Content recommendation method and device based on shared gap cloud mobile phone intelligent suspension ball

Abstract

The embodiment of the invention provides a content recommendation method, device and equipment based on a shared gap cloud mobile phone intelligent suspension ball and a computer readable storage medium. The method comprises the following steps: acquiring information of a current application program through a started floating ball; based on the information, judging the security level of the current running application program, and if the security level is greater than a threshold value, performing screenshot operation; uploading a request instruction comprising the intercepted picture and the information to an AI server cluster; the AI server cluster calculates a priority factor in response to the request instruction: selects a target server through the priority factor; and processing the request instruction through the target server to obtain corresponding recommendation content and sending the recommendation content to a client. In this way, the user experience is greatly improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing, and in particular to a content recommendation method, device, equipment and computer-readable storage medium based on a shared Hongmeng cloud phone smart floating ball. Background Art

[0002] The floating ball on the Hongmeng cloud phone currently has no intelligent recognition function, and only provides cloud machine operation functions. At present, AI intelligence is very mature and has a wide range of applications. Similar to the intelligent floating ball on the Android system, most of them are manually triggered by the floating ball, the general page of the floating ball is expanded, and then the additional information required for the corresponding current page is actively triggered or searched. The common game assistant type floating ball trigger also provides full information, and you need to search and filter the information yourself to obtain the complete information currently needed.

[0003] When cloud phone users need to get more recommendations or introductions while using apps or games, they usually don't want to interrupt the current operation. The floating ball is very suitable for use in this scenario, with less interface intrusion and floating close to the edge. The existing floating ball of Hongmeng cloud phone only has some simple operation functions, and similar floating ball functions also require manual information screening and processing. Information acquisition is not direct enough and lacks intelligence. Summary of the invention

[0004] According to an embodiment of the present application, a content recommendation solution based on the shared Hongmeng cloud phone smart floating ball is provided. An AI recognition function is added to the floating ball of the Hongmeng cloud phone APP to automatically identify the current usage scenario of the cloud phone and recommend relevant content for the current scenario. It has features such as cross-application, multi-tasking, and context awareness, which greatly improves the user experience.

[0005] In a first aspect of the present application, a content recommendation method based on a shared Hongmeng cloud mobile phone smart floating ball is provided. The method comprises: Get the information of the current application through the opened floating ball; Based on the information, determine the security level of the currently running application, and if the security level is greater than a threshold, perform a screenshot operation; Uploading the request instruction including the captured image and the information to the AI ​​server cluster; The AI ​​server cluster, in response to the request instruction, calculates the priority factor in the following manner: ; Among them, R1 represents the current GPU computing power level; R2 represents the current server CPU computing power; R3 represents GPU memory usage; R4 represents the server memory usage; R5 indicates GPU utilization; R6 represents CPU usage; Cn represents the complexity of the tasks to be processed in the task queue; M1 represents GPU weight; M2 represents CPU weight; A target server is selected according to the priority factor; the request instruction is processed by the target server to obtain corresponding recommended content and send it to the client.

[0006] In a possible implementation, the information of the application includes: Application name, application version number, version name, and / or application source information.

[0007] In a possible implementation, if the security level is greater than a threshold, performing a screenshot operation includes: If the security level of the current application is greater than the threshold, a screenshot is taken of the current screen to obtain a target image; The complexity of the target image is calculated by the following formula: ; Among them, G(i) is the horizontal complexity; K(j) is the vertical complexity; If the complexity is greater than a second threshold, sending a picture replacement request to the cloud server; The cloud server, in response to the image replacement request, sends a replacement image corresponding to the target image to the client.

[0008] In a possible implementation, the horizontal complexity can be calculated as follows: ; Among them, R r1 Indicates the color richness of the image; R r2 Indicates the degree of color deviation.

[0009] In a possible implementation, the vertical complexity may be calculated as follows: ; Among them, R r1 Indicates the color richness of the image; R r2 Indicates the degree of color deviation.

[0010] In a possible implementation, selecting a target server according to the priority factor includes: Based on the priority factor, calculating the task priority; Based on the task priority, a target server is selected from the AI ​​server cluster.

[0011] In a possible implementation, calculating the task priority based on the priority factor includes: ; in, Indicates the task priority; Represents the priority factor.

[0012] In a second aspect of the present application, a content recommendation device based on a shared Hongmeng cloud mobile phone smart floating ball is provided. The device includes: The acquisition module is used to obtain the information of the current application through the opened floating ball; A determination module, used to determine the security level of the currently running application based on the information, and if the security level is greater than a threshold, perform a screenshot operation; An upload module, used to upload the request instruction including the captured image and the information to the AI ​​server cluster; A calculation module, used for the AI ​​server cluster, calculates the priority factor in response to the request instruction in the following manner: ; Among them, R1 represents the current GPU computing power level; R2 represents the current server CPU computing power; R3 represents GPU memory usage; R4 represents the server memory usage; R5 indicates GPU utilization; R6 represents CPU usage; Cn represents the complexity of the tasks to be processed in the task queue; M1 represents GPU weight; M2 represents CPU weight; The recommendation module is used to select a target server according to the priority factor; process the request instruction through the target server, obtain corresponding recommended content and send it to the client.

[0013] In a third aspect of the present application, an electronic device is provided, which includes a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method described above is implemented.

[0014] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method according to the first aspect of the present application is implemented.

[0015] The content recommendation method based on the shared Hongmeng cloud mobile phone smart floating ball provided in the embodiment of the present application obtains the information of the current application through the turned-on floating ball; based on the information, determines the security level of the currently running application, and if the security level is greater than a threshold, performs a screenshot operation; uploads a request instruction including the captured picture and the information to an AI server cluster; the AI ​​server cluster, in response to the request instruction, calculates the priority factor in the following manner: ; Among them, R1 represents the current GPU computing power level; R2 represents the current server CPU computing power; R3 represents GPU memory usage; R4 represents the server memory usage; R5 indicates GPU utilization; R6 represents CPU usage; Cn represents the complexity of the tasks to be processed in the task queue; M1 represents GPU weight; M2 represents CPU weight; The target server is selected by the priority factor; the request instruction is processed by the target server to obtain the corresponding recommended content and send it to the client, which greatly improves the user experience.

[0016] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein: Figure 1 A system architecture diagram of the method provided in the embodiments of the present application; Figure 2 It is a flowchart of a content recommendation method based on a shared Hongmeng cloud mobile phone smart floating ball according to an embodiment of the present application; Figure 3It is a block diagram of a content recommendation device based on a shared Hongmeng cloud mobile phone smart floating ball according to an embodiment of the present application; Figure 4 It is a schematic diagram of the structure of a terminal device or a server suitable for implementing the embodiments of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0019] In addition, the term "and / or" in this article is only a description of the association relationship between 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. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0020] Figure 1 A schematic diagram of an exemplary operating environment 100 in which the embodiments of the present disclosure can be implemented is shown. The operating environment 100 includes a cloud server 101, a client 102, and an AI server cluster 103.

[0021] Among them, the cloud server 101, in response to the picture replacement request uploaded by the client 102, sends a replacement picture to the client 102; The client 102 is used to obtain a screenshot of the current application and information about the application through a set floating ball; determine the security level of the current application; send a request to the cloud server 101 and / or the AI ​​server cluster 103; and receive data sent by the cloud server 101 and / or the AI ​​server cluster 103; The AI ​​server cluster 103 is used to generate push content in response to the request instruction uploaded by the client 102; and send the recommended content to the client. Compared with a single server, a server cluster can greatly improve the response speed and improve the user experience. That is, when server A fails, server B can be automatically switched, or when server A is under high load, it can also automatically switch to other idle servers.

[0022] Figure 2 A flow chart of a method for content recommendation based on sharing the Hongmeng Cloud mobile phone smart floating ball according to an embodiment of the present disclosure is shown. The method includes: S210, obtaining information of the current application through the turned-on floating ball.

[0023] In some embodiments, the user's operation instruction is obtained through the set (enabled) floating ball. For example, double-click operation, etc. When the floating ball receives the user's instruction, the information of the currently running program is collected; the information includes application name, application version number, version name, startup time, running time and / or application source information.

[0024] S220: Based on the information, determine the security level of the currently running application program, and if the security level is greater than a threshold, perform a screenshot operation.

[0025] In some embodiments, the security level of the currently running application is determined based on the information collected in step S210. That is, it is determined whether the current application is a sensitive application. If the current security level is S4 or S3, the screenshot operation is directly prohibited; if the security level is S2, the user is further asked whether to perform further operations; if the security level is S1, the screenshot operation is performed.

[0026] Security levels can usually be divided as follows: S1: usually refers to some common applications, such as video apps, news apps, mobile game apps, etc.; the video sensitivity index of the above categories is relatively low and can be collected directly; S2: Involving some user's private data, the operation needs to obtain the user's consent before further operation, such as chat tools; S3: usually refers to some financial apps, which involve property data security and are usually prohibited from operation. Only the app name and category, and a few app-related data can be collected; S4: The highest security level. Usually no operations are allowed, mainly through setting up an application whitelist.

[0027] In some embodiments, after taking a screenshot, the complexity of the screenshot can be calculated as follows: The complexity of the target image is calculated by the following formula: ; Among them, G(i) is the horizontal complexity: ; Among them, R r1 Indicates the color richness of the image; R r2 Indicates the degree of color deviation; K(j) is the vertical complexity; ; Furthermore, if the complexity If the value is greater than a second threshold, a request for replacing the image is sent to the cloud server; the second threshold can be preset according to the actual application scenario; The cloud server, in response to the image replacement request, sends a replacement image corresponding to the target image to the client. That is, the client sends an image replacement request to the cloud server, and after receiving the request, the cloud server regenerates the latest screenshot that meets the requirements and sends it back to the client.

[0028] S230, uploading the captured image and the request instruction of the information to the AI ​​server cluster.

[0029] In some embodiments, a request instruction including a captured image (high-definition screenshot) and the information is uploaded to an AI server cluster; the AI ​​server cluster includes multiple AI servers.

[0030] S240, the AI ​​server cluster calculates a priority factor in response to the request instruction.

[0031] In some embodiments, the AI ​​server cluster, in response to the request instruction, may calculate the priority factor in the following manner: ; Among them, R1 represents the current GPU computing power level; R2 represents the current server CPU computing power; R3 represents GPU memory usage; R4 represents the server memory usage; R5 indicates GPU utilization; R6 represents CPU usage; Cn represents the complexity of the tasks to be processed in the task queue; M1 represents GPU weight; M2 represents CPU weight.

[0032] S250, selecting a target server according to the priority factor; processing the request instruction by the target server, obtaining corresponding recommended content and sending it to the client.

[0033] In some embodiments, the task priority of the AI ​​server is calculated by the priority factor: ; in, Indicates the task priority; Represents the priority factor.

[0034] Furthermore, the target server (optimal server) is selected from the AI ​​server cluster in the following way: ; in, Indicates the priority of the AI ​​server. The lower the value, the higher the priority.

[0035] In some embodiments, the screenshot and application information in the request instruction are processed by the target server.

[0036] Specifically, the target server inserts the relevant data into the end of the task queue according to the FIFO (First-In-First-Out) scheduling method. The AI ​​big model in the target server recognizes the image content and combines the application information to determine the current page browsing content, such as the product currently browsed by the user.

[0037] After the recognition is completed, the recognized information will be sent to the algorithm recommendation platform, which will make targeted recommendations on the recognized information and content. If the product that the user is browsing is recognized, the platform can recommend relevant product content and introductions; if the game content that the user is playing is recognized, the platform can recommend relevant game strategy videos; if no relevant content is recognized, the algorithm recommendation platform can randomly recommend some content to the user based on the configured template; the template can be pre-set according to the actual application scenario.

[0038] In some embodiments, the target server sends the pushed content to the client and displays it through a floating ball, such as displaying recommended content such as game strategy video information and / or product content.

[0039] For example, a user plays the mobile game "Honor of Kings" on a cloud phone through a client. When the user double-clicks the floating ball, the AI ​​automatic recognition function is triggered, a screenshot of the current game screen is taken, and the screenshot is sent to the mobile AI cloud server. The mobile AI cloud server takes a screenshot of the current cloud phone screen and combines it with the running application. It identifies the game details such as the game the current user is playing, whether he is in the game, the selected game character, the opponent's game lineup, etc. Then, based on the above game scene details, relevant content is recommended to the user in a targeted manner. For example, if the user is currently playing the game character "Lu Ban", you can recommend "Lu Ban" how to equip the game, the order of skill upgrades, and / or related game character strategy videos.

[0040] According to the embodiments of the present disclosure, the following technical effects are achieved: It can quickly obtain information from the collection page, extract the required resource information, speed up the acquisition of key data, and save users time in obtaining information; Relying on AI intelligence, accurate search and acquisition of key information data can reduce interference from irrelevant data and improve the efficiency of users in obtaining useful information; The main data information is obtained as soon as it is triggered, which reduces the user operation steps, greatly improves the user experience, and increases the user experience satisfaction.

[0041] In summary, through the method disclosed in the present invention, it is possible to intelligently identify the current page content, extract key page data, and provide users with information that may be needed to display the current page content. The intelligent capabilities of the Hongmeng cloud phone floating ball have been increased, reducing the need for users to obtain relevant information or operating methods from other places when they are not familiar with the page content. At the same time, the intelligent recognition capabilities disclosed in the present invention take into account performance, network, resource conditions, etc., to avoid the phenomenon of client or cloud phone service freezes caused by consuming a large amount of resources, and have the characteristics of improving the user experience of cloud phone products and increasing operational convenience, which greatly improves the user experience.

[0042] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0043] The above is an introduction to the method embodiment. The following is a further explanation of the scheme described in this application through an apparatus embodiment.

[0044] Figure 3 A block diagram of a content recommendation device based on a shared Hongmeng cloud mobile phone smart floating ball according to an embodiment of the present application is shown, Figure 3 Shown include: The acquisition module 310 is used to acquire information of the current application through the opened floating ball; A determination module 320, configured to determine the security level of the currently running application based on the information, and to perform a screenshot operation if the security level is greater than a threshold; An uploading module 330, for uploading a request instruction including the captured image and the information to the AI ​​server cluster; The calculation module 340, used in the AI ​​server cluster, calculates the priority factor in response to the request instruction in the following manner: ; Among them, R1 represents the current GPU computing power level; R2 represents the current server CPU computing power; R3 represents GPU memory usage; R4 represents the server memory usage; R5 indicates GPU utilization; R6 represents CPU usage; Cn represents the complexity of the tasks to be processed in the task queue; M1 represents GPU weight; M2 represents CPU weight; The recommendation module 350 is used to select a target server according to the priority factor; process the request instruction through the target server, obtain corresponding recommended content and send it to the client.

[0045] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0046] Figure 4 A schematic diagram of the structure of a terminal device or server suitable for implementing an embodiment of the present application is shown.

[0047] like Figure 4 As shown, the terminal device or server includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 into the random access memory (RAM) 403. In RAM403, various programs and data required for the operation of the terminal device or server are also stored. CPU401, ROM 402 and RAM403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0048] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.

[0049] In particular, according to an embodiment of the present application, the above method flow steps can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a machine-readable medium, and the computer program includes a program code for executing the method shown in the flow chart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the above-mentioned functions defined in the system of the present application are executed.

[0050] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0051] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of the code, and the aforementioned module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0052] The units or modules involved in the embodiments described in the present application may be implemented by software or hardware. The units or modules described may also be arranged in a processor. The names of these units or modules do not, in some cases, constitute limitations on the units or modules themselves.

[0053] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable storage medium stores one or more programs, and when the above programs are used by one or more processors to execute the method described in the present application.

[0054] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of application involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned application concept. For example, the above features are replaced with (but not limited to) technical features with similar functions applied in the present application.

Claims

1. A content recommendation method based on sharing Hongmeng cloud mobile phone intelligent floating ball, characterized in that: include: Get the information of the current application through the opened floating ball; Based on the information, determine the security level of the currently running application, and if the security level is greater than a threshold, perform a screenshot operation; Uploading the request instruction including the captured image and the information to the AI ​​server cluster; The AI ​​server cluster, in response to the request instruction, calculates the priority factor in the following manner: ； Among them, R1 represents the current GPU computing power level; R2 represents the current server CPU computing power; R3 represents GPU memory usage; R4 represents the server memory usage; R5 indicates GPU utilization; R6 represents CPU usage; Cn represents the complexity of the tasks to be processed in the task queue; M1 represents GPU weight; M2 represents CPU weight; A target server is selected according to the priority factor; the request instruction is processed by the target server to obtain corresponding recommended content and send it to the client.

2. The method according to claim 1, characterized in that The application information includes: Application name, application version number, version name, and / or application source information.

3. The method according to claim 1, characterized in that If the security level is greater than a threshold, performing a screenshot operation includes: If the security level of the current application is greater than the threshold, a screenshot is taken of the current screen to obtain a target image; The complexity of the target image is calculated by the following formula: ； Among them, G(i) is the horizontal complexity; K(j) is the vertical complexity; If the complexity is greater than a second threshold, sending a picture replacement request to the cloud server; The cloud server, in response to the image replacement request, sends a replacement image corresponding to the target image to the client.

4. The method according to claim 3, characterized in that: The horizontal complexity can be calculated as follows: ； Among them, R r1 Indicates the color richness of the image; R r2 Indicates the degree of color deviation.

5. The method according to claim 4, characterized in that The vertical complexity can be calculated as follows: ； Among them, R r1 Indicates the color richness of the image; R r2 Indicates the degree of color deviation.

6. The method according to claim 5, characterized in that The selecting a target server according to the priority factor comprises: Based on the priority factor, calculating the task priority; Based on the task priority, a target server is selected from the AI ​​server cluster.

7. The method according to claim 6, characterized in that The calculating task priority based on the priority factor includes: ； in, Indicates the task priority; Represents the priority factor.

8. A content recommendation device based on a shared Hongmeng cloud mobile phone intelligent floating ball, characterized in that: include: The acquisition module is used to obtain the information of the current application through the opened floating ball; A determination module, used to determine the security level of the currently running application based on the information, and if the security level is greater than a threshold, perform a screenshot operation; An upload module, used to upload the request instruction including the captured image and the information to the AI ​​server cluster; A calculation module, used for the AI ​​server cluster, calculates the priority factor in response to the request instruction in the following manner: ； Among them, R1 represents the current GPU computing power level; R2 represents the current server CPU computing power; R3 represents GPU memory usage; R4 represents the server memory usage; R5 indicates GPU utilization; R6 represents CPU usage; Cn represents the complexity of the tasks to be processed in the task queue; M1 represents GPU weight; M2 represents CPU weight; The recommendation module is used to select a target server according to the priority factor; process the request instruction through the target server, obtain corresponding recommended content and send it to the client.

9. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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