and program product. Background Art

[0002] With the development of computer technology, electronic devices have more and more functions, and the related functions displayed on the desktop of electronic devices are becoming more and more complicated. In order to ensure the normal use of electronic devices by users, it is necessary to manage the desktop of electronic devices.

[0003] Currently, users often need to manually adjust window layouts, organize desktop icons, switch desktop themes, modify system settings, etc., so that the managed desktop meets the user's current desktop usage needs. However, manual desktop management is time-consuming and has low management efficiency. Summary of the invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desired to provide a desktop management method, apparatus, device, storage medium and program product that can avoid users from manually adjusting the desktops of a large number of applications or icons, thereby effectively improving the efficiency of desktop management.

[0005] In a first aspect, the present application provides a desktop management method. The method comprises: Obtaining the user's operation data on the electronic device and current environment information, and determining the user's behavior based on the operation data; Inputting the user behavior into the first adjustment model to obtain a first adjustment scheme; the first adjustment model is trained according to the user's historical operation data and the desktop display parameters corresponding to the historical operation data; the desktop display parameters include icon positions, window layouts and system parameters; The current environment information is input into the second adjustment model to obtain a second adjustment scheme; the second adjustment model is trained according to the historical environment information and the desktop display parameters corresponding to the historical environment information; The desktop display parameters of the electronic device are adjusted according to the first adjustment scheme and the second adjustment scheme.

[0006] In combination with the first aspect, in a possible implementation method, the training process of the first adjustment model includes: determining historical user behavior based on historical operation data, and determining the user's historical operation habits based on the frequency of the same historical user behavior; adjusting the desktop display parameters corresponding to the historical operation data according to the first convenient operation rule based on the historical operation habits; the first convenient operation rule indicates the desktop display parameters of convenient operations corresponding to different operation habits; using the historical user behavior and the corresponding adjusted desktop display parameters as training samples to train the first initial adjustment model until the accuracy of the trained first adjustment model reaches the first preset accuracy, thereby obtaining the first adjustment model.

[0007] In combination with the first aspect, in a possible implementation method, the training process of the second adjustment model includes: determining the operation scenario of the electronic device based on historical environment information, and adjusting the desktop display parameters corresponding to the historical environment information according to the second convenient operation rule based on the operation scenario; the second convenient operation rule indicates the desktop display parameters of convenient operations corresponding to different operation scenarios; using the historical environment information and the corresponding adjusted desktop display parameters as training samples to train the second initial adjustment model until the accuracy of the trained second adjustment model reaches the second preset accuracy, thereby obtaining the second adjustment model.

[0008] In combination with the first aspect, in a possible implementation method, the adjustment scheme includes a parameter to be adjusted and a target value of the parameter to be adjusted, the parameter to be adjusted represents the desktop display parameter to be adjusted, and the desktop display parameter of the electronic device is adjusted according to the first adjustment scheme and the second adjustment scheme, including: determining the parameter to be adjusted in the second adjustment scheme that is the same as the first adjustment scheme to obtain candidate parameters; filtering out the candidate parameters in the second adjustment scheme and the target value of the candidate parameters; adjusting the desktop display parameters of the electronic device according to the first adjustment scheme and the second adjustment scheme after filtering.

[0009] In combination with the first aspect, in a possible implementation, the desktop management method also includes: when the usage time or number of times the electronic device is used reaches a preset update condition, obtaining user operation data within a preset time period before the current moment; updating the historical operation data according to the user operation data; training the first adjustment model according to the updated historical operation data and the desktop display parameters corresponding to the updated historical operation data, until the accuracy of the first adjustment model reaches a first preset accuracy, thereby obtaining an updated first adjustment model.

[0010] In combination with the first aspect, in a possible implementation method, the desktop management method also includes: adjusting the training samples according to healthy operation rules, and performing model training on the initial adjustment model based on the adjusted training samples; the initial adjustment model is the first initial adjustment model or the second initial adjustment model, and the healthy operation rules indicate the desktop display parameters corresponding to different user behaviors when using the electronic device in a healthy manner, or the desktop display parameters corresponding to different operation scenarios.

[0011] In a second aspect, the present application also provides a desktop management device. The device includes: An acquisition module, used to acquire the user's operation data on the electronic device and current environment information, and determine the user behavior based on the operation data; A first input module is used to input the user behavior into the first adjustment model to obtain a first adjustment scheme; the first adjustment model is trained according to the user's historical operation data and the desktop display parameters corresponding to the historical operation data; the desktop display parameters include icon positions, window layouts and system parameters; A second input module is used to input the current environment information into a second adjustment model to obtain a second adjustment scheme; the second adjustment model is trained based on the historical environment information and the desktop display parameters corresponding to the historical environment information; The adjustment module is used to adjust the desktop display parameters of the electronic device according to the first adjustment scheme and the second adjustment scheme.

[0012] In a third aspect, the present application further provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0013] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0014] In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0015] The embodiments of the present application provide a desktop management method, device, equipment, storage medium and program product, which can obtain the user's operation data and current environmental information on the electronic device, and after determining the user behavior based on the operation data, input the user behavior into the first adjustment model to obtain the first adjustment scheme; input the current environmental information into the second adjustment model to obtain the second adjustment scheme. Finally, the desktop display parameters of the electronic device are adjusted according to the first adjustment scheme and the second adjustment scheme. The embodiments of the present application construct a model for the relationship between user operation and desktop management mode, and construct a model for the relationship between environmental information and desktop management mode. Finally, a desktop management scheme is generated based on the two constructed models, and the desktop display parameters are directly adjusted according to the desktop management scheme to realize desktop automation management, avoiding the user's manual adjustment operation on the desktop of a large number of applications or icons, and effectively improving the efficiency of desktop management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 is a flowchart of a desktop management method in one embodiment; Figure 2 A schematic diagram of desktop display parameters in one embodiment; Figure 3 is another schematic diagram of desktop display parameters in one embodiment; Figure 4 is another flowchart of a desktop management method in one embodiment; Figure 5 is another flowchart of a desktop management method in one embodiment; Figure 6 is another flowchart of a desktop management method in one embodiment; Figure 7 is another flowchart of a desktop management method in one embodiment; Figure 8 is a structural block diagram of a desktop management device in one embodiment; Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0017] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0018] It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments. In addition, the term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The terms "first" and "second" in the description and claims of the embodiments of the present application are used to distinguish different objects, rather than to describe a specific order of objects.

[0019] In one embodiment, a desktop management method is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Figure 1 As shown, the method comprises the following steps: Step 101: Obtain user operation data on an electronic device and current environment information, and determine user behavior based on the operation data.

[0020] In the embodiment of the present application, after the electronic device is started, it starts to detect the user's operation on the electronic device and the environment in which the electronic device is currently located, that is, to obtain information on both operation data and current environment information. Specifically, the user's operation data can be directly obtained in real time from the operation record of the electronic device, and at the same time, the current environment information of the electronic device can be obtained by using the environment monitoring device.

[0021] The operation data includes the application started by the user, the arrangement and adjustment method of the window by the user (such as full screen, split screen, floating window), the operation time and other data. The current environment information includes the current light, time, location and other information. The environment monitoring device can be a device or function integrated in the electronic device. For example, a photoelectric sensor, a global positioning system, etc.

[0022] Then, the operation data can be analyzed to determine the current user behavior, for example, using application A in a small window manner, using application A and application B in a split screen manner, etc.

[0023] Step 102: Input the user behavior into the first adjustment model to obtain a first adjustment solution.

[0024] In an embodiment of the present application, after the user behavior and the current environment information are determined, the user behavior can be input into a pre-trained first adjustment model to obtain a first adjustment solution output by the model.

[0025] The first adjustment scheme is an adjustment scheme for desktop display parameters, for example, desktop display parameters to be adjusted, and target values ​​of desktop display parameters to be adjusted. Desktop display parameters may include at least one of icon position, window layout, and system parameters. Icon position refers to the position of an application or functional module on the screen of an electronic device; window layout refers to the window arrangement of the electronic device desktop, and the display content (application, blank, etc.) of at least one sub-window under the window arrangement, for example, Figure 2 As shown, when the window arrangement is split into two sub-windows, the display contents of the two sub-windows are the home page of application A and the reading page of application B respectively; Figure 3 As shown, when the window arrangement is displayed in the small screen in the lower left corner, the display content of the sub-window corresponding to the small screen is application C, and the remaining area is blank; the system parameters are parameters related to the desktop display of the electronic device (such as screen brightness, resolution, background, theme, etc.).

[0026] Among them, the first adjustment model is trained based on the user's historical operation data and the desktop display parameters corresponding to the historical operation data. Specifically, the user's historical operation data can be obtained, and the corresponding historical user behavior can be determined based on the historical operation data analysis. Then the historical user behavior is marked according to the desktop display parameters corresponding to the historical operation data. Next, the marked historical user behavior is used as a training set to train the initial first adjustment model until the model accuracy reaches the preset accuracy of the first adjustment model, and the model training is completed to obtain the first adjustment model. Finally, the trained first adjustment model can be integrated into the electronic device, so that after the electronic device is started and the current user behavior is determined, the first adjustment model is triggered to generate an adjustment plan for the desktop display parameters corresponding to the current user behavior, that is, the first adjustment plan.

[0027] In a possible implementation, in order to ensure that users use electronic devices in a healthy manner, training samples may be adjusted according to healthy operation rules, and the initial adjustment model may be trained based on the adjusted training samples.

[0028] The initial adjustment model is a first initial adjustment model, and the healthy operation rules indicate desktop display parameters corresponding to different user behaviors when the electronic device is used in a healthy manner.

[0029] That is, during the training process of the first adjustment model, after determining the desktop display parameters corresponding to the historical user behavior (called the first original parameters), the desktop display parameters corresponding to the historical user behavior indicated in the health operation rules can be determined for each historical user behavior. If the desktop display parameters indicated in the health operation rules are different from the first original parameters for the same historical user behavior, the historical user behavior marked with the first original parameters in the training sample is deleted, and the historical user behavior is re-marked according to the desktop display parameters indicated in the health operation rules to obtain the adjusted training samples. The first initial adjustment model is trained based on the adjusted training samples to obtain the first adjustment model.

[0030] Step 103: Input the current environment information into the second adjustment model to obtain a second adjustment solution.

[0031] In an embodiment of the present application, after the user behavior and the current environment information are determined, the current environment information can be input into a pre-trained second adjustment model to obtain a second adjustment solution output by the model.

[0032] The second adjustment scheme is also an adjustment scheme for desktop display parameters, including desktop display parameters to be adjusted and target values ​​of the desktop display parameters to be adjusted.

[0033] Among them, the second adjustment model is trained based on the historical environment information and the desktop display parameters corresponding to the historical environment information. Specifically, the user's historical environment information can be obtained, and then the historical environment information can be marked according to the desktop display parameters corresponding to the historical environment information. Next, the marked historical environment information is used as a training set to train the initial second adjustment model until the model accuracy reaches the preset second adjustment model accuracy, and the model training is completed to obtain the second adjustment model. Finally, the trained second adjustment model can be integrated into the electronic device, so that after the electronic device is started and the current environment information is determined, the second adjustment model is triggered to generate an adjustment plan for the desktop display parameters corresponding to the current environment information, that is, the second adjustment plan.

[0034] In a possible implementation, in order to ensure that users use electronic devices in a healthy manner, training samples may be adjusted according to healthy operation rules, and the initial adjustment model may be trained based on the adjusted training samples.

[0035] The initial adjustment model is a second initial adjustment model, and the healthy operation rules indicate desktop display parameters corresponding to different operation scenarios when the electronic device is used in a healthy manner.

[0036] That is, during the training process of the second adjustment model, after determining the desktop display parameters (called second original parameters) corresponding to the historical environment information, the desktop display parameters corresponding to the historical environment information indicated in the health operation rules can be determined for each historical environment information. If the desktop display parameters indicated in the health operation rules are different from the second original parameters for the same historical environment information, the historical environment information marked with the second original parameters in the training sample is deleted, and the historical environment information is re-marked according to the desktop display parameters indicated in the health operation rules to obtain an adjusted training sample. The second initial adjustment model is trained based on the adjusted training samples to obtain a second adjustment model.

[0037] Step 104: adjusting the desktop display parameters of the electronic device according to the first adjustment scheme and the second adjustment scheme.

[0038] In the embodiment of the present application, the desktop display parameters to be adjusted and the target values ​​of the desktop display parameters to be adjusted in the first adjustment scheme and the second adjustment scheme are determined, and the desktop display parameters with adjustment are adjusted to the target values.

[0039] For example, if the desktop display parameter to be adjusted is application A and the target value is the center of the desktop, then application A will be moved to the center of the desktop; if the desktop display parameter to be adjusted is application B and the target value is the small screen window in the lower left corner, then application B will be adjusted to the small screen display in the lower left corner; if the desktop display parameter to be adjusted is screen brightness and the target value is 35, then the screen brightness will be adjusted to 35.

[0040] In a possible implementation, when there are the same desktop display parameter to be adjusted but with different target values ​​in the first adjustment scheme and the second adjustment scheme, the adjustment scheme with a higher priority can be determined according to a preset priority list, and the desktop display parameter to be adjusted can be adjusted according to the target value of the desktop display parameter to be adjusted in the adjustment scheme with a higher priority.

[0041] The method provided by the embodiment of the present application can obtain the user's operation data and current environment information of the electronic device, and after determining the user behavior according to the operation data, the user behavior is input into the first adjustment model to obtain the first adjustment scheme; the current environment information is input into the second adjustment model to obtain the second adjustment scheme. Finally, the desktop display parameters of the electronic device are adjusted according to the first adjustment scheme and the second adjustment scheme. The embodiment of the present application constructs a model for the relationship between the user operation and the desktop management method, and constructs a model for the relationship between the environment information and the desktop management method. Finally, a desktop management scheme is generated based on the two constructed models, and the desktop display parameters are directly adjusted according to the desktop management scheme to realize desktop automation management, avoiding the user manually adjusting the desktop of a large number of applications or icons, and effectively improving the efficiency of desktop management. Moreover, the present application trains the adjustment model for user behavior and environment information respectively, so that the final adjustment scheme matches the user behavior, conforms to the user's operation habits of the electronic device, and matches the current environment, that is, the final desktop management scheme takes into account the user's operation habits and the impact of the current environment on the user on the basis of improving the efficiency of desktop management, and ensures the effectiveness and safety of desktop management.

[0042] The above-mentioned embodiment introduces a solution for outputting a desktop adjustment solution that conforms to user behavior according to a first adjustment model. In another embodiment of the present application, a training process of a first adjustment model is provided. The embodiment includes: Figure 4 The method shown: Step 201: determine historical user behaviors based on historical operation data, and determine the user's historical operation habits based on the frequency of the same historical user behaviors.

[0043] In an embodiment of the present application, historical operation data such as applications launched by users at the same historical time or the same historical period, the way users arrange windows (such as full screen, split screen, floating window), and corresponding historical operation time are integrated to determine historical user behavior.

[0044] For example, the determined historical user behaviors may include a user using application A in full screen at 6:00 p.m. on a weekday, a user using application B in small screen from 10:00 p.m. to 12:00 p.m. on a weekday, a user using application C within ten minutes after using application B, a user using application C and application D in split screen at 2:00 p.m. on a holiday, etc.

[0045] Then, the number of times the same historical user behavior occurs is determined, the frequency of the same historical user behavior is calculated, and the historical user behavior with a frequency greater than a preset frequency is determined as the user's historical operation habit.

[0046] Step 202: adjusting the desktop display parameters corresponding to the historical operation data according to the historical operation habits and the first convenient operation rule.

[0047] The first convenient operation rule indicates desktop display parameters of convenient operations corresponding to different operation habits.

[0048] In an embodiment of the present application, after determining the user's historical operating habits, the desktop display parameters of the convenient operation corresponding to the historical operating habits are searched in the first convenient operation rule, and the desktop display parameters corresponding to the historical operating habits are replaced based on the desktop display parameters corresponding to the convenient operation to obtain the desktop display parameters of the adjusted historical operating habits (historical user behaviors with higher frequency).

[0049] For example, if the frequency of the historical user behavior "the user uses application A in full screen at 6 pm on weekdays" is higher than the preset frequency, the historical user behavior is determined to be the user's historical operating habit, and the convenient operation corresponding to the historical user behavior in the first convenient operation rule is "starting the application in the center of the desktop", and the position parameter in the desktop display parameters corresponding to the convenient operation is "the center position of the desktop". Based on the position parameter, the original desktop display parameters of the historical user behavior "the user uses application A in full screen at 6 pm on weekdays" are replaced to obtain the desktop display parameters of the adjusted historical operating habit (the historical user behavior with a higher frequency).

[0050] For example, if the frequency of the historical user behavior "the user uses application C within ten minutes after using application B" is higher than the preset frequency, the historical user behavior is determined to be the user's historical operating habit, and the convenient operation corresponding to the historical user behavior in the first convenient operation rule is "displaying two applications in adjacent positions on the desktop", and the position parameter in the desktop display parameters corresponding to the convenient operation is "adjacent positions on the desktop". Based on the position parameter, the original desktop display parameters of the historical user behavior "the user uses application C within ten minutes after using application B" are replaced to obtain the desktop display parameters of the adjusted historical operating habit (the historical user behavior with higher frequency).

[0051] Step 203: Use the historical user behaviors and the corresponding adjusted desktop display parameters as training samples to train the first initial adjustment model until the accuracy of the trained first adjustment model reaches a first preset accuracy, thereby obtaining a first adjustment model.

[0052] In an embodiment of the present application, historical user behaviors are marked according to the adjusted desktop display parameters, and the marked historical user behaviors are used as training samples to train the first initial adjustment model until the accuracy of the trained first adjustment model reaches a first preset accuracy, thereby obtaining a first adjustment model.

[0053] The method provided in the embodiment of the present application can analyze the user's historical operating habits based on historical user behaviors, and adjust the desktop display parameters corresponding to the historical operating habits to desktop display parameters that are more convenient for user operation. Finally, the first adjustment model is trained based on the adjusted desktop display parameters, so that the desktop adjusted based on the first adjustment scheme output by the first adjustment model is both in line with user habits and convenient for user operation.

[0054] The above-mentioned embodiment introduces a solution for outputting a desktop adjustment solution that conforms to the environmental information according to the second adjustment model. In another embodiment of the present application, a training process of the second adjustment model is provided. The embodiment includes the following steps: Figure 5 The method shown: Step 301: determine an operation scenario of the electronic device according to historical environment information, and adjust desktop display parameters corresponding to the historical environment information according to a second convenient operation rule according to the operation scenario.

[0055] The second convenient operation rule indicates desktop display parameters of convenient operations corresponding to different operation scenarios.

[0056] In an embodiment of the present application, the operation scenario of the electronic device is determined based on at least one of the time, location, light and other information in the historical environment information, such as a daytime work scenario, an evening work scenario, an evening family leisure scenario, etc.

[0057] Then, the desktop display parameters of the convenient operation corresponding to the operation scenario are searched in the second convenient operation rule, and the desktop display parameters of the historical environment information corresponding to the operation scenario are replaced based on the desktop display parameters corresponding to the convenient operation to obtain the desktop display parameters of the adjusted historical environment information.

[0058] For example, the convenient operation corresponding to the "daytime work scene" in the first convenient operation rule is "starting a work-related application in a folder on the desktop", and the position parameter in the desktop display parameters corresponding to the convenient operation is "a folder on the desktop". Based on the position parameter, the original desktop display parameters of the "daytime work scene" are replaced (that is, the work-related applications are moved to a folder on the desktop) to obtain the adjusted desktop display parameters of the historical environment information.

[0059] For example, the convenient operation corresponding to the "evening family leisure scene" in the first convenient operation rule is "operate in dark mode", the brightness in the desktop display parameters corresponding to the convenient operation is 0-50, and the theme is a dark theme. Based on the above brightness and theme, the original desktop display parameters (brightness and theme) of the "evening family leisure scene" are replaced to obtain the adjusted desktop display parameters of the historical environment information.

[0060] Step 302: Use the historical environment information and the corresponding adjusted desktop display parameters as training samples to train the second initial adjustment model until the accuracy of the trained second adjustment model reaches a second preset accuracy, thereby obtaining a second adjustment model.

[0061] In an embodiment of the present application, historical environment information is marked according to the adjusted desktop display parameters, and the marked historical environment information is used as a training sample to train the second initial adjustment model until the accuracy of the trained second adjustment model reaches the second preset accuracy, thereby obtaining a second adjustment model.

[0062] The method provided in the embodiment of the present application can analyze the operation scenario of the electronic device according to the historical environment information, and adjust the desktop display parameters corresponding to the historical environment information to desktop display parameters that are more in line with the environment. Finally, the second adjustment model is trained based on the adjusted desktop display parameters, so that the desktop adjusted based on the first adjustment scheme output by the second adjustment model not only conforms to the user's habits, but also avoids the impact of the mismatch between the environment and the desktop parameters on the user's operation.

[0063] The above-mentioned embodiment introduces a scheme for adjusting desktop display parameters according to two adjustment schemes. In another embodiment of the present application, the adjustment scheme includes a parameter to be adjusted and a target value of the parameter to be adjusted. To avoid conflicts between the two adjustment schemes, the parameters to be adjusted in the two adjustment schemes may be deduplicated before adjusting the desktop display parameters. This embodiment includes the following: Figure 6 The steps shown; Step 401: Determine the parameters to be adjusted in the second adjustment scheme that are the same as those in the first adjustment scheme, and obtain candidate parameters.

[0064] Step 402: Filter out candidate parameters and target values ​​of the candidate parameters in the second adjustment scheme.

[0065] Step 403: adjusting the desktop display parameters of the electronic device according to the first adjustment scheme and the second adjustment scheme after filtering.

[0066] The parameter to be adjusted represents the desktop display parameter to be adjusted.

[0067] In an embodiment of the present application, for the first adjustment scheme based on user behavior and the second adjustment scheme based on environmental information, the priority of the first adjustment scheme is set higher than that of the second adjustment scheme. Therefore, the parameters to be adjusted in the first adjustment scheme and the parameters to be adjusted in the second adjustment scheme are matched, and after the same parameters to be adjusted (i.e., candidate parameters) are determined, the relevant information of the candidate parameters in the second adjustment scheme (candidate parameters and target values ​​of the candidate parameters) is filtered out, and the candidate parameters in the first adjustment scheme and the corresponding target values ​​are retained. Finally, the desktop display parameters are determined based on the first adjustment scheme and the parameters to be adjusted in the second adjustment scheme after filtering, and the desktop display parameters are adjusted to the corresponding target values.

[0068] The method provided in the embodiment of the present application deduplicates the same parameters to be adjusted in the two adjustment schemes before adjusting the desktop display parameters according to the first adjustment scheme and the second adjustment scheme, thereby avoiding desktop management based on the same parameters to be adjusted with different target values, which may lead to desktop management errors, and improving the effectiveness and accuracy of desktop management.

[0069] In one embodiment, new data can be continuously acquired during the user's use of the electronic device to update the model and ensure the accuracy of the model. Figure 7 Steps shown: Step 501: When the usage time or usage frequency of the electronic device reaches a preset update condition, user operation data within a preset period before the current moment is obtained.

[0070] Step 502: Update historical operation data according to user operation data.

[0071] Step 503: Train the first adjustment model according to the updated historical operation data and the desktop display parameters corresponding to the updated historical operation data until the accuracy of the first adjustment model reaches a first preset accuracy, thereby obtaining an updated first adjustment model.

[0072] In the embodiment of the present application, an update condition may be preset, and the preset update condition may include a preset usage time or a preset number of times of use. When the usage time of the electronic device reaches the preset usage time, or the number of times of use of the electronic device reaches the preset number of times of use, the user operation data within the preset period before the current moment is obtained.

[0073] The preset time period may be the same as or different from the preset usage time.

[0074] Then, the historical operation data is updated according to the user operation data. Specifically, the user operation data can be added to the historical operation data; or the historical operation data can be sorted in chronological order from the beginning to the end, the historical operation data in the preset time period in the first order can be deleted, and then the user operation data in the preset time period before the current moment can be added to the historical operation data.

[0075] Finally, the updated historical operation data is marked according to the desktop display parameters corresponding to the updated historical operation data, and the marked historical operation data is used as a training set to train the first adjustment model until the accuracy of the first adjustment model reaches the first preset accuracy again, thereby obtaining an updated first adjustment model.

[0076] In a possible implementation, when the usage time of the electronic device reaches a preset usage time, or the number of times the electronic device is used reaches a preset number of times, the environment information within a preset period before the current moment can be obtained. The historical environment information is updated according to the obtained environment information. The updated historical environment information is marked according to the desktop display parameters corresponding to the updated historical environment information, and the marked historical environment information is used as a training set to train the second adjustment model until the accuracy of the second adjustment model reaches the second preset accuracy again, thereby obtaining an updated second adjustment model.

[0077] The method provided in the embodiment of the present application can continuously obtain user operation data to update the first adjustment model, so that the model can follow the changes in user behavior habits, thereby effectively improving the accuracy of the model, and then improving the accuracy of the adjustment plan based on the model output.

[0078] It should be noted that although the operations of the method of the present invention are described in a particular order in the accompanying drawings, this does not require or imply that the operations must be performed in this particular order, or that all the operations shown must be performed to achieve the desired results. On the contrary, the steps depicted in the flow chart can be performed in a different order. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be decomposed into multiple steps.

[0079] In one embodiment, Figure 8 As shown, a desktop management device is provided, including: an acquisition module 601, a first input module 602, a second input module 603 and an adjustment module 604, wherein: The acquisition module 601 is used to acquire the user's operation data on the electronic device and the current environment information, and determine the user behavior according to the operation data.

[0080] The first input module 602 is used to input user behavior into the first adjustment model to obtain a first adjustment scheme; the first adjustment model is trained based on the user's historical operation data and the desktop display parameters corresponding to the historical operation data; the desktop display parameters include icon position, window layout and system parameters.

[0081] The second input module 603 is used to input the current environment information into the second adjustment model to obtain a second adjustment scheme; the second adjustment model is trained based on the historical environment information and the desktop display parameters corresponding to the historical environment information.

[0082] The adjustment module 604 is used to adjust the desktop display parameters of the electronic device according to the first adjustment scheme and the second adjustment scheme.

[0083] In one embodiment, the training process of the first adjustment model includes: determining historical user behavior based on historical operation data, and determining the user's historical operation habits based on the frequency of the same historical user behavior; adjusting the desktop display parameters corresponding to the historical operation data according to the first convenient operation rule based on the historical operation habits; the first convenient operation rule indicates the desktop display parameters of convenient operations corresponding to different operation habits; using the historical user behavior and the corresponding adjusted desktop display parameters as training samples to train the first initial adjustment model until the accuracy of the trained first adjustment model reaches the first preset accuracy, thereby obtaining the first adjustment model.

[0084] In one embodiment, the training process of the second adjustment model includes: determining the operation scenario of the electronic device based on historical environment information, and adjusting the desktop display parameters corresponding to the historical environment information according to the second convenient operation rule based on the operation scenario; the second convenient operation rule indicates the desktop display parameters of the convenient operation corresponding to different operation scenarios; using the historical environment information and the corresponding adjusted desktop display parameters as training samples to train the second initial adjustment model until the accuracy of the trained second adjustment model reaches the second preset accuracy, thereby obtaining the second adjustment model.

[0085] In one embodiment, the adjustment scheme includes a parameter to be adjusted and a target value of the parameter to be adjusted, the parameter to be adjusted represents a desktop display parameter to be adjusted, and the adjustment module 604 is specifically used to determine the parameter to be adjusted in the second adjustment scheme that is the same as the first adjustment scheme, and obtain candidate parameters; filter out the candidate parameters in the second adjustment scheme and the target value of the candidate parameters; and adjust the desktop display parameters of the electronic device according to the first adjustment scheme and the second adjustment scheme after filtering.

[0086] In one embodiment, the desktop management device also includes an update module, which is used to obtain user operation data within a preset time period before the current moment when the usage time or number of times the electronic device is used reaches a preset update condition; update the historical operation data according to the user operation data; and train the first adjustment model according to the updated historical operation data and the desktop display parameters corresponding to the updated historical operation data until the accuracy of the first adjustment model reaches a first preset accuracy, thereby obtaining an updated first adjustment model.

[0087] In one embodiment, the desktop management device also includes a training module, which is used to adjust the training samples according to the healthy operation rules, and perform model training on the initial adjustment model based on the adjusted training samples; the initial adjustment model is the first initial adjustment model or the second initial adjustment model, and the healthy operation rules indicate the desktop display parameters corresponding to different user behaviors when using the electronic device in a healthy way, or the desktop display parameters corresponding to different operation scenarios.

[0088] It should be understood that the units or modules described in the desktop management device are similar to those described in the reference Figure 1 The various steps in the described method correspond to each other. Thus, the operations and features described above for the method are also applicable to the desktop management device and the units contained therein, and will not be repeated here. The desktop management device can be pre-implemented in the browser or other security applications of the electronic device, and can also be loaded into the browser or its security application of the electronic device by downloading or the like. The corresponding units in the desktop management device can cooperate with the units in the electronic device to implement the scheme of the embodiment of the present application.

[0089] Reference below Fig. 9 , which shows a schematic diagram of the structure of a computer system 700 of a terminal device or server suitable for implementing an embodiment of the present application.

[0090] like Fig. 9 As shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage part 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0091] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage section 708 as needed.

[0092] In particular, according to the embodiments of the present disclosure, the above reference Figure 1 The described processes may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising a computer program for executing Figure 1 In such an embodiment, the computer program may be downloaded and installed from a network via the communication section 709 and / or installed from the removable medium 711.

[0093] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium such as a computer-readable storage medium that can send, propagate or transmit a program for use by or in conjunction with an instruction execution system, device or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0094] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a different order from the order marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0095] The units or modules involved in the embodiments described in the present application may be implemented by software or hardware. The units or modules described may also be arranged in a processor. The names of these units or modules do not, in some cases, constitute limitations on the units or modules themselves.

[0096] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the computer device described in the above embodiment, or may exist independently without being installed in the computer device. The above computer-readable storage medium stores one or more programs, and when the above programs are used by one or more processors to execute the method described in the present application. For example, it can be executed Figure 1 The individual steps of the method are shown.

[0097] The present application embodiment provides a computer program product, which includes instructions. When the instructions are executed, the method described in the present application embodiment is executed. For example, Figure 1 The individual steps of the method are shown.

[0098] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0099] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the present application.

Claims

1. A desktop management method, characterized in that: The method comprises: Acquire user operation data on the electronic device and current environment information, and determine user behavior based on the operation data; The user behavior is input into a first adjustment model to obtain a first adjustment scheme; the first adjustment model is trained according to the historical operation data of the user and the desktop display parameters corresponding to the historical operation data; the desktop display parameters include icon positions, window layouts and system parameters; The current environment information is input into a second adjustment model to obtain a second adjustment scheme; the second adjustment model is trained based on the historical environment information and the desktop display parameters corresponding to the historical environment information; The desktop display parameters of the electronic device are adjusted according to the first adjustment scheme and the second adjustment scheme.

2. The method according to claim 1, characterized in that The training process of the first adjustment model includes: Determine the historical user behavior based on the historical operation data, and determine the user's historical operation habits based on the frequency of the same historical user behavior; According to the historical operation habits, the desktop display parameters corresponding to the historical operation data are adjusted according to the first convenient operation rule; the first convenient operation rule indicates the desktop display parameters of convenient operations corresponding to different operation habits; The historical user behavior and the corresponding adjusted desktop display parameters are used as training samples to train the first initial adjustment model until the accuracy of the trained first adjustment model reaches a first preset accuracy, thereby obtaining the first adjustment model.

3. The method according to claim 1, characterized in that The training process of the second adjustment model includes: Determining an operation scenario of the electronic device according to the historical environment information, and adjusting a desktop display parameter corresponding to the historical environment information according to a second convenient operation rule according to the operation scenario; the second convenient operation rule indicates desktop display parameters of convenient operations corresponding to different operation scenarios; The historical environment information and the corresponding adjusted desktop display parameters are used as training samples to train the second initial adjustment model until the accuracy of the trained second adjustment model reaches a second preset accuracy, thereby obtaining the second adjustment model.

4. The method according to claim 1, characterized in that The adjustment scheme includes a parameter to be adjusted and a target value of the parameter to be adjusted, the parameter to be adjusted represents a desktop display parameter to be adjusted, and adjusting the desktop display parameter of the electronic device according to the first adjustment scheme and the second adjustment scheme includes: Determine, in the second adjustment scheme, the parameters to be adjusted that are the same as those in the first adjustment scheme, and obtain candidate parameters; Filtering out candidate parameters and target values ​​of the candidate parameters in the second adjustment scheme; The desktop display parameters of the electronic device are adjusted according to the first adjustment scheme and the second adjustment scheme after filtering.

5. The method according to claim 1, characterized in that The method further comprises: When the usage time or usage frequency of the electronic device reaches a preset update condition, obtaining user operation data within a preset period before the current moment; Updating the historical operation data according to the user operation data; The first adjustment model is trained according to the updated historical operation data and the desktop display parameters corresponding to the updated historical operation data until the accuracy of the first adjustment model reaches a first preset accuracy, thereby obtaining an updated first adjustment model.

6. The method according to claim 2 or 3, characterized in that: The method further comprises: The training samples are adjusted according to the healthy operation rules, and the initial adjustment model is trained based on the adjusted training samples; the initial adjustment model is the first initial adjustment model or the second initial adjustment model, and the healthy operation rules indicate the desktop display parameters corresponding to different user behaviors when the electronic device is used in a healthy manner, or the desktop display parameters corresponding to different operation scenarios.

7. A desktop management device, characterized in that: The device comprises: An acquisition module, used to acquire the user's operation data on the electronic device and current environment information, and determine the user behavior according to the operation data; A first input module, used to input the user behavior into a first adjustment model to obtain a first adjustment scheme; the first adjustment model is trained according to the historical operation data of the user and the desktop display parameters corresponding to the historical operation data; the desktop display parameters include icon positions, window layouts and system parameters; A second input module is used to input the current environment information into a second adjustment model to obtain a second adjustment scheme; the second adjustment model is trained based on the historical environment information and the desktop display parameters corresponding to the historical environment information; The adjustment module is used to adjust the desktop display parameters of the electronic device according to the first adjustment scheme and the second adjustment scheme.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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