Shortcut switch recommendation method and electronic equipment

Abstract

The invention provides a shortcut switch recommendation method and electronic equipment, and is applied to the technical field of terminals, and the recommended shortcut switch obtained by using the shortcut switch recommendation method is higher in accuracy. The user can quickly select the required shortcut switch based on the recommended shortcut switch, so that the complexity of user operation is reduced. The method comprises the following steps: in response to a pull-down operation input by a user, acquiring scene information of the electronic equipment; the pull-down operation is used for triggering a display control center interface; inputting scene information of the electronic equipment into the trained recommendation model, and outputting a predicted shortcut switch by the trained recommendation model; determining a recommended shortcut switch based on the predicted shortcut switch, and displaying the recommended shortcut switch in a recommendation area of the control center interface; and displaying an interface before pull-down in response to a packing-up operation input by the user.

Description

Technical Field

[0001] The present disclosure relates to the field of terminal technology, and in particular to a method for recommending a quick switch and an electronic device. Background Art

[0002] When using an electronic device, the user can trigger a pull-down operation on the right side of the top status bar to display the control center interface of the electronic device. The control center interface includes multiple shortcut switches. For example, a wireless network shortcut switch, a Bluetooth shortcut switch, a mute shortcut switch, etc. These shortcut switches can facilitate users to quickly start the corresponding control function.

[0003] Since there are many quick switches displayed on the control center interface, in order to help users quickly determine the quick switches they need, the operating system sets a recommendation area in the control center interface, which can display recommended quick switches. In related technologies, recommended quick switches are determined based on the frequency of users using quick switches. This recommendation method relies on too single data and has low accuracy. Summary of the invention

[0004] The embodiments of the present disclosure provide a method for recommending a quick switch and an electronic device, wherein the quick switch recommendation method obtains a more accurate recommended quick switch, and the user can quickly select the desired quick switch based on the recommended quick switch, thereby reducing the complexity of the user's operation.

[0005] To achieve the above objectives, the embodiments of the present disclosure adopt the following technical solutions:

[0006] In a first aspect, the present disclosure provides a method for recommending a quick switch, the method comprising: first, in response to a pull-down operation input by a user, acquiring scene information of an electronic device; the pull-down operation is used to trigger the display of a control center interface. Then, the scene information of the electronic device is input into a trained recommendation model, and the trained recommendation model outputs a predicted quick switch. Next, based on the predicted quick switch, a recommended quick switch is determined, and the recommended quick switch is displayed in a recommendation area of ​​the control center interface. Finally, in response to a folding operation input by the user, the interface before the pull-down is displayed.

[0007] Based on the data processing method of the first aspect, after detecting the user's pull-down operation, the present disclosure can respond to the user's pull-down operation and obtain the scene information of the electronic device. Then the scene information of the electronic device is used as the input of the trained recommendation model, so that the trained recommendation model outputs the predicted shortcut switch. Afterwards, the predicted shortcut switch is used to obtain the recommended shortcut switch, and the recommended shortcut switch is displayed, and the display timing of the recommended shortcut switch is before the user inputs the retract operation, that is, the user can view the recommended shortcut switch in real time, ensuring the real-time nature of the recommendation. Compared with the related art, in which the recommended shortcut switch is generated by the statistical frequency of the shortcut switch, the present disclosure uses the trained recommendation model to determine the predicted shortcut switch, and the trained recommendation model also refers to the scene information of the electronic device when generating the predicted shortcut switch. Since the scene information of the electronic device can affect the user's choice of the shortcut switch to a certain extent, the use of this method can ensure that the accuracy of the output predicted shortcut switch is higher, and accordingly, the accuracy of the recommended shortcut switch obtained based on the predicted shortcut switch is also higher.

[0008] In combination with the first aspect, in another possible implementation, the scene information of the electronic device is input into the trained recommendation model, and the trained recommendation model outputs the predicted shortcut switch, including: when the recommendation model has been trained, the scene information of the electronic device is input into the trained recommendation model, and the trained recommendation model outputs the predicted shortcut switch. Based on this solution, it can be ensured that the model applied when outputting the predicted shortcut switch using the trained recommendation model is the trained recommendation model. Using the trained recommendation model, the accuracy of the output predicted shortcut switch can be guaranteed.

[0009] In combination with the first aspect, in another possible implementation, before responding to the folding operation input by the user, the method further includes: detecting a touch operation input by the user, the touch operation being used to change the state of the shortcut switch in the control center interface; generating behavior data information in response to the touch operation; the behavior data information including the name of the shortcut switch; generating a statistical shortcut switch based on the behavior data information; the statistical shortcut switch is a shortcut switch whose usage frequency exceeds a threshold within a preset period. Based on this solution, a method for determining the statistical shortcut switch based on the usage frequency is proposed.

[0010] In combination with the first aspect, in another possible implementation manner, determining a recommended quick switch based on the predicted quick switch includes: when the number of predicted quick switches is greater than or equal to a first threshold, determining the recommended quick switch based on the predicted quick switch; when the number of predicted quick switches is equal to a second threshold, determining the recommended quick switch based on the statistical quick switch; when the number of predicted quick switches is not equal to the second threshold and is less than the first threshold, determining the recommended quick switch based on the statistical quick switch and the predicted quick switch.

[0011] Based on this solution, after using the trained recommendation model to obtain the predicted quick switches, it is necessary to determine whether the number of predicted quick switches meets the requirements. If the number of predicted quick switches meets the requirements, the predicted quick switches are used to obtain the recommended quick switches. If the number of predicted quick switches does not meet the requirements, it is determined based on the number of predicted quick switches whether to use the statistical quick switches to obtain the recommended quick switches, or to use the predicted quick switches and the statistical quick switches to obtain the recommended quick switches. In this way, in any case, it can be ensured that the number of recommended quick switches meets the requirements.

[0012] In combination with the first aspect, in another possible implementation, before inputting the scene information of the electronic device into the trained recommendation model, the method also includes: obtaining first scene information, the first scene information being the scene in which the electronic device is currently located; encapsulating the first scene information and the behavior data information to obtain encapsulated data; based on the encapsulated data, obtaining training data, and the training data is used to train the recommendation model. Since the first scene information and the behavior data information are both single fields, based on this solution, by encapsulating the first scene information and the behavior data information, the single field can be integrated into a new data structure. In this way, the storage and reading of data are facilitated, the simplicity of the data is increased, the data is made easier to read and maintain, and the data processing efficiency can be improved later.

[0013] In combination with the first aspect, in another possible implementation method, training data is obtained based on the encapsulated data, including: obtaining second scene information, the second scene information is the scene information sent by the always-displayed application; parsing the encapsulated data to obtain parsed data, the parsed data includes the first scene information and behavior data information; encapsulating the first scene information, the behavior data information and the second scene information to obtain training data.

[0014] Based on this solution, when generating training data, the electronic device also obtains the second scene information sent by other applications (for example, always display applications). This is equivalent to adding more external information on the basis of the original first scene information and behavior data information. In this way, the integrity and richness of the training data can be guaranteed. Training the recommendation model based on the training data can make the accuracy of the trained recommendation model higher.

[0015] In combination with the first aspect, in another possible implementation, after obtaining the training data, the method further includes: training a recommendation model using the training data to obtain a trained recommendation model. Based on this solution, an example of obtaining a trained recommendation model is provided.

[0016] In combination with the first aspect, in another possible implementation, after responding to a pull-down operation input by the user, the method further includes: outputting a predicted quick switch based on multiple preset quick switches when the recommendation model has not been trained. Based on this scheme, after detecting a pull-down operation, the present disclosure preferentially uses the trained recommendation model to recommend quick switches to the user. Since the training data of the recommendation model is related to the user's touch operation, the trained recommendation model cannot be used to make recommendations to the user before a large amount of training data is collected. Therefore, the present disclosure also proposes that when the recommendation model has not been trained, a predicted quick switch can be output based on multiple preset quick switches. This ensures that the user can view the recommended quick switches in the recommendation area of ​​the control center interface at any time.

[0017] In a second aspect, an embodiment of the present disclosure provides a recommendation device for a quick switch, which can be applied to an electronic device to implement the method in the first aspect. The function of the recommendation device for the quick switch can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, such as an acquisition module, a processing module, a determination module, and a display module.

[0018] Among them, the acquisition module is configured to acquire scene information of the electronic device in response to a pull-down operation input by the user; the pull-down operation is used to trigger the display of the control center interface.

[0019] The processing module is configured to input the scene information of the electronic device into a trained recommendation model, and the trained recommendation model outputs a predicted shortcut switch.

[0020] The determination module is configured to determine a recommended shortcut switch based on the predicted shortcut switch, and display the recommended shortcut switch in a recommendation area of ​​the control center interface.

[0021] The display module is configured to display the interface before being pulled down in response to a retracting operation input by the user.

[0022] In combination with the second aspect, in a possible implementation, the processing module is further configured to input the scene information of the electronic device into the trained recommendation model when the recommendation model has been trained, and the trained recommendation model outputs a predicted shortcut switch.

[0023] In combination with the second aspect, in a possible implementation, the processing module is also configured to detect a touch operation input by a user, where the touch operation is used to change the state of a shortcut switch in the control center interface; in response to the touch operation, generate behavior data information; the behavior data information includes the name of the shortcut switch; based on the behavior data information, generate a statistical shortcut switch; the statistical shortcut switch is a shortcut switch whose usage frequency exceeds a threshold within a preset period.

[0024] In combination with the second aspect, in a possible implementation, the determination module is further configured to determine a recommended quick switch based on the predicted quick switch when the number of predicted quick switches is greater than or equal to a first threshold; determine the recommended quick switch based on the statistical quick switch when the number of predicted quick switches is equal to the second threshold; and determine the recommended quick switch based on the statistical quick switch and the predicted quick switch when the number of predicted quick switches is not equal to the second threshold and is less than the first threshold.

[0025] In conjunction with the second aspect, in a possible implementation, the acquisition module is further configured to acquire first scene information, where the first scene information is the scene that the electronic device is currently in. The processing module is further configured to encapsulate the first scene information and the behavior data information to obtain encapsulated data; based on the encapsulated data, obtain training data, where the training data is used to train the recommendation model.

[0026] In conjunction with the second aspect, in a possible implementation, the acquisition module is further configured to acquire second scene information, where the second scene information is scene information sent by the always-displayed application. The processing module is further configured to parse the encapsulated data to obtain parsed data, where the parsed data includes the first scene information and the behavior data information; and encapsulate the first scene information, the behavior data information, and the second scene information to obtain training data.

[0027] In combination with the second aspect, in a possible implementation manner, the processing module is further configured to train the recommendation model using the training data to obtain the trained recommendation model.

[0028] In combination with the second aspect, in a possible implementation, the processing module is further configured to output a predicted shortcut switch based on a plurality of preset shortcut switches when the recommendation model has not been trained.

[0029] In a third aspect, the present disclosure provides an electronic device, comprising: a memory, a display screen, and one or more processors; the memory, the display screen, and the processor are coupled. The memory is used to store computer program codes, and the computer program codes include computer instructions; when the electronic device is running, the processor is used to execute one or more computer instructions stored in the memory, so that the electronic device executes the data processing method as described in any one of the first aspects above.

[0030] In a fourth aspect, the present disclosure provides a computer storage medium, comprising computer instructions, which, when executed on an electronic device, enables the electronic device to execute any of the data processing methods in the first aspect.

[0031] In a fifth aspect, the present disclosure provides a computer program product. When the computer program product is executed on an electronic device, the electronic device executes the data processing method as described in any one of the first aspects.

[0032] In a sixth aspect, a device (for example, the device may be a chip system) is provided, the device including a processor for supporting a first terminal device to implement the functions involved in the first aspect. In one possible design, the device also includes a memory for storing necessary program instructions and data for the first terminal device. When the device is a chip system, it may be composed of a chip, or may include a chip and other discrete devices.

[0033] It should be understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is one of the display schematic diagrams provided in the embodiment of the present disclosure.

[0035] Figure 2 A flowchart of a recommended method for a quick switch provided in the related art.

[0036] Figure 3 The present invention provides a second display schematic diagram of an embodiment of the present invention.

[0037] Figure 4 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present disclosure.

[0038] Figure 5 A schematic diagram of the software structure of an electronic device provided in an embodiment of the present disclosure.

[0039] Figure 6 A flowchart of a recommended method for quick switching provided in an embodiment of the present disclosure.

[0040] Figure 7 A schematic diagram of a flow chart of determining a recommended quick switch in a quick switch recommendation method provided in an embodiment of the present disclosure.

[0041] Figure 8 A schematic diagram of the structure of a chip system provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0042] The technical solution in the embodiment of the present disclosure will be described below in conjunction with the drawings in the embodiment of the present disclosure. Among them, in the description of the present disclosure, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the present disclosure is only a kind of association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. And, in the description of the present disclosure, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present disclosure, in the embodiments of the present disclosure, the words "first", "second" and the like are used to distinguish between the same items or similar items with substantially the same functions and effects. Those skilled in the art will understand that the words "first", "second" and the like do not limit the quantity and execution order, and the words "first", "second" and the like do not necessarily limit the differences. At the same time, in the embodiments of the present disclosure, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present disclosure should not be interpreted as being more preferred or more advantageous than other embodiments or design. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for easy understanding.

[0043] In addition, the network architecture and business scenarios described in the embodiments of the present disclosure are intended to more clearly illustrate the technical solutions of the embodiments of the present disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. Ordinary technicians in this field can know that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems.

[0044] In order to make the description of the following embodiments clear and concise, a brief introduction to the relevant concepts or technologies is first given:

[0045] With the development of mobile communication technology, electronic devices such as smart phones and tablet computers have been increasingly widely used. In the process of using electronic devices, in order to facilitate users to quickly enter the required application or implement the corresponding function, the relevant technology can set a specific page (for example, a control center interface) on the electronic device to display a quick switch icon to facilitate user operation.

[0046] Taking the electronic device as a mobile phone as an example, when the mobile phone receives the unlocking operation of the user, as a response, such as Figure 1 As shown in (a) in the figure, the mobile phone can display the main interface. The main interface (i.e., desktop) includes area 101, area 102, area 103, and area 104. Among them, area 101 can also be called the top status bar 101, which is used to display conventional prompt data, such as: network status (i.e., 5G), battery power, time (i.e., 08:00), etc. Area 102 occupies most of the area of ​​the main interface, is located below area 101, and is used to display application (Application, App) icons, such as: clock icon, calendar icon, gallery icon, memo icon, file management icon, email icon, music icon, calculator icon, video icon, sports health icon, weather icon, browser icon, smart assistant icon, settings icon, recorder icon, etc. Area 103 can also be called page indicator display area 103, which is located below area 102. Area 103 includes a page indicator, which is used to characterize the positional relationship between the currently displayed page and other pages. Area 104 is located at the bottom bar of the mobile phone and is used to display application icons fixed to the bottom bar of the mobile phone (the application icons do not change when the display interface switches), such as: camera icon, address book icon, phone icon and information icon.

[0047] When the user needs to activate a related function through a quick switch, the mobile phone can receive a pull-down operation (also referred to as a pull-down operation) performed by the user on the right side of the top status bar 101 of the main interface 100. In response to the pull-down operation, Figure 1 As shown in (b) of FIG. 1 , the mobile phone can display a control center interface 105. The control center interface 105 can include multiple different cards, each card is used to display controls for different functions. For example, the control center interface 105 includes a common function card 106, a recommendation card 107, a music card, a brightness adjustment control bar, a volume adjustment control bar, a general quick switch card 109, and a smart interconnection service card 110.

[0048] Among them, the frequently used display card 106 is located in the upper left corner of the control center interface 105, and is used to display frequently used shortcut switches, such as Wi-Fi shortcut switch, Bluetooth shortcut switch, etc. The shortcut switches displayed in the frequently used display card 106 are fixed.

[0049] The recommendation card 107 is located at the upper right corner of the control center interface 105 and is used to display recommended shortcut switches, for example, the recommended shortcut switches are Honor Share (YOYO suggestion) and Mobile Data (YOYO suggestion), etc. The recommended shortcut switches displayed in the recommendation card 107 are changeable.

[0050] Below the commonly used display card 106 and the recommended card 107 may be a display area for the audio-visual control 108. For example, the audio-visual control 108 may include a music card, a brightness adjustment control bar, and a volume adjustment control bar. The music card is used to display the playback information of the music in the mobile phone, and the playback information includes the playback status, the previous song shortcut switch, the next song shortcut switch, the music name, etc. The brightness adjustment control bar is used to adjust the brightness of the mobile phone. The volume adjustment control bar is used to adjust the volume of the mobile phone.

[0051] Below the audio-visual control 108 may be a display area for a general quick switch card 109, which includes multiple quick switches and a drop-down button 1091. For example, the multiple quick switches may include: a hotspot quick switch, a screenshot quick switch, a flashlight quick switch, a ring mode quick switch, and an automatic rotation quick switch. The drop-down button 1091 is used to display more quick switches.

[0052] Below the universal quick switch card 109 may be a display area for a smart interconnection service card 110, which is used to instruct the user to turn on the smart interconnection service. The smart interconnection service card 110 may include an entry interface for the introduction of the smart interconnection service (such as Figure 1 ), the icon corresponding to the smart interconnection service, and the exit control for closing the card (such as Figure 1 “×” icon shown in (b) in the figure).

[0053] It is understandable that the multiple cards in the control center interface 105 can be deleted or added according to actual usage needs. For example, the music card, the brightness adjustment control bar, and the volume adjustment control bar can be deleted. The positions of multiple cards can also be adjusted based on the user's usage habits. For example, the audio-visual control 108 in the multiple cards is placed below the universal quick switch card 109. Alternatively, the universal quick switch card 109 is placed at the top of the control center interface 105, etc. The present disclosure does not limit this.

[0054] If the current control center interface 105 does not display the shortcut switch required by the user, such as Figure 1 As shown in (b) of FIG. 1 , the mobile phone may receive a second pull-down operation performed by the user on the pull-down button 1091 of the universal quick switch card 109. In response to the second pull-down operation, as shown in FIG. Figure 1As shown in (c) in the figure, the mobile phone can display the general quick switch interface 111. In addition to the quick switches displayed on the general quick switch card 109, the general quick switch interface 110 can also display more quick switches, such as the Honor Share quick switch, the airplane mode quick switch, the mobile data quick switch, the location information quick switch, the screen recording quick switch, the eye protection mode quick switch, the dark mode quick switch, the Do Not Disturb quick switch, the wireless screen projection quick switch, the power saving mode quick switch, the calculator quick switch, the NFC quick switch, the reading quick switch, the timer quick switch and the recorder quick switch. Combined with Figure 1 As can be seen from (c) in the figure, the quick switches that the user has turned on are the ring quick switch and the location information quick switch.

[0055] Figure 1 (c) in the figure exemplarily shows a plurality of quick switches displayed in a general quick switch interface 111. It is understandable that the general quick switch interface 111 may also display other quick switches, and the position of each quick switch in the general quick switch interface 111 may be adjusted based on actual needs. The present disclosure does not limit this.

[0056] A recommended method for quick switch is proposed in the related art, and the method can be applied to electronic devices. Figure 1 The recommended quick switch displayed in the recommended card 107 in the control center interface 105 shown in (b) of FIG. Figure 2 As shown, the recommended method for this quick switch is introduced in detail below.

[0057] Step 201: The electronic device detects a pull-down operation by the user.

[0058] The pull-down operation may refer to a pull-down operation input by the user through other interfaces (such as a main interface, a setting interface, a video playback interface, an application interface, etc.) after the electronic device is unlocked when the electronic device has not yet displayed any interface of the system user interface application. The pull-down operation is used to trigger the display of the control center interface.

[0059] In some examples, when a user attempts to activate certain shortcut switches through the control center interface, the user can input a pull-down operation on the right side of the top status bar of the electronic device to use the pull-down operation to make the electronic device display the control center interface, thereby facilitating the user to activate certain shortcut switches in the control center interface.

[0060] Step 202: In response to the pull-down operation, the system user interface application of the electronic device displays a control center interface.

[0061] After detecting the user's pull-down operation, in response, the system user interface application can display the control center interface.

[0062] In some examples, the system user interface (system UI) application is an application that includes a top status bar, a notification center, and a control center. Figure 1 In (a), the top status bar is used to display network status information, battery information, time information, etc. The notification center is used to display push messages from each application and the processing options for each push message. Figure 1 (b) and Figure 1 As can be seen from (c) in the figure, the control center interface of the control center is used to display shortcut switches for some function options.

[0063] Step 203: The system user interface application detects a touch operation of the user.

[0064] The touch operation is used to change the state of the shortcut switch in the control center interface. For example, the touch operation is used to trigger the shortcut switch to turn on, or to trigger the shortcut switch to turn off.

[0065] Exemplarily, the touch operation may be any one of a single click operation (also referred to as a one-click operation), a double click operation, a sliding operation, and a long press operation.

[0066] A single click operation refers to a click operation performed by the user on a quick switch in the control center interface. For example, Figure 1 As shown in (b) in FIG. 1 , a single click operation may be a click operation of a user on a Bluetooth shortcut switch.

[0067] Since some quick switches can correspond to multiple similar quick switches, for example, for the screenshot quick switch, there are also similar quick switches as the partial screenshot quick switch and the scrolling screenshot quick switch. In order to facilitate user operation, quick switches with similar functions can be clustered into one quick switch. In this way, the control center interface can display more types of quick switches. For example, Figure 3 As shown in (a) in the figure, the control center interface displays a screenshot shortcut switch, and an expansion control is displayed in the lower right corner of the screenshot shortcut switch. The user can click the expansion control to select other shortcut switches similar to the screenshot shortcut switch.

[0068] In this case, the user can select a similar shortcut switch by a second click operation. For example, when the electronic device receives a second click operation of the user on the expansion control, in response to the second click operation, such as Figure 3As shown in (b) of FIG. 1 , the electronic device displays a screenshot function interface 201. The user can select a desired shortcut switch by clicking in the screenshot function interface 201. For example, the electronic device receives a click operation of the user on the scrolling screenshot shortcut switch in the screenshot function interface 201. In response to the click operation, the electronic device triggers the scrolling screenshot function.

[0069] The sliding operation may include an upward sliding operation and a downward sliding operation. The sliding operation refers to a sliding operation performed by a user on the adjustment control bar in the control center interface. For example, the adjustment control bar may be a volume adjustment control bar or a brightness adjustment control bar. The sliding operation may be an upward sliding operation performed by a user on the brightness adjustment control bar.

[0070] Long press operation means that in the control center interface, the user long presses certain shortcut switches to make the electronic device display the setting interface of the shortcut switch. Figure 3 As shown in (a) of FIG. 1 , the user performs a long press operation on the Honor Share shortcut switch. In response to the long press operation, as shown in FIG. Figure 3 As shown in (c) of FIG. 1 , the electronic device displays a setting interface 202 of Honor Share. The user can further learn about the function of Honor Share in the setting interface 202 of Honor Share, and can also start the Honor Share function through the Honor Share interface 202.

[0071] It is understandable that the user's touch operation may also include other operations, and the specific implementation of other operations is related to the shortcut switches set in the control center interface, and the present disclosure does not limit this.

[0072] Step 204: In response to the touch operation, the system user interface application generates behavior data information.

[0073] The behavior data information is the quick switch information corresponding to the touch operation. The quick switch information corresponding to the touch operation includes the name of the quick switch, the original state of the quick switch, the click method of the quick switch, etc. The original state of the quick switch refers to the state before the quick switch is clicked. The original state of the quick switch includes the on state and the off state.

[0074] When a touch operation input by a user is detected, in response to the touch operation, the system user interface application records the shortcut switch information (ie, behavior data information) corresponding to the touch operation, so as to determine the usage frequency of different shortcut switches using the shortcut switch information corresponding to the touch operation.

[0075] Exemplarily, if the operation object of the touch operation is a flashlight, the shortcut switch information corresponding to the touch operation includes: the name of the shortcut switch: flashlight; the original state of the shortcut switch: off; the click way of the shortcut switch: single click. The shortcut switch information corresponding to the touch operation can be recorded in the form of "suggestion data". For example, suggestion data: {"shortcutName": "flashlight", "position": "shortcut", "originalstatus": "off", "clickway": "body"}.

[0076] In some examples, when the electronic device is turned on, the system user interface application starts recording the quick switch information corresponding to the touch operation until the electronic device is turned off. When the electronic device is turned on again, the system user interface application starts to re-record the quick switch information corresponding to the touch operation. In other words, the system user interface application records the quick switch information corresponding to the touch operation for a period starting from when the electronic device is turned on to when the electronic device is turned off.

[0077] In some examples, the quick switch information corresponding to the touch operation may also include scene information. In the related art, only the low-battery scene is recorded in the quick switch information corresponding to the touch operation. If the electronic device is not in the low-battery scene when the user performs the touch operation, the scene information recorded in the quick switch information corresponding to the touch operation is empty, or the scene information is not recorded in the quick switch information corresponding to the touch operation.

[0078] Step 205: The system user interface application uses the behavior data information to determine a statistics shortcut switch.

[0079] The statistical quick switch is a quick switch whose usage frequency exceeds a threshold within a preset period.

[0080] When the electronic device displays the control center interface, the system user interface application can detect a single touch operation by the user, or can detect multiple touch operations by the user. Based on the user's touch operation, behavior data information can be generated. Afterwards, the behavior data information can be used to determine the statistics shortcut switch.

[0081] In some examples, each time a user triggers a touch operation, the system user interface application generates a behavior data message. Using the behavior data message, determining the statistical shortcut switch can be: traversing all the behavior data messages, counting the shortcut switches corresponding to the shortcut switch names in all the behavior data messages, and obtaining the counting results. According to the counting results, sorting is performed from large to small to obtain the sorted shortcut switches. According to the sorted shortcut switches, the statistical shortcut switches are determined. For example, the first two shortcut switches in the sorted shortcut switches are determined as the statistical shortcut switches.

[0082] It is understandable that the number of quick switches counted is related to the number of quick switches displayed in the recommendation area of ​​the control center interface, and the present disclosure does not impose any limitation on this.

[0083] In some examples, the statistical shortcut switches are shortcut switches whose usage frequency exceeds a threshold within a preset period (ie, from when the electronic device is turned on to when the electronic device is turned off).

[0084] Step 206: The electronic device detects a retracting operation by the user, and in response to the retracting operation, displays the interface before the pull-down operation.

[0085] When the user does not need to use the function of the quick switch, the user can perform a retracting operation on the control center interface to retract the control center interface using the retracting operation.

[0086] In some examples, when the electronic device detects a retracting operation input by the user, in response to the retracting operation, the electronic device displays the interface before the pull-down operation. For example, the interface before the pull-down operation may be a main interface, a setting interface, a video playback interface, an application interface, and the like.

[0087] In some examples, in response to the collapse operation, the electronic device displays the statistics shortcut switch in the recommended area of ​​the control center interface while the electronic device displays the interface before the pull-down. Since the user has triggered the collapse operation at this time, the user cannot view the statistics shortcut switch in the recommended area of ​​the control center interface.

[0088] For some electronic devices with poor performance, users may observe flickering in the control center interface when the control center interface is closed. Only when the user triggers the pull-down operation again can the statistics shortcut switch be viewed in the recommended area of ​​the control center interface. Figure 2 The recommended method for quick switches is shown. The statistical quick switches shown have a certain hysteresis.

[0089] Step 207: The electronic device detects the user's pull-down operation again, and in response to the pull-down operation, displays a statistics shortcut switch on the control center interface.

[0090] When the quick switch needs to be operated, the user can trigger the pull-down operation again. When the electronic device detects the user's pull-down operation again, in response to the pull-down operation, the electronic device can display the statistics quick switch in the recommendation area of ​​the control center interface.

[0091] Combination Figure 2 It can be seen from the method for recommending a quick switch provided by the illustrated embodiment that the statistical quick switch is determined by counting the frequency of users clicking on the quick switch. The data referenced by this recommendation method is too single and may not be suitable for all application scenarios. For example, by counting the frequency, the statistical quick switches are determined to be the power saving mode quick switch and the flashlight quick switch. If the current power of the electronic device used by the user is 80%, then the power saving mode quick switch in the statistical quick switch is completely incompatible with the user's current usage scenario. Therefore, Figure 2 The recommended method for quick switching provided by the illustrated embodiment has certain limitations.

[0092] In addition, combined Figure 2 It can be seen from the embodiment shown that when the user activates the quick switch through the control center interface, the user cannot view the statistics quick switch in real time in the recommended area of ​​the control center interface. Only when the user triggers the pull-down operation again can the statistics quick switch be viewed in the recommended area of ​​the control center interface. This display method has a certain lag, which affects the user experience.

[0093] To this end, the embodiments of the present disclosure provide a method for recommending a quick switch, which is applied to an electronic device. The recommended quick switches obtained by the quick switch recommendation method are more accurate. The user can quickly select the desired quick switch based on the recommended quick switch, thereby reducing the complexity of the user's operation. In addition, the quick switch recommendation method adjusts the display timing of the recommended quick switch to after the user pulls down the control center interface and before the control center interface is folded, thereby ensuring the real-time nature of the recommended quick switch and improving the user's experience.

[0094] For example, the electronic device may be a mobile terminal such as a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), or other devices, or may be a professional camera or other device. The embodiments of the present disclosure do not impose any restrictions on the specific type of the electronic device.

[0095] For example, Figure 4A schematic diagram of the structure of an electronic device 400 is shown. The electronic device may include: a processor 410, an external memory interface 420, an internal memory 421, a universal serial bus (USB) interface 430, a charging management module 440, a power management module 441, a battery 442, an antenna 1, an antenna 2, a mobile communication module 450, a wireless communication module 460, an audio module 470, a speaker 470A, a receiver 470B, a microphone 470C, an earphone interface 470D, a sensor module 480, a button 490, a motor 491, an indicator 492, a camera 493, a display screen 494, and a subscriber identification module (SIM) card interface 495, etc.

[0096] Among them, the above-mentioned sensor module 480 may include sensors such as pressure sensor, gyroscope sensor, air pressure sensor, magnetic sensor, acceleration sensor, distance sensor, proximity light sensor, fingerprint sensor, temperature sensor, touch sensor, ambient light sensor and bone conduction sensor.

[0097] It is to be understood that the structure illustrated in this embodiment does not constitute a specific limitation on the electronic device 400. In other embodiments, the electronic device 400 may include more or fewer components than shown in the figure, or combine some components, or separate some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0098] The processor 410 may include one or more processing units, for example, the processor 410 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0099] The controller may be the nerve center and command center of the electronic device 400. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

[0100] The processor 410 may also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 410 is a cache memory. The memory may store instructions or data that the processor 410 has just used or cyclically used. If the processor 410 needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor 410, and thus improves the efficiency of the system.

[0101] In some embodiments, the processor 410 may include one or more interfaces. The interface may include an inter-integrated circuit (I4C) interface, an inter-integrated circuit sound (I4S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0102] It is understandable that the interface connection relationship between the modules shown in this embodiment is only a schematic illustration and does not constitute a structural limitation on the electronic device 400. In other embodiments, the electronic device 400 may also adopt different interface connection methods in the above embodiments, or a combination of multiple interface connection methods.

[0103] The charging management module 440 is used to receive charging input from a charger. The charger can be a wireless charger or a wired charger. While the charging management module 440 charges the battery 442, it can also power the electronic device through the power management module 441.

[0104] The power management module 441 is used to connect the battery 442, the charging management module 440 and the processor 410. The power management module 441 receives input from the battery 442 and / or the charging management module 440, and supplies power to the processor 410, the internal memory 421, the external memory, the display screen 494, the camera 493, and the wireless communication module 460. In some embodiments, the power management module 441 and the charging management module 440 can also be arranged in the same device.

[0105] The wireless communication function of the electronic device 400 can be implemented through antenna 1, antenna 2, mobile communication module 450, wireless communication module 460, modem processor and baseband processor, etc. In some embodiments, the antenna 1 of the electronic device 400 is coupled with the mobile communication module 450, and the antenna 2 is coupled with the wireless communication module 460, so that the electronic device 400 can communicate with the network and other devices through wireless communication technology.

[0106] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 400 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of antennas. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

[0107] The mobile communication module 450 can provide solutions for wireless communications including 2G / 3G / 4G / 5G, etc., applied to the electronic device 400. The mobile communication module 450 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 450 can receive electromagnetic waves from the antenna 1, and perform filtering, amplification, etc. on the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation.

[0108] The mobile communication module 450 can also amplify the signal modulated by the modem processor and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some functional modules of the mobile communication module 450 can be set in the processor 410. In some embodiments, at least some functional modules of the mobile communication module 450 can be set in the same device as at least some modules of the processor 410.

[0109] The wireless communication module 460 can provide wireless communication solutions for application in the electronic device 400, including WLAN (such as (wirelessfidelity, Wi-Fi) network), Bluetooth (bluetooth, BT), global navigation satellite system (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), nearfield communication technology (nearfield communication, NFC), infrared technology (infrared, IR), etc.

[0110] The wireless communication module 460 may be one or more devices integrating at least one communication processing module. The wireless communication module 460 receives electromagnetic waves via the antenna 1, modulates the electromagnetic wave signal and performs filtering, and sends the processed signal to the processor 410. The wireless communication module 460 may also receive a signal to be sent from the processor 410, modulate the signal, amplify the signal, and convert the signal into an electromagnetic wave and radiate it via the antenna 1.

[0111] The electronic device 400 implements the display function through a GPU, a display screen 494, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 494 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 410 may include one or more GPUs, which execute program instructions to generate or change display information.

[0112] The display screen 494 is used to display images, videos, etc. The display screen 494 includes a display panel.

[0113] The electronic device 400 can realize the shooting function through the ISP, the camera 493, the video codec, the GPU, the display screen 494 and the application processor. The ISP is used to process the data fed back by the camera 493. The camera 493 is used to capture a static image or a video. In some embodiments, the electronic device 400 may include 4 or N cameras 493, where N is a positive integer greater than 4.

[0114] The external memory interface 420 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 400. The external memory card communicates with the processor 410 through the external memory interface 420 to implement a data storage function, such as storing music, video and other files in the external memory card.

[0115] The internal memory 421 may be used to store computer executable program codes, which may include instructions. The processor 410 executes various functional applications and data processing of the electronic device 400 by running the instructions stored in the internal memory 421. For example, in an embodiment of the present disclosure, the processor 410 may execute the instructions stored in the internal memory 421, and the internal memory 421 may include a program storage area and a data storage area.

[0116] 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 during the use of the electronic device 400 (such as audio data, a phone book, etc.), etc. In addition, the internal memory 421 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, a universal flash storage (UFS), etc.

[0117] The electronic device 400 can implement audio functions such as music playing and recording through the audio module 470, the speaker 470A, the receiver 470B, the microphone 470C, the headphone jack 470D, and the application processor.

[0118] Button 490 includes a power button, a volume button, etc. Button 490 can be a mechanical button. It can also be a touch button. Motor 491 can generate a vibration prompt. Motor 491 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. Indicator 492 can be an indicator light, which can be used to indicate the charging status, power changes, messages, missed calls, notifications, etc. SIM card interface 495 is used to connect a SIM card. The SIM card can be connected to and separated from the electronic device 400 by inserting it into the SIM card interface 495 or pulling it out from the SIM card interface 495. The electronic device 400 can support 4 or N SIM card interfaces, where N is a positive integer greater than 4. SIM card interface 495 can support Nano SIM card, Micro SIM card, SIM card, etc.

[0119] In addition, an operating system, such as Hongmeng operating system, iOS operating system, Android operating system, Windows operating system, etc., is running on the above components. Applications can be installed and run on the operating system. In other embodiments, there may be multiple operating systems running in the electronic device.

[0120] It should be understood that Figure 4 The hardware modules included in the electronic device shown are only described for example, and do not limit the specific structure of the electronic device. In fact, the electronic device provided by the embodiment of the present disclosure may also include other hardware modules that have an interactive relationship with the hardware modules illustrated in the figure, which are not specifically limited here. For example, the electronic device may also include a flashlight, a micro-projection device, etc. For another example, if the electronic device is a PC, then the electronic device may also include components such as a keyboard and a mouse.

[0121] The software system of the electronic device may adopt a layered architecture, an event-driven architecture, a micro-core architecture, a micro-service architecture, or a cloud architecture. Taking the system as an example, the software structure of the electronic device is illustrated.

[0122] Figure 5 is a software structure diagram of an electronic device in an embodiment of the present disclosure. The layered architecture divides the software into several layers, each with a clear role and division of labor. The layers communicate with each other through software interfaces. In some embodiments, The system is divided into four layers, from top to bottom: application layer, application framework layer, Android runtime and system library, and kernel layer.

[0123] The application layer may include a series of application packages. For example, the application package may include camera, gallery, calendar, phone, map, navigation, WLAN, Bluetooth, system user interface, data center, computing engine, short message and other applications (application, APP).

[0124] Among them, the system user interface application can provide a visual interface of the operating system and its functions, so that users can use the various functions provided by the operating system. Generally, the system user interface application includes components such as the desktop, window manager, top taskbar, notification center, and control center. The system user interface application is used to manage interface elements and make them operational.

[0125] Computing engines can use computer hardware and software resources to perform various computing tasks. For example, they can process data analysis, scientific computing, machine learning, and other tasks. Computing engines usually contain components such as computing, storage, and communication. Computing engines are used to perform tasks and manage resource usage.

[0126] The data center can help different applications and systems access and share data. The data center provides data storage, access, processing, management and other functions so that data can better meet the needs of different application systems, services and users. The data center solves the problem of data dispersion and difficulty in coordination caused by the diversity of data sources and their respective storage and management. It can effectively improve the value and utilization efficiency of data and accelerate digital transformation.

[0127] The application framework layer provides an application programming interface (API) and a programming framework for the applications in the application layer. The application framework layer includes some predefined functions.

[0128] The application framework layer may include an activity manager, a window manager, a content provider, a view system, a resource manager, a notification manager, etc., and the embodiments of the present disclosure do not impose any restrictions on this.

[0129] Activity Manager: used to manage the life cycle of each application. Applications usually run in the operating system in the form of Activities. For each Activity, there is a corresponding application record (ActivityRecord) in the Activity Manager. This ActivityRecord records the status of the Activity of the application. The Activity Manager can use this ActivityRecord as an identifier to schedule the Activity process of the application.

[0130] Window Manager Service: It is used to manage the graphical user interface (GUI) resources used on the screen. Specifically, it can be used to obtain the screen size, create and destroy windows, show and hide windows, layout windows, manage focus, and manage input methods and wallpapers.

[0131] Content providers are used to store and retrieve data and make it accessible to applications. This data can include videos, images, audio, calls made and received, browsing history and bookmarks, phone books, etc. Resource managers provide applications with various resources, such as localized strings, icons, images, layout files, video files, etc.

[0132] Android Runtime includes core libraries and virtual machines. Android runtime is responsible for scheduling and management of the Android system. The core library consists of two parts: one is the function that the Java language needs to call, and the other is the Android core library. The application layer and the application framework layer run in the virtual machine. The virtual machine executes the Java files of the application layer and the application framework layer as binary files. The virtual machine is used to perform object life cycle management, stack management, thread management, security and exception management, and garbage collection.

[0133] The application framework layer may also include a perception module. The perception module is used to receive a scene query request sent by a system user interface application. In response to the scene query request, a scene query result is sent to the system user interface application. The perception module is also used to receive a scene query request sent by a computing engine. In response to the scene query request, a scene query result is sent to the computing engine. Among them, the scene query request is used to request to query the scene information in which the electronic device is currently located. The scene query result includes the scene in which the electronic device is currently located. Exemplarily, the scene in which the electronic device is currently located may include any scene in a low-battery scene, an airport scene, a dim light scene, a sleeping scene, a video scene, a meeting scene, a reading scene, a home scene, a company scene, and a non-scene.

[0134] The system library may include multiple functional modules, such as surface manager, media library, 3D graphics processing library (such as OpenGL ES), 2D graphics engine (such as SGL), etc.

[0135] The surface manager is used to manage the display subsystem and provide fusion of 2D and 3D layers for multiple applications. The media library supports playback and recording of multiple common audio and video formats, as well as static image files. The media library can support multiple audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc. OpenGL ES is used to implement 3D graphics drawing, image rendering, synthesis, and layer processing. SGL is a drawing engine for 2D drawing.

[0136] The system library may also include a database, which is used to receive a scene query request sent by the system user interface application. In response to the scene query request, the scene query result is sent to the system user interface application. The database is also used to receive a scene query request sent by the computing engine. In response to the scene query request, the scene query result is sent to the computing engine. Among them, the database may include a scene field. The database may feed back the scene query result to the system user interface application or the computing engine in the form of a scene field.

[0137] The kernel layer is a layer between hardware and software. The kernel layer at least includes display driver, camera driver, audio driver, sensor driver, etc., and the embodiments of the present disclosure do not impose any restrictions on this.

[0138] In some scenarios, the database can be set in a server, and the server and the electronic device can communicate via wired or wireless means. If the database is set in a server, the database in the server can provide the electronic device with a larger capacity, higher performance, better reliability and availability, and stronger security measures.

[0139] In some scenarios, the data center can be set up in the server, and the server and electronic devices can communicate via wired or wireless means. If the data center is set up in the server, centralized data management and collaboration can be achieved, the value and utilization efficiency of data can be improved, and better scalability, security and privacy protection can be achieved. Setting the data center on the server is suitable for processing large amounts of data and supports access and sharing by multiple applications and systems.

[0140] The methods in the following embodiments can all be implemented in an electronic device having the above hardware structure or software structure. In the following embodiments, the database and the data middle platform are set in an electronic device as an example for illustrative description.

[0141] The following is a detailed description of a recommended method for a quick switch provided by an embodiment of the present disclosure in conjunction with the accompanying drawings. The method can be applied to the above electronic device. Figure 6 As shown, the method specifically includes:

[0142] Step 601: The electronic device detects a pull-down operation by the user.

[0143] The electronic device in the embodiment of the present disclosure detects the user's pull-down operation and can refer to the above Figure 2 Step 201 in the illustrated embodiment will not be described in detail in the embodiment of the present disclosure.

[0144] Step 602: In response to the pull-down operation, the system user interface application of the electronic device sends a shortcut switch query request to the computing engine.

[0145] The quick switch query request is used to request to obtain the predicted quick switch.

[0146] After the electronic device detects the user's pull-down operation, in response, the system user interface application can generate a shortcut switch query request and send the shortcut switch query request to the computing engine to obtain the predicted shortcut switch through the computing engine.

[0147] In some examples, based on the pull-down operation, the system user interface application generates a quick switch query request and sends the quick switch query request to the computing engine.

[0148] In some examples, when a user triggers a pull-down operation, the system user interface application generates a quick switch query request and sends the quick switch query request to the computing engine.

[0149] In some examples, in response to a pull-down operation, the process of the system user interface application generating a quick switch query request may include: first, when the user performs a pull-down operation on the touch screen of the electronic device, a user interface event corresponding to the pull-down operation is triggered. Then, the operating system of the electronic device (e.g., Android TM) will capture the user interface event corresponding to the drop-down operation, and parse the user interface event corresponding to the drop-down operation to represent the drop-down operation. Then, the operating system uses the identified drop-down operation as input, calls the Application Programming Interface (API) corresponding to the drop-down operation, and passes the drop-down operation to the system user interface application. After the system user interface application receives the drop-down operation through the API, it will generate a quick switch query request based on the drop-down operation.

[0150] In some examples, before the system user interface application sends a quick switch query request to the computing engine, the system user interface application also needs to subscribe to the computing engine. After the subscription is successful, the system user interface application can obtain the predicted quick switch through the computing engine.

[0151] The process of the system user interface application subscribing to the computing engine is as follows: when a user performs a power-on and unlocking operation on the electronic device, the system user interface application sends a subscription message to the computing engine in response to the power-on and unlocking operation. The subscription message is used to request the computing engine to execute a subscription process. The computing engine receives the subscription message, and in response to the subscription message, the computing engine executes the subscription process. After the subscription process is completed, the computing engine sends the subscription result to the system user interface application.

[0152] Generally, the system user interface application can implement the subscription of the computing engine within 5 seconds. If the computing engine supports the subscription of the system user interface application, the computing engine will provide corresponding support capabilities for the system user interface application. If the computing engine does not support the subscription of the system user interface application, the computing engine will feedback a subscription failure message to the system user interface application. The subscription failure message will indicate the reason why the system user interface application failed to subscribe (for example, the system environment does not support it).

[0153] In the case where the system user interface application fails to subscribe to the computing engine, the system user interface will automatically send a subscription message to the computing engine at a fixed period until the subscription to the computing engine succeeds. Exemplarily, the fixed period is 24 hours. The fixed period can be flexibly set based on actual needs, and the present disclosure does not limit this.

[0154] In some examples, the electronic device includes an intelligent assistant application. The intelligent assistant application can be used to turn on or off the function of the computing engine. When the intelligent assistant application is started, the function of the computing engine is in an on state, and the system user interface application can call the computing engine. When the intelligent assistant application is turned off, the function of the computing engine is in an off state, and the system user interface application cannot call the computing engine.

[0155] The computing engine can detect the status of the smart assistant application. The status of the smart assistant application includes an on state and a off state. When the user closes the smart assistant application, the computing engine can detect that the smart assistant application is in a closed state, and the computing engine will send a close instruction to the system user interface application. The close instruction is used to indicate that the system user interface application cannot continue to call the computing engine. When the system user interface receives the close instruction, if the electronic device detects the user's pull-down operation, the system user interface application will no longer send a quick switch query request to the computing engine. After that, the system user interface application can use the statistical quick switches to display recommended quick switches for users in the recommendation area of ​​the control center interface.

[0156] When the user starts the smart assistant application, the computing engine can detect that the smart assistant application is in the turned-on state, and the computing engine will send an opening instruction to the system user interface application. The opening instruction is used to indicate that the system user interface application can continue to call the computing engine. When the system user interface application receives the opening instruction, the system user interface application will continue to subscribe to the computing engine. After the computing engine is successfully subscribed, the system user interface application can obtain the predicted shortcut switch through the computing engine. The predicted shortcut switch is then used to display the recommended shortcut switch for the user in the recommendation area of ​​the control center interface.

[0157] Step 603: The computing engine receives a quick switch query request.

[0158] Step 604: In response to the quick switch query request, the computing engine sends the predicted quick switch to the system user interface application.

[0159] After the computing engine receives the quick switch query request, in response, the computing engine can send a predicted quick switch to the system user interface application, and then the system user interface application can display the recommended quick switch for the user in the recommendation area of ​​the control center interface based on the predicted quick switch.

[0160] In some examples, the computing engine includes a recommendation model. In response to a quick switch query request, the computing engine can generate a predicted quick switch in two ways. The first is to determine the predicted quick switch based on a trained recommendation model. The second is to determine the predicted quick switch based on multiple preset quick switches.

[0161] Exemplarily, in response to the quick switch query request, the computing engine first determines whether the recommendation model has been trained. If the recommendation model has been trained, the computing engine can use the first implementation method, that is, determine the predicted quick switch based on the trained recommendation model.

[0162] If the recommendation model has not been trained, the computing engine may use the second implementation method, that is, determining a predicted shortcut switch based on a plurality of preset shortcut switches.

[0163] In some examples, if the recommendation model has been trained, the computing engine uses the first implementation method to determine the predicted shortcut switch process, which may be: determining that the recommendation model has been trained, the computing engine obtains the scene information of the electronic device; then the scene information of the electronic device is input into the trained recommendation model, and the trained recommendation model outputs the predicted shortcut switch; finally, the computing engine sends the predicted shortcut switch to the system user interface application.

[0164] In some examples, if the recommendation model has not completed training, the computing engine uses the second implementation method, and the process of determining the predicted shortcut switch may include: determining that the recommendation model has not completed training, the computing engine determines the predicted shortcut switch based on multiple preset shortcut switches, and then the computing engine sends the predicted shortcut switch to the system user interface application.

[0165] The process of determining the predicted shortcut switch based on the plurality of preset shortcut switches may be: randomly selecting a preset number of predicted shortcut switches based on the plurality of preset shortcut switches.

[0166] It is understandable that when the recommendation model has not completed training, since the predicted quick switch is determined based on multiple preset quick switches, the predicted quick switch can be determined based on the number of recommended quick switches displayed in the recommendation area of ​​the control center interface. In other words, the number of predicted quick switches is consistent with the number of recommended quick switches that need to be displayed in the recommendation area of ​​the control center interface. For example, if the number of recommended quick switches displayed in the recommendation area of ​​the control center interface is 2, then 2 predicted quick switches can be determined based on multiple preset quick switches.

[0167] In some examples, the computing engine obtains the scene information of the electronic device by using a database, or the computing engine obtains the scene information of the electronic device by using a perception module.

[0168] The process of the computing engine obtaining the scene information of the electronic device through the database can be: the computing engine sends a scene query request to the database; then the database receives the scene query request, and finally, the database responds to the scene query request, determines the scene query result, and sends the scene query result to the computing engine.

[0169] The process of the computing engine acquiring the scene information of the electronic device through the perception module can be: the computing engine sends a scene query request to the perception module; then the perception module receives the scene query request, and finally, the perception module responds to the scene query request, determines the scene query result, and sends the scene query result to the computing engine.

[0170] Exemplarily, the scene query result may be any scene among a low-battery scene, an airport scene, a dim light scene, a sleeping scene, a video scene, a meeting scene, a reading scene, a home scene, an office scene, and a non-scene.

[0171] After the computing engine obtains the scene information of the electronic device, the scene information of the electronic device is input into the trained recommendation model, and the trained recommendation model outputs the predicted shortcut switch. The process can be: the computing engine inputs the obtained scene query result into the trained recommendation model, and the trained recommendation model outputs the predicted shortcut switch. The predicted shortcut switch output by the trained recommendation model can be one or more. When an error occurs in the trained recommendation model, the number of predicted shortcut switches output can also be 0.

[0172] In some examples, the computing engine determines whether the recommendation model is a trained recommendation model by evaluating the performance of the recommendation model using some evaluation indicators, such as accuracy, recall, etc. If the evaluation indicator of the model reaches a preset threshold or preset standard, the computing engine considers that the recommendation model has completed training.

[0173] In some scenarios, since the recommendation model in the computing engine needs training data before use, the training data of the recommendation model is obtained based on the behavior data information. The behavior data information is related to the user's touch operation, and the specific content of the behavior data information can refer to step 204.

[0174] Therefore, when the user has not triggered the touch operation, the computing engine cannot use the recommendation model to generate a predicted shortcut switch. Therefore, after the computing engine receives the shortcut switch query request, in response, the computing engine can determine the predicted shortcut switch based on multiple preset shortcut switches and send the predicted shortcut switch to the system user interface application. For example, the multiple preset shortcut switches are a screenshot shortcut switch, a screen recording shortcut switch, a calculator shortcut switch, a timer shortcut switch, and a recorder shortcut switch. The predicted shortcut switch can be a screenshot shortcut switch and a screen recording shortcut switch.

[0175] Typically, the number of predicted quick switches displayed in the recommendation area of ​​the control center interface is 2. As the control center interface design is updated and iterated, the number of predicted quick switches may change, and accordingly, the number of predicted quick switches sent by the computing engine to the system user interface application will also change. For example, as the control center interface design is updated and iterated, the number of predicted quick switches displayed in the recommendation area of ​​the control center interface is 3, and the number of predicted quick switches sent by the computing engine to the system user interface application is 3. This disclosure does not limit this.

[0176] Step 605: The system user interface application receives the predicted shortcut switch.

[0177] Step 606: The system user interface application determines a recommended quick switch based on the predicted number of quick switches, and displays the recommended quick switch.

[0178] After obtaining the predicted quick switches, the system user interface application can first determine the recommended quick switches based on the number of predicted quick switches, and then display the recommended quick switches in the recommendation area of ​​the control center interface.

[0179] In some examples, since the number of predicted quick switches displayed in the recommendation area of ​​the control center interface is fixed, it can be seen from step 604 that the number of predicted quick switches output by the calculation engine can be fixed or not. Therefore, after the system user interface application obtains the predicted quick switches, the system user interface application needs to further determine the recommended quick switches based on the number of predicted quick switches.

[0180] For example, after the system user interface application obtains the predicted shortcut switches, it can determine the recommended shortcut switches based on the number of predicted shortcut switches. Figure 7 As shown, the process of determining the recommended quick switch based on the predicted number of quick switches is: determining whether the predicted number of quick switches is greater than or equal to a first threshold based on the predicted number of quick switches. If the predicted number of quick switches is greater than or equal to the first threshold, determining the recommended quick switch based on the predicted quick switch.

[0181] If the number of predicted shortcut switches is less than the first threshold, then continue to determine whether the number of predicted shortcut switches is equal to the second threshold. If the number of predicted shortcut switches is equal to the second threshold, determine the recommended shortcut switch based on the statistical shortcut switches.

[0182] If the number of predicted shortcut switches is not equal to the second threshold (ie, greater than the second threshold), indicating that the number of predicted shortcut switches is greater than the second threshold and less than the first threshold, a recommended shortcut switch is determined based on the predicted shortcut switches and the statistical shortcut switches.

[0183] The first threshold and the second threshold are related to the number of predicted shortcut switches displayed in the recommendation area of ​​the control center interface. The process of determining the statistical shortcut switches can refer to the contents of the following steps 606 to 608, which will not be repeated here.

[0184] For example, the number of predicted quick switches displayed in the recommendation area of ​​the control center interface is 2. The first threshold is 2. The second threshold is 0. After obtaining the predicted quick switches, the system user interface application can determine whether the number of predicted quick switches is greater than or equal to the first threshold based on the number of predicted quick switches. If the number of predicted quick switches is greater than or equal to the first threshold, that is, the number of predicted quick switches is greater than or equal to 2, it means that the number of predicted quick switches generated by the calculation engine is greater than or equal to the number of predicted quick switches displayed in the recommendation area, and the recommended quick switch can be directly obtained based on the predicted quick switches.

[0185] If the number of predicted shortcut switches is less than the first threshold (i.e., less than 2), then it is determined whether the number of predicted shortcut switches is equal to the second threshold (i.e., equal to 0). If the number of predicted shortcut switches is equal to 0, it means that there may be an error in the recommendation model in the calculation engine, and a statistical shortcut switch can be generated based on steps 606 to 608, and the statistical shortcut switch can be used to obtain a recommended shortcut switch.

[0186] If the number of predicted shortcut switches is greater than 0, that is, the number of predicted shortcut switches is greater than the second threshold and less than the first threshold (greater than 0 and less than 2), the number of predicted shortcut switches is equal to 1, indicating that the trained recommendation model in the computing engine only outputs 1 predicted shortcut switch. Since the number of predicted shortcut switches displayed in the recommendation area is 2, it is necessary to select 1 statistical shortcut switch from the statistical shortcut switches. Therefore, 1 predicted shortcut switch and 1 statistical shortcut switch are finally used to obtain the recommended shortcut switch.

[0187] In some examples, steps 602 to 605 are performed during the pull-down process of the control center interface, that is, when the electronic device displays the control center interface, the quick switches displayed in the recommendation area of ​​the control center interface are recommended quick switches. In this way, when the user triggers the pull-down operation, the user can view the recommended quick switches in the recommendation area in real time, thereby ensuring the real-time nature of the recommendation.

[0188] In addition, in combination with the aforementioned step 604, it can be known that after receiving the quick switch query request, the computing engine can respond to the quick switch query request and send the predicted quick switch to the system user interface application in two different ways. If the computing engine determines the predicted quick switch using the first implementation method, it is necessary to first perform the training process of the recommendation model. The training process of the recommendation model includes obtaining training data, and then using the training data to train the recommendation model to obtain the trained recommendation model.

[0189] The following takes the contents of step 607 to step 616 as an example to illustrate the process of obtaining training data, and then using the training data to train the recommendation model, thereby obtaining the trained recommendation model.

[0190] Step 607: The system user interface application detects a touch operation by the user.

[0191] Step 608: In response to the touch operation, the system user interface application generates behavior data information.

[0192] Step 609: The system user interface application determines a statistics shortcut switch based on the behavior data information.

[0193] The system user interface application in the embodiment of the present disclosure detects a user's touch operation. In response to the touch operation, the system user interface application generates behavior data information. The system user interface determines the statistics shortcut switch based on the behavior data information. Figure 2 Steps 203 to 205 in the illustrated embodiment will not be described in detail in the embodiment of the present disclosure.

[0194] Step 610: The system user interface application sends a scene query request to the database.

[0195] The scene query request is used to request a query of the scene in which the electronic device is currently located.

[0196] Exemplarily, the scene in which the electronic device is currently located includes a low-battery scene, an airport scene, a dim light scene, a sleeping scene, a video scene, a meeting scene, a reading scene, a home scene, a company scene, and a non-scene, etc.

[0197] Since the user's operation of the quick switch is related to the current scene of the electronic device to a certain extent, for example, when the electronic device is currently in a low-battery scene, the user generally chooses to activate the power saving mode quick switch. When the electronic device is currently in an airport scene, the user generally chooses to activate the flight mode quick switch.

[0198] Therefore, after the system user interface application obtains the behavioral data information, the system user interface application can also obtain the current scene of the electronic device through a scene query request, which helps to more accurately recommend the required shortcut switches to the user, thereby improving the user's satisfaction.

[0199] It should be noted that the embodiment of the present disclosure may not limit the execution order between step 609 and step 610. For example, step 609 may be executed first and then step 610; step 610 may be executed first and then step 609; or step 609 and step 610 may be executed simultaneously, which may be determined according to actual usage requirements.

[0200] Step 611: The database receives a scene query request.

[0201] Step 612: In response to the scene query request, the database sends the scene query result to the system user interface application.

[0202] After receiving the scene query request, the database may determine the scene query result and feed back the scene query result (ie, the first scene information) to the system user interface application.

[0203] In some examples, the scene query result sent by the database to the system user interface application can be sent in the form of a scene field. It is understandable that the database can also send the scene query result to the system user interface application in other forms, and the present disclosure does not limit this.

[0204] In some scenarios, the system user interface application can also obtain scene query results through the perception module. The process of the system user interface application obtaining the scene query results through the perception module is as follows: first, the system user interface application sends a scene query request to the perception module; then the perception module receives the scene query request, and finally, the perception module responds to the scene query request, determines the scene query result, and sends the scene query result to the system user interface application. For example, the system user interface application determines that the scene currently in which the electronic device is located is an airport scene through the perception module.

[0205] In some scenarios, the system user interface application can first obtain the scene query result from the database. If the scene query result cannot be obtained through the database, the scene query result can be obtained through the perception module in the electronic device. Alternatively, the system user interface application can first obtain the scene query result from the perception module. If the scene query result cannot be obtained through the perception module, the scene query result can be obtained through the database.

[0206] Step 613: The system user interface application receives the scene query result, encapsulates the scene query result and behavior data information, and obtains encapsulated data.

[0207] After receiving the scene query result, the system user interface application can process the scene query result and behavior data information to obtain encapsulated data.

[0208] In some examples, scene query results and behavior data information are stored in the form of a single field. In order to make the storage and call of these fields more convenient, the scene query results and behavior data information can be encapsulated, that is, the single field corresponding to the scene query result and the single field corresponding to the behavior data information are placed in a larger container. Then, multiple fields can be read from the container at one time. This eliminates the need to read multiple times, improving data processing efficiency.

[0209] Exemplarily, the system user interface application encapsulates the scene query results and behavior data information, and the encapsulated data can be: a single field corresponding to the scene query result and a single field corresponding to the behavior data information are placed into a new data structure (i.e., a container). For example, the scene query results and behavior data information exist in the form of strings, and a new data structure is formed by associating the strings with corresponding key names. The new data structure stores the scene query results and behavior data information in the form of key names and key values ​​(i.e., strings). In addition, other data structures such as dictionaries and mappings can also be used in the new data structure to encapsulate scene query results and behavior data information, and the present disclosure does not limit this.

[0210] For example, the data structure corresponding to the encapsulated data is suggestion data: {"shortcutName":"flashlight","position":"shortcut","originalstatus":"off","clickway":"body","scene":"dark light mode"}. In this data structure, "flashlight","shortcut","off"and"body"are behavior data information. "dark light mode" is the scene query result.

[0211] Step 614: The system user interface application sends the packaged data to the data center.

[0212] After the system user interface application obtains the packaged data, the system user interface can send the packaged data to the data middle station so that the data middle station uses the packaged data to generate training data.

[0213] In some examples, before the system user interface application sends the packaged data to the data middle station, the system user interface application needs to subscribe to the data middle station.

[0214] In some examples, the process of the system user interface application subscribing to the data middle station is as follows: the system user interface application sends an initialization instruction to the data middle station. The data middle station receives the initialization instruction and initializes in response to the initialization instruction. The system user interface application may include a monitoring API, and when the monitoring API detects that the data middle station has been successfully initialized, the monitoring value of the system user interface application is output as true. When the monitoring value is output as true, it means that the system user interface application has successfully subscribed to the data middle station, and the system user interface application can send encapsulated data to the data middle station.

[0215] Step 615: The data center receives the packaged data and sends the training data to the computing engine.

[0216] The training data includes encapsulated data.

[0217] In some examples, after receiving the packaged data, the data center can send the packaged data to the computing engine. After the computing engine obtains the packaged data, it can use the packaged data as training data to train the recommendation model, thereby obtaining a trained recommendation model, and then use the trained recommendation model to generate a prediction shortcut switch.

[0218] In some examples, in order to obtain more accurate training data, after receiving the packaged data, the data center can also obtain the scene information (i.e., the second scene information) sent by other applications. Then, the scene information sent by other applications and the packaged data can be used as training data to train the recommendation model, so that the recommendation effect of the trained recommendation model is better.

[0219] If the data center also obtains scene information sent by other applications, the data center will first parse the packaged data to obtain the parsed data (i.e., scene query results and behavior data information). Then the scene query results, behavior data information and scene information sent by other applications will be packaged again to obtain training data, and finally the training data will be sent to the computing engine.

[0220] Exemplarily, the scene information sent by other applications acquired by the data center may be scene information sent by an Always On Display (AOD) application, and the scene information sent by the AOD application may be screen-off scene information. Of course, the AOD application may also send other scene information according to the actual use scenario of the electronic device. This disclosure is not limited to this.

[0221] Step 616: The computing engine receives the training data, and uses the training data to train the recommendation model to obtain a trained recommendation model.

[0222] After receiving the training data, the computing engine may use the training data to train the recommendation model, thereby obtaining a trained recommendation model. Thereafter, the trained recommendation model may be used to generate a prediction shortcut switch.

[0223] In some examples, the recommendation model may adopt a classic deep learning neural network model. Specifically, the recommendation model may be constructed based on basic network models such as multilayer perceptron (MLP), convolutional neural network (CNN) and recurrent neural network (RNN).

[0224] MLP is a feed-forward artificial neural network model used to map multiple input data sets to a single output data set. MLP usually includes: an input layer, multiple fully connected layers, and an output layer. The input layer may include at least one input, and the output layer may include at least one output. The number of inputs in the input layer, the number of fully connected layers, and the number of outputs in the output layer can be determined according to requirements.

[0225] CNN usually includes: input layer, convolution layer, pooling layer, fully connected layer (FC) and output layer. Generally speaking, the first layer of CNN is the input layer and the last layer is the output layer. The convolution layer usually contains several feature planes, each of which can be composed of some rectangularly arranged neural units. The neural units in the same feature plane share weights, and the shared weights are the convolution kernels. The pooling layer usually comes after the convolution layer. The pooling layer can obtain features with large dimensions, cut the features into several regions, take the maximum value or average value, and thus obtain new features with smaller dimensions. The fully connected layer can combine all local features into global features to calculate the final score of each category.

[0226] RNN is a type of recursive neural network that takes sequence data as input, performs recursion in the direction of sequence evolution, and all nodes are connected in a chain.

[0227] The training of the recommendation model consists of the following steps:

[0228] 1. Initialize the recommendation model.

[0229] Initializing the recommendation model can refer to the initialization method of the prior art to initialize the weight parameters and bias parameters in the recommendation model. There are four commonly used initialization methods, namely Gaussian initialization, Xavier initialization, MSRA initialization and He initialization. Generally, the bias parameters are initialized to 0 and the weight parameters are randomly initialized. The specific initialization process is not described in detail in this disclosure.

[0230] 2. Input the training data into the recommendation model, and after cyclic iteration, obtain the trained recommendation model.

[0231] The training data may include scene query results and behavior data information. The training data may also include scene query results, behavior data information, and scene information sent by other applications.

[0232] The training data is input into the recommendation model. After a cycle of iterations, the trained recommendation model is obtained, which specifically includes the steps of feature extraction, determining the target quick switch result, and determining the trained recommendation model.

[0233] Exemplarily, feature extraction refers to inputting the name of the quick switch and the scene query result in the behavior data information into the recommendation model, and the recommendation model extracts features from the name of the quick switch and the scene query result through the feature extraction network to obtain the feature extraction result. Determining the target quick switch result refers to inputting the feature extraction result into the regression network, and the regression network outputs the regression result. Then the feature extraction result corresponding to the scene query result is multiplied by the regression result to obtain the target quick switch result. Determining the trained recommendation model refers to comparing the target quick switch result with the quick switch in the behavior data information, determining the difference between the target quick switch result and the quick switch in the behavior data information, and then determining whether the difference meets the threshold. In the case of not meeting the threshold, the loss value is determined based on the difference and the loss function, and the weight parameters and bias parameters in the recommendation model are adjusted according to the loss value. Then, the adjusted parameters are used to obtain a new target quick switch result and a new loss value, and it is determined whether the new loss value meets the threshold. Repeat this cycle until the loss value meets the threshold, thereby obtaining a trained recommendation model.

[0234] The above process of adjusting the weight parameters and bias parameters in the recommendation model according to the loss value can be: setting a preset condition that the loss value satisfies, and the preset condition can be that the loss value is less than the target loss value. If it is not satisfied, adjust the weight parameters and bias parameters. Update the recommendation model according to the adjusted weight parameters and bias parameters. Then repeat the above processing of the training data with the adjusted recommendation model, and then calculate the new loss value, and judge whether the new loss value meets the preset conditions, and iterate repeatedly until the new loss value meets the preset conditions, thereby obtaining the trained recommendation model. The loss value is specifically calculated by inputting the difference between the target quick switch result and the quick switch in the behavior data information into the loss function. The calculation of the loss value can also perform other operations according to needs, which are not illustrated here one by one.

[0235] The above steps of this embodiment are explained using a set of training data as an example. It can be understood that multiple sets of training data can also be used to perform the training process on the above recommendation model. Adjusting the recommendation model according to the multiple sets of training data can improve the recommendation accuracy and intelligence of the trained recommendation model.

[0236] In combination with step 607 to step 616, it can be seen that the training data used to train the recommendation model is obtained based on the touch operation triggered by the user. Therefore, when the user has not triggered the touch operation, the computing engine cannot train the recommendation model, and it is also impossible to generate the prediction shortcut switch using the first implementation method mentioned above.

[0237] In addition, in order to ensure the performance of the trained recommendation model, the computing engine needs to obtain a large amount of training data. Combined with the above, it can be seen that the training data is related to the user's touch operation. That is to say, when the obtained training data is insufficient (i.e., when the user triggers the pull-down operation for the first few times), the recommended shortcut switches displayed in the recommendation area of ​​the control center interface are determined based on multiple preset shortcut switches. Only after the recommendation model is trained can the predicted shortcut switches be obtained based on the trained recommendation model.

[0238] In addition, a complete operation performed by a user in the control center interface also includes the following steps:

[0239] Step 617: The system user interface application detects the user's folding operation.

[0240] The folding operation refers to a swiping operation performed by the user on the control center interface.

[0241] It should be noted that the embodiment of the present disclosure may not limit the execution order of step 617. Step 617 may be executed at any step after step 607.

[0242] Step 618: In response to the user's folding operation, the electronic device displays the interface before pulling down.

[0243] In some examples, when the user does not need to operate in the control center interface, the electronic device can detect the user's retracting operation and use the retracting operation to make the electronic device display the interface before pulling down.

[0244] Based on the method provided by the embodiment of the present disclosure, after detecting the pull-down operation of the user, the present disclosure can respond to the pull-down operation of the user and obtain the scene information of the electronic device. Then the scene information of the electronic device is used as the input of the trained recommendation model, so that the trained recommendation model outputs the predicted shortcut switch. Afterwards, the predicted shortcut switch is used to obtain the recommended shortcut switch, and the recommended shortcut switch is displayed, and the display timing of the recommended shortcut switch is before the user inputs the retract operation, that is, the user can view the recommended shortcut switch in real time, ensuring the real-time nature of the recommendation. Compared with the related art, in which the recommended shortcut switch is generated by the statistical frequency of the shortcut switch, the present disclosure determines the predicted shortcut switch by using the trained recommendation model, and the trained recommendation model also refers to the scene information of the electronic device when generating the predicted shortcut switch. Since the scene information of the electronic device can affect the user's choice of the shortcut switch to a certain extent, the accuracy of the output predicted shortcut switch can be guaranteed to be higher by adopting this method, and accordingly, the accuracy of the recommended shortcut switch obtained based on the predicted shortcut switch is also higher.

[0245] It should be understood that each step in the above method embodiment provided by the present disclosure can be completed by an integrated logic circuit of hardware in a processor or by instructions in the form of software. The method steps disclosed in the embodiments of the present disclosure can be directly embodied as being executed by a hardware processor, or by a combination of hardware and software modules in a processor.

[0246] In one example, the unit in the above apparatus may be one or more integrated circuits configured to implement the above method, such as one or more ASICs, or one or more DSPs, or one or more FPGAs, or a combination of at least two of these integrated circuit forms.

[0247] For another example, when the units in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a CPU or other processor that can call a program. For another example, these units can be integrated together and implemented in the form of a system on a chip SOC.

[0248] In one implementation, the units of the above apparatus implementing the corresponding steps in the above method can be implemented in the form of a processing element scheduling program. For example, the apparatus may include a processing element and a storage element, and the processing element calls the program stored in the storage element to execute the method of the above method embodiment. The storage element may be a storage element on the same chip as the processing element, that is, an on-chip storage element.

[0249] In another implementation, the program for executing the above method may be in a storage element on a different chip from the processing element, i.e., an off-chip storage element. In this case, the processing element calls or loads the program from the off-chip storage element to the on-chip storage element to call and execute the method of the above method embodiment.

[0250] For example, the embodiments of the present disclosure may also provide a device, such as an electronic device, which may include a processor and a memory for storing instructions executable by the processor. When the processor is configured to execute the above instructions, the electronic device implements the data processing method of the above embodiment. The memory may be located inside the electronic device or outside the electronic device. And the processor includes one or more.

[0251] In another implementation, the unit of the device implementing each step in the above method may be configured as one or more processing elements, which may be arranged on the corresponding electronic device, and the processing element here may be an integrated circuit, for example: one or more ASICs, or one or more DSPs, or one or more FPGAs, or a combination of these integrated circuits. These integrated circuits may be integrated together to form a chip.

[0252] For example, the present disclosure also provides a chip, such as Figure 8 As shown, the chip system includes at least one processor 801 and at least one interface circuit 802. The processor 801 and the interface circuit 802 can be interconnected through a line. For example, the interface circuit 802 can be used to receive signals from other devices. For another example, the interface circuit 802 can be used to send signals to other devices (such as the processor 801).

[0253] For example, the interface circuit 802 can read the instructions stored in the memory in the device and send the instructions to the processor 801. When the instructions are executed by the processor 801, the electronic device (such as Figure 4 The electronic device 400 shown in the figure performs each step in the above embodiment. Of course, the chip system may also include other discrete devices, which is not specifically limited in the embodiment of the present disclosure.

[0254] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by an electronic device, the electronic device can implement the above-mentioned data processing method.

[0255] The disclosed embodiments also provide a computer program product, including computer instructions for the electronic device to run as described above, and when the computer instructions are run in the electronic device, the electronic device can implement the data processing method as described above. Through the description of the above implementation methods, technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0256] In the several embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0257] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0258] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0259] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present disclosure is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, such as a program. The software product is stored in a program product, such as a computer-readable storage medium, including a number of instructions to enable a terminal device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the methods of each embodiment of the present disclosure. The aforementioned storage medium includes: U disk, mobile hard disk, ROM, RAM, disk or optical disk and other media that can store program codes.

[0260] For example, the embodiments of the present disclosure may also provide a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by an electronic device, the electronic device implements the data processing method in the aforementioned method embodiment.

[0261] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A recommended method for quick switching, It is characterized in that Applied to electronic equipment, the method comprises: In response to a pull-down operation input by a user, scene information of the electronic device is acquired; the pull-down operation is used to trigger a display control center interface; Inputting the scene information of the electronic device into a trained recommendation model, wherein the trained recommendation model outputs a predicted shortcut switch; Determining a recommended quick switch based on the predicted quick switch, and displaying the recommended quick switch in a recommendation area of ​​the control center interface; In response to a retracting operation input by the user, the interface before the pull-down is displayed.

2. The method according to claim 1, It is characterized in that The step of inputting the scene information of the electronic device into a trained recommendation model, wherein the trained recommendation model outputs a predicted shortcut switch, comprises: When the recommendation model has been trained, the scenario information of the electronic device is input into the trained recommendation model, and the trained recommendation model outputs the predicted shortcut switch.

3. The method according to claim 1 or 2, It is characterized in that Before the retracting operation in response to the user input, the method further includes: Detecting a touch operation input by a user, wherein the touch operation is used to change the state of a shortcut switch in the control center interface; In response to the touch operation, generating behavior data information; the behavior data information includes the name of the shortcut switch; A statistical shortcut switch is generated based on the behavior data information; the statistical shortcut switch is a shortcut switch whose usage frequency exceeds a threshold within a preset period.

4. The method according to claim 3, It is characterized in that The determining the recommended shortcut switch based on the predicted shortcut switch includes: When the number of the predicted shortcut switches is greater than or equal to a first threshold, determining the recommended shortcut switch based on the predicted shortcut switches; When the number of the predicted shortcut switches is equal to a second threshold, determining the recommended shortcut switch based on the statistical shortcut switches; When the number of the predicted shortcut switches is not equal to the second threshold but is smaller than the first threshold, the recommended shortcut switch is determined based on the statistical shortcut switches and the predicted shortcut switches.

5. The method according to claim 3, It is characterized in that Before inputting the scene information of the electronic device into the trained recommendation model, the method further includes: Acquire first scene information, where the first scene information is the scene in which the electronic device is currently located; Encapsulating the first scene information and the behavior data information to obtain encapsulated data; Based on the encapsulated data, training data is obtained, and the training data is used to train the recommendation model.

6. The method according to claim 5, It is characterized in that The obtaining of training data based on the encapsulated data includes: Acquire second scene information, where the second scene information is scene information sent by the always-displayed application; Parsing the encapsulated data to obtain parsed data, wherein the parsed data includes the first scene information and the behavior data information; The first scene information, the behavior data information and the second scene information are encapsulated to obtain the training data.

7. The method according to claim 5 or 6, It is characterized in that After obtaining the training data, the method further includes: The recommendation model is trained using the training data to obtain the trained recommendation model.

8. The method according to claim 1, It is characterized in that After the pull-down operation in response to the user input, the method further includes: When the recommendation model is not trained, the predicted shortcut switch is output based on a plurality of preset shortcut switches.

9. An electronic device, It is characterized in that The electronic device comprises a processor and a memory for storing instructions executable by the processor; when the processor is configured to execute the instructions, the electronic device implements the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having computer program instructions stored thereon; It is characterized in that When the computer program instructions are executed by an electronic device, the electronic device implements the method according to any one of claims 1 to 8.

Images