Content recommendation method and electronic device

Abstract

This application provides a content recommendation method and electronic device, relating to the field of computer technology. It accurately obtains recommended content that meets user needs, achieving personalized recommendations and improving user experience. In this method, the electronic device receives a first instruction to retrieve information and obtains content recommendation suggestions from a server. The content recommendation suggestions indicate at least one of the following: the source of the information, the content of the information, or the reference factors used when recommending information. Then, based on the content recommendation suggestions, the electronic device obtains first data, which is generated based on memory information stored on the electronic device. Based on the first data and the content recommendation suggestions, the electronic device retrieves and displays the recommended content in response to the first instruction by calling an application.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more particularly to a content recommendation method and electronic device. Background Technology

[0002] Voice assistants can interact with users, receive voice commands from users, and send the voice commands to the server. The server determines the operation or content that the user wants to obtain based on the voice command and sends the information to the voice assistant. The voice assistant then performs the operation or provides the content that the user needs based on the information sent by the server.

[0003] For example, a user can ask the voice assistant, "Do you have any recommendations for clothes?" The voice assistant will then provide recommendations and suggestions based on the information sent by the server, such as recommendations for sun-protective clothing, women's clothing brands, shops to avoid buying from, and men's clothing brands.

[0004] However, while voice assistants can provide some content to users, this content often has a low degree of matching with users' actual needs, making it difficult to meet users' needs and thus affecting the user experience. Summary of the Invention

[0005] This application provides a content recommendation method and electronic device that can more accurately obtain recommended content that meets user needs, achieve the purpose of personalized recommendations for users, and improve the user experience.

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] Firstly, a content recommendation method is provided, applied to an electronic device. In this method, the electronic device receives a first instruction input by a user, wherein the first instruction indicates information requested by the user. Then, the electronic device sends a first request to a server, wherein the first request indicates the request for content recommendation suggestions. The electronic device receives content recommendation suggestions sent by the server, wherein the content recommendation suggestions indicate at least one of the following: the source of the information, the content of the information, or the reference factors used when recommending the information. Next, the electronic device obtains first data based on the content recommendation suggestions, wherein the first data is generated based on memory information stored on the electronic device. Based on the first data and the content recommendation suggestions, the electronic device obtains recommended content by invoking an application, wherein the recommended content is used in response to the first instruction. Finally, the electronic device displays the recommended content.

[0008] In the above method, the first data is generated based on memory information. The memory information on electronic devices has a wide range of sources and can comprehensively reflect the user's characteristics, preferences and habits of using electronic devices and / or applications. Therefore, based on the first data, the electronic device can also more accurately obtain recommended content that meets the user's needs, achieve the purpose of personalized recommendations for users, and improve the user experience.

[0009] In one possible implementation of the first aspect, the electronic device invokes multiple applications, each of which retrieves recommended content.

[0010] In the above implementation, recommended content can be obtained from multiple applications, enabling cross-application content recommendation. This allows users to view or select more recommended content, improving the user's interactive experience.

[0011] In one possible implementation of the first aspect, there are multiple recommended contents, including displaying recommended contents based on the user's usage of the application.

[0012] For example, user usage of an application may include at least one of the following: duration of application use, frequency of application use, number of times the application is used, or content viewed within the application.

[0013] In the above implementation, user behavior regarding the application can reflect their preferences and usage habits. In other words, when displaying multiple recommendations, the selection can be based on the user's preferences and usage habits with the application providing the recommendations, resulting in a better user experience.

[0014] In one possible implementation of the first aspect, a user can wake up the voice assistant and input a first command while the electronic device is displaying any page. The page displayed on the electronic device can be a desktop, an application page, a system page displayed in response to the user's action, etc.

[0015] For example, in response to a user's search for content in a first image, the electronic device displays at least one search result related to the content in the first image, wherein the at least one search result comes from the same application or different applications of the electronic device. The first instruction instructs the user to request information related to the first image. In this way, after obtaining search results through image search, the user can continue to input the first instruction regarding the search results or search content to further obtain recommended content.

[0016] In the above implementation, users can wake up the voice assistant in various scenarios and interact with it, demonstrating the real-time nature of the interaction and providing users with a better interactive experience.

[0017] In one possible implementation of the first aspect, the electronic device obtains first data based on content recommendation suggestions, provided that the user authorizes the use of the memory information.

[0018] In the above implementation, with user authorization, the electronic device obtains the initial data based on content recommendations. This ensures the security of data and application data on the electronic device.

[0019] In one possible implementation of the first aspect, when the first instruction is used to instruct the user to request information for the user, the first data to be obtained includes the user's usage of the shopping application and first information, which includes user identity information and / or the user's current scenario.

[0020] In the above implementation, when a user uses an electronic device to obtain recommended content for themselves, the electronic device can obtain the user's usage of the shopping application based on the information it has stored, as well as the user's identity information and / or the user's current scenario. This information better reflects the user's preferences, usage habits, and needs. Subsequently, based on the first data, it can obtain recommended content that is more in line with the user's preferences, usage habits, and needs, thus bringing a better interactive experience to the user.

[0021] In one possible implementation of the first aspect, when the first instruction is used to instruct a user to request information for another user who is not the user, the first data to be obtained includes the user's usage of the shopping application and second information, the second information including the other user's identity information and / or the other user's needs.

[0022] In the above implementation, when a user uses an electronic device to obtain recommended content for other users, the electronic device can obtain the user's usage of the shopping application based on the memory information, as well as the identity information of other users and / or the needs of other users. This content can better reflect the user's and other users' preferences, usage habits, and needs. Subsequently, based on the first data, it can also obtain recommended content that is more in line with the user's and other users' preferences, usage habits, and needs, bringing a better interactive experience to the user.

[0023] In one possible implementation of the first aspect, the above content recommendation method can be applied to various scenarios, such as shopping, ordering food, and booking tickets.

[0024] In a shopping scenario, the application is a shopping app, and the content recommendation suggestions indicate at least one of the following factors when recommending products: style, material, color, size, and personal preferences.

[0025] In a shopping scenario, the application is a shopping app, and the recommended content includes at least one of the following: product display images, brief product descriptions, product prices, application information providing the product, and store information providing the product.

[0026] In one possible implementation of the first aspect, when the electronic device displays recommended content, it also displays a process of analyzing the content and making recommendations.

[0027] In the above implementation method, the analysis process can be displayed in real time while the electronic device is acquiring recommended content, so that users can more intuitively understand the process of acquiring recommended content and improve the user experience.

[0028] Secondly, a content recommendation method is provided, applied to a communication system, which includes electronic devices and servers. In this method,

[0029] The electronic device receives a first instruction input by the user; wherein the first instruction is used to indicate the information requested by the user.

[0030] The electronic device sends a first request to the server; wherein the first request is used to instruct the user to obtain content recommendation suggestions;

[0031] The server receives the first request and obtains content recommendation suggestions; it then sends the content recommendation suggestions to the electronic device; wherein the content recommendation suggestions are used to indicate at least one of the following: the source of the information, the content of the information, or the reference factors when recommending information;

[0032] The electronic device receives content recommendation suggestions sent by the server and obtains first data based on the content recommendation suggestions; wherein, the first data is generated based on the memory information on the electronic device;

[0033] The electronic device obtains recommended content by calling an application based on the first data and content recommendation suggestions; wherein the recommended content is used to respond to the first instruction;

[0034] Electronic devices display recommended content.

[0035] Thirdly, a communication system is provided, including electronic devices and a server; wherein,

[0036] An electronic device for performing the content recommendation method as described in the first aspect and any of its implementable embodiments;

[0037] The server is used to receive the first request and obtain content recommendation suggestions; it then sends content recommendation suggestions to electronic devices.

[0038] Fourthly, an electronic device is provided, including a memory and one or more processors; the memory is coupled to the processors; wherein the memory stores computer program code, the computer program code including computer instructions, which, when executed by the processor, cause the electronic device to perform the content recommendation method as described in the first aspect and any of its implementable embodiments.

[0039] Fifthly, a computer-readable storage medium is provided, including computer instructions that, when executed on an electronic device, cause the electronic device to perform the content recommendation method as described in the first aspect and any of its implementable embodiments.

[0040] In a sixth aspect, a computer program product is provided that, when run on a computer, causes the computer to perform the content recommendation method as described in the first aspect and any of its implementable embodiments.

[0041] The beneficial effects that can be achieved by the content recommendation method provided in the second aspect, the communication system provided in the third aspect, the electronic device provided in the fourth aspect, the computer-readable storage medium provided in the fifth aspect, and the computer program product provided in the sixth aspect can refer to the beneficial effects that can be achieved by the first aspect and any of its implementation methods, and will not be repeated here. Attached Figure Description

[0042] Figure 1 A schematic diagram of the communication system provided in the embodiments of this application;

[0043] Figure 2 Schematic diagram of the structure of the electronic device provided in the embodiments of this application Figure 1 ;

[0044] Figure 3 Schematic diagram of the structure of the electronic device provided in the embodiments of this application Figure 2 ;

[0045] Figure 4 This is a schematic diagram illustrating the interaction between an electronic device and a server provided in an embodiment of this application;

[0046] Figure 5 A flowchart illustrating the content recommendation method provided in this application embodiment;

[0047] Figure 6 A schematic diagram illustrating the acquisition of voice commands provided in an embodiment of this application;

[0048] Figure 7 A schematic diagram of the server processing flow provided in the embodiments of this application;

[0049] Figure 8 A schematic diagram of the recommended content provided for the embodiments of this application. Figure 1 ;

[0050] Figure 9 A schematic diagram of the recommended content provided for the embodiments of this application. Figure 2 ;

[0051] Figure 10 A schematic diagram illustrating the analysis process provided in an embodiment of this application;

[0052] Figure 11 A schematic diagram of the terminal-side processing flow provided in an embodiment of this application;

[0053] Figure 12 Schematic diagram of the structure of the electronic device provided in the embodiments of this application Figure 3 . Detailed Implementation

[0054] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. In the description of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single 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, and c can be single or multiple. Furthermore, to facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" are not necessarily different. Meanwhile, in the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for ease of understanding.

[0055] Furthermore, the business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0056] Traditional voice assistants can meet users' question-and-answer needs in various aspects. Taking shopping as an example, after receiving a user's inquiry, the voice assistant mainly relies on server big data and user profiles to obtain recommendations. While this method can provide recommendations, it often proves inaccurate when dealing with complex and personalized needs. For instance, if a user has recently been frequently searching for cameras on their phone, and has spent a significant amount of time searching or browsing for cameras they like, they might want the voice assistant to recommend cameras that include basic parameters and also those that interest them. However, in reality, the voice assistant can only simply recommend basic camera parameters and cannot provide more advanced, personalized product recommendations based on the user's behavior on their phone.

[0057] For example, users frequently search for or browse clothes on their phones, and they tend to search for or browse clothes they like more often. When users select clothes through a voice assistant, they might want the voice assistant to recommend comfortable clothing types and materials suitable for the current season, as well as clothes they personally prefer. However, in reality, the voice assistant can only simply recommend clothing types and materials, and cannot provide more advanced, personalized product recommendations based on the user's behavior on their phone.

[0058] It is evident that when users interact with traditional voice assistants, the recommended content provided by the voice assistant may not necessarily match the user's actual needs, or may be difficult to meet the user's needs. This not only affects the user experience, but may also reduce the user's trust in the voice assistant.

[0059] However, this content often has a low degree of relevance to users' actual needs, making it difficult to meet those needs and thus affecting the user experience.

[0060] Based on the above, this application provides a content recommendation method. In this method, the voice assistant can obtain preliminary recommendation suggestions from the server according to the user's instructions. Then, based on the recommendation suggestions, it obtains some data provided by the electronic device where the voice assistant is located, which can represent the user's habits, behaviors, and preferences. Finally, the voice assistant recommends more personalized content to the user based on this data.

[0061] For example, taking the above content recommendation method applied to an electronic device, the electronic device receives a first instruction input by a user, wherein the first instruction is used to indicate the information requested by the user. The electronic device sends a first request, wherein the first request is used to indicate the request for content recommendation suggestions. Then, the electronic device receives content recommendation suggestions sent by a server, wherein the content recommendation suggestions are used to indicate at least one of the following: the source of the information, the content of the information, or the reference factors when recommending information. Next, the electronic device obtains first data based on the content recommendation suggestions, and obtains recommended content by calling an application based on the first data and the content recommendation suggestions, wherein the first data is generated based on memory information on the electronic device, and the recommended content is used in response to the first instruction. Finally, the electronic device displays the recommended content.

[0062] In the above method, the first data is generated based on memory information. The memory information on electronic devices has a wide range of sources and can comprehensively reflect the user's characteristics, preferences and habits of using electronic devices and / or applications. Therefore, based on the first data, the electronic device can also more accurately obtain recommended content that meets the user's needs, achieve the purpose of personalized recommendations for users, and improve the user experience.

[0063] The above method can be applied to communication systems. In some embodiments, see [link to relevant documentation]. Figure 1 As shown, the communication system can consist of an electronic device 100 and a server 200. The electronic device 100 can receive user commands and send a request to the server 200 to obtain content recommendation suggestions. The server 200 obtains the content recommendation suggestions based on the request. The server 200 then sends the content recommendation suggestions back to the electronic device 100, which retrieves the first data from its local storage or stored memory based on the content recommendation suggestions. The electronic device 100 then uses the first data and the content recommendation suggestions to retrieve recommended content in response to the user command by calling an application and displays the recommended content.

[0064] Among them, memory information refers to at least one of the following contents stored on electronic device 100: user behavior data, application data, images captured by camera, sounds captured by microphone, etc.

[0065] The above method can be applied to various content recommendation scenarios to enable question-and-answer interactions between users and the voice assistant on electronic devices. These applicable scenarios include shopping, ordering food, and booking tickets.

[0066] Taking a shopping scenario as an example, a user's instruction might be something like, "Recommend a summer dress for me." After receiving the request from the electronic device 100, the server 200 can provide relatively traditional and basic content recommendation suggestions, such as "Common considerations for choosing a summer dress." These considerations might specifically point out factors such as size, color, style, and user preferences. It's understandable that this content recommendation suggestion can indicate at least one of the following: the source of the information, the content of the information, or the factors considered when recommending the information. For example, by obtaining application data from a photo album application or a shopping application, the electronic device 100 can determine the user's body shape, appearance, height, age, weight, and other identity information, thereby determining the size and color of the dress to recommend; and also determining the user's preferences, thus determining the style and design of the dress to recommend. After determining the size, color, style, and other information of the dress recommended to the user, the electronic device 100 then obtains relevant dress display images, brief descriptions, prices, application information, and store information from at least one shopping application of the electronic device 100, and displays this information to the user as recommended content based on the user's instructions.

[0067] In some embodiments, see Figure 2 As shown, the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a microphone 170C, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc.

[0068] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the electronic device 100. In other embodiments of this application, the electronic device 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements.

[0069] Processor 110 may include one or more processing units, such as: application processor (AP), modem processor, graphics processing unit (GPU), image signal processor (ISP), controller, memory, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0070] In some possible application scenarios, the electronic device 100 can implement the content recommendation method provided in the embodiments of this application through the processor 110 described above.

[0071] USB port 130 is a USB standard compliant interface, specifically a Mini USB port, Micro USB port, USB Type-C port, etc. USB port 130 can be used to connect a charger to charge electronic device 100, and can also be used for data transfer between electronic device 100 and peripheral devices. It can also be used to connect headphones for audio playback. This interface can also be used to connect other electronic devices, such as AR devices.

[0072] The charging management module 140 receives charging input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 receives charging input from the wired charger via the USB interface 130. In some wireless charging embodiments, the charging management module 140 receives wireless charging input via the wireless charging coil of the electronic device 100. While charging the battery 142, the charging management module 140 can also supply power to the electronic device via the power management module 141.

[0073] The power management module 141 connects the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, providing power to the processor 110, internal memory 121, external memory, display screen 194, camera 193, and wireless communication module 160, etc. The power management module 141 can also monitor parameters such as battery capacity, battery cycle count, and battery health status (leakage current, impedance). In some other embodiments, the power management module 141 may also be located within the processor 110. In other embodiments, the power management module 141 and the charging management module 140 may be located in the same device.

[0074] The wireless communication function of electronic device 100 can be realized through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor, etc.

[0075] Electronic device 100 implements display functions through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations and for graphics rendering. Processor 110 may include one or more GPUs, which execute program instructions to generate or modify display information.

[0076] The display screen (or screen) 194 is used to display images, videos, etc. In some embodiments, the electronic device 100 may include one or N display screens 194, where N is a positive integer greater than 1.

[0077] In some possible application scenarios, the display screen 194 can display the recommended content obtained by the processor 110 when executing the above-described content recommendation method to the user.

[0078] Electronic device 100 can perform shooting functions through ISP, camera 193, video codec, GPU, display 194 and application processor.

[0079] The ISP (Image Signal Processor) is used to process data fed back from the camera 193. For example, when taking a picture, the shutter is opened, and light is transmitted through the lens to the camera's photosensitive element. The light signal is converted into an electrical signal, and the camera's photosensitive element transmits the electrical signal to the ISP for processing, transforming it into an image visible to the naked eye. The ISP can also perform algorithmic optimization of image noise, brightness, and skin tone. The ISP can also optimize parameters such as exposure and color temperature of the shooting scene. In some embodiments, the ISP can be set in the camera 193.

[0080] Camera 193 is used to capture still images or videos. An object is projected onto a photosensitive element by generating an optical image through the lens. The photosensitive element can be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, which is then passed to an ISP for conversion into a digital image signal. The ISP outputs the digital image signal to a DSP for processing. The DSP converts the digital image signal into image signals in standard RGB, YUV, or other formats. In some embodiments, the electronic device 100 may include one or N cameras 193, where N is a positive integer greater than 1.

[0081] In some possible application scenarios, camera 193 can be either a front-facing camera or a rear-facing camera. After the user issues a command to electronic device 100, the front-facing or rear-facing camera can capture an image. Subsequently, processor 110 obtains the image captured by the camera based on content recommendation suggestions sent by the server. Alternatively, after electronic device 100 receives content recommendation suggestions sent by the server, the front-facing or rear-facing camera can capture an image. The captured image, as the first data obtained by processor 110, can be used to determine user information, environmental information of electronic device 100, etc. Subsequently, processor 110 can also combine user information, environmental information, etc., to obtain recommended content that meets user needs.

[0082] Digital signal processors (DSPs) are used to process digital signals. Besides digital image signals, they can also process other digital signals. For example, when electronic device 100 selects a frequency, the DSP can perform Fourier transforms on the frequency energy.

[0083] The external storage interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 110 through the external storage interface 120 to perform data storage functions. For example, music, video, and other files can be saved on the external memory card.

[0084] Internal memory 121 can be used to store computer executable program code, which includes instructions. Processor 110 executes various functional applications and data processing of electronic device 100 by running the instructions stored in internal memory 121. Internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback, image playback, etc.), etc. The data storage area may store data created during the use of electronic device 100 (such as audio data, phonebook, etc.). Furthermore, internal memory 121 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc.

[0085] Electronic device 100 can implement audio functions, such as music playback and recording, through audio module 170 and application processor.

[0086] The audio module 170 is used to convert digital audio information into analog audio signals for output, and also to convert analog audio input into digital audio signals. The audio module 170 can also be used for encoding and decoding audio signals. In some embodiments, the audio module 170 may be located in the processor 110, or some functional modules of the audio module 170 may be located in the processor 110.

[0087] The audio module 170 may include a microphone 170C. The microphone 170C, also called a "microphone" or "voice transducer," is used to convert sound signals into electrical signals. When making a phone call or sending a voice message, the user can speak by bringing their mouth close to the microphone 170C, inputting the sound signal into the microphone 170C. The electronic device 100 may have at least one microphone 170C. In some embodiments, the electronic device 100 may have two microphones 170C, which, in addition to collecting sound signals, can also perform noise reduction. In other embodiments, the electronic device 100 may also have three, four, or more microphones 170C, enabling sound signal collection, noise reduction, sound source identification, and directional recording, among other functions.

[0088] In some potential application scenarios, after a user issues a command to the electronic device 100, the microphone 170C can collect sound. Then, the processor 110 obtains the sound collected by the microphone based on content recommendations sent by the server. Alternatively, the microphone 170C can collect sound after the electronic device 100 receives content recommendations from the server. The collected sound, as the first data obtained by the processor 110, can be used to determine user information, environmental information of the electronic device 100, etc. Subsequently, the processor 110 can also combine user information, environmental information, etc., to obtain recommended content that meets the user's needs.

[0089] Buttons 190 include a power button, volume buttons, etc. A motor 191 can generate vibration feedback. An indicator 192 can be an indicator light, used to indicate charging status, battery level changes, and also to indicate messages, missed calls, notifications, etc. A SIM card interface 195 is used to connect a SIM card.

[0090] In some possible application scenarios, in addition to the images captured by the camera and the sounds captured by the microphone, user behavior data and application data on the electronic device 100 can also be used to obtain recommended content that meets user needs.

[0091] The electronic device 100 contains at least one application, which can be a third-party application or a non-third-party application. User activity information within the application, such as browsed content, searched content, duration of browsing, number of searches, and user comments, can all be included in the application data. Alternatively, content saved within the application can also be included in the application data. Examples include content saved in a memo application, user-set schedules, reminders, etc., stored in a calendar application, images and videos saved in a photo album application, user body information and health data saved in a health application, and user's historical input content saved in an input method application.

[0092] In addition, user behavior data on electronic device 100 may include user account information for logging into electronic device 100, duration of user use of various applications, number of times of use of various applications, and time periods of use of various applications.

[0093] The processor 110 can obtain a basic user profile based on images captured by the camera, sounds captured by the microphone, and user account information, as well as identify the user's current scene, environment, and location, thereby providing a comprehensive user profile and facilitating the understanding of user needs. The processor 110 can also collect more granular information about the user based on behavioral data and application data from the electronic device 100, making it easier to determine the user's usage habits, preferences, and needs.

[0094] Understandably, the processor 110 can obtain recommended content based on any one of the following: images captured by the camera, sounds captured by the microphone, user behavior data on the electronic device 100, and application data. Alternatively, it can combine recommended content obtained from at least two of these sources. The more data combined, the more accurate and user-friendly the recommended content will be, thereby achieving the goal of personalized recommendations and improving the user experience.

[0095] The electronic device provided in this application embodiment can run an operating system (OS). This operating system can be various operating systems used in the industry, such as an operating system based on OpenHarmony, like HarmonyOS; or other operating systems such as Android. TM An operating system can refer to the iOS mobile operating system; it can also refer to various open-source operating systems or their derivatives, such as Linux OS and other embedded operating systems; or it can refer to future new operating systems, such as AI operating systems based on artificial intelligence. An operating system is a set of interconnected system software programs that manage and control the operation of electronic devices, utilize and run hardware and software resources, and provide public services to organize user interactions. In electronic devices, the operating system connects downwards to the physical devices at the hardware layer and upwards to provide a runtime environment for application software.

[0096] An operating system typically includes a kernel layer, a middleware layer, and an application layer. The application layer includes applications, which can include system applications and third-party applications. The middleware layer includes a suite of software providing various services to application developers, or frameworks providing services such as databases, multimedia, and graphics, or capabilities such as distributed scheduling and system scaling. For example, the middleware layer may include a framework layer and / or a system service layer. The framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer. The system service layer includes the system's core capabilities, providing services to applications through the framework layer. The kernel layer is the layer between hardware and software. The kernel layer may include hardware drivers and the operating system kernel. In addition to providing hardware drivers, the kernel layer also supports functions such as memory management and system process management.

[0097] The electronic devices we use in our daily lives come in various types and forms, and are applied in a wide range of scenarios. Therefore, based on the different forms and functions of electronic devices, different application scenarios, and different user needs, the operating systems used in these devices may also differ. The basic functions implemented by the electronic device provided in this application can be implemented using a general-purpose operating system or a dedicated operating system. To more clearly illustrate the implementation of the embodiments of this application under a specific operating system, the architecture of HarmonyOS is shown below. Those skilled in the art can deduce the implementation of the embodiments of this application under other specific operating systems, such as Android. TM Implementation under operating systems, etc.

[0098] The software architecture of an electronic device can be divided into several layers. In some embodiments, see [link to documentation]. Figure 3 As shown, from bottom to top, the layers are: kernel layer, system service layer, framework layer, and application layer. Layers communicate with each other through software interfaces. System functions can be tailored, added, or combined at the subsystem level depending on the deployment scenario of different device types, and each subsystem can also be tailored, added, or combined at the functional level.

[0099] The kernel layer includes the kernel abstraction layer, the kernel subsystem, and the driver subsystem.

[0100] The kernel abstract layer (KAL) provides basic kernel capabilities to upper layers by shielding the differences between multiple kernels, including but not limited to process / thread management, memory management, file system, network management, and peripheral device management.

[0101] The kernel subsystem supports selecting a suitable OS kernel for different resource-constrained devices, including but not limited to Linux kernel, HarmonyOS kernel, LiteOS (Lite Operating System), etc.

[0102] The driver framework within the driver subsystem forms the foundation for an open system hardware ecosystem, providing unified peripheral access capabilities and a framework for driver development and management. The driver framework includes: display drivers, camera drivers, audio drivers, Bluetooth drivers, sensor drivers, etc.

[0103] The system service layer comprises the core capabilities of the system, providing services to applications through the framework layer. This layer includes, but is not limited to, the following subsystems:

[0104] The system's basic capability subsystem set provides fundamental capabilities for the operation, scheduling, and migration of distributed applications across multiple devices. This set may include distributed soft bus, distributed data management, distributed task scheduling, and Ark multi-language runtime; it may also include multi-modal input subsystem, graphics subsystem, security subsystem, and AI business subsystem.

[0105] Basic software service subsystem set: provides public and general software services; the basic software service subsystem set may include event notification subsystem, telephone service subsystem, multimedia subsystem, etc.

[0106] Enhanced software service subsystem suite: Provides differentiated enhanced software services for different devices; the enhanced software service subsystem suite may include smart screen proprietary business subsystem, wearable proprietary business subsystem, IoT proprietary business subsystem, etc.

[0107] Hardware service subsystem set: Provides hardware services; the hardware service subsystem set may include location service subsystem, unified identity and access management (IAM) subsystem, wearable proprietary hardware service subsystem, biometric identification, IoT proprietary hardware service subsystem, etc.

[0108] Distributed task scheduling enables distributed service management (discovery, synchronization, registration, and invocation), supporting remote startup, remote invocation, remote connection, and migration of applications across devices.

[0109] Distributed data management enables data synchronization, data storage, data sharing, and data access across all scenarios and devices.

[0110] The distributed soft bus provides communication-related capabilities for seamless interconnection between multiple devices, including: WLAN service capabilities, Bluetooth service capabilities, soft bus, inter-process communication RPC (Remote Procedure Call), and StarFlash communication capabilities.

[0111] Ark Multilingual Runtime is a unified compilation runtime platform designed to support the joint compilation and execution of multiple programming languages ​​and multiple chip platforms.

[0112] The framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer. The framework layer includes: the ArkUI framework (which provides a complete infrastructure for UI development of system applications, including UI functions such as components, layouts, animations, and interactive events, as well as a real-time interface preview tool), the user application framework, and the Ability framework (an Ability is a lightweight application; the Ability framework schedules and manages the operation and lifecycle of Abilities). Different devices may have different operating systems, and the APIs they support may also differ.

[0113] The HarmonyOS API is a series of open capabilities provided to support HarmonyOS application development. The HarmonyOS API can be set at the framework layer or independently of the framework layer. The HarmonyOS API includes the Audio API (audio service), Push API (push service), and Account API (account service), among others.

[0114] Applications in the application layer can include system applications and extended / third-party applications. System applications can include the desktop, control bar, settings, contacts, phone, camera, etc., while extended / third-party applications can include social applications, travel applications, etc.

[0115] In some embodiments, the electronic device may include an edge-side image module, an edge-side memory module, and a voice assistant module.

[0116] The voice assistant module receives user commands, sends requests to the server, and retrieves memory information from the device-side profiling module and device-side memory module based on content recommendation suggestions sent by the server, generating first data. Alternatively, after receiving user commands, the voice assistant can retrieve memory information from the device-side profiling module and device-side memory module, and generate first data based on the content recommendation suggestions sent by the server. Then, the voice assistant module can use the first data and content recommendation suggestions to invoke the application of the electronic device 100 to obtain recommended content and control the display screen to show the recommended content.

[0117] The edge profiling module is used to acquire images captured by the camera, sounds captured by the microphone, user account information, etc., to determine the user's profile, the scene the user is in, the environment the user is in, and the location the user is in. Among them, the user's basic profile is used to describe the user, or the user's basic profile can also represent the user's identity information. The basic profile can reflect the user's appearance, body shape, age, weight, etc.

[0118] The edge memory module is used to acquire user behavior data on the electronic device 100, application data of applications on the electronic device 100 (such as photo album, memo, input method, sports and health, etc.), so as to collect more granular information from the user.

[0119] It is understood that, in the embodiments of this application, the process of the electronic device 100 generating the first data is performed under the authorization or permission of the user to use the memory information. For example, the user authorizes the electronic device 100 to provide user behavior data, authorizes the application on the electronic device 100 to provide application data, authorizes the camera to provide captured images, authorizes the microphone to provide captured sounds, etc.

[0120] It is understood that, in this embodiment of the application, the process of the electronic device 100 obtaining recommended content from the application is also carried out with the user's authorization or permission. When the user authorizes the application to provide recommended content, the application on the electronic device 100 can also register a preset instruction format, such as a schema, which facilitates the electronic device 100 in obtaining recommended content from the application. For example, after understanding or analyzing the user's needs based on the first data, the electronic device 100 generates a content retrieval instruction in a preset instruction format related to the needs, and sends the content retrieval instruction to at least one application on the electronic device 100. Upon receiving the content retrieval instruction, the application provides recommended content to the electronic device 100.

[0121] For example, see Figure 4 As shown, the electronic device mainly implements the following processes: receiving user input commands, sending requests to the server, receiving content recommendation suggestions from the server, obtaining first data based on the content recommendation suggestions, and obtaining recommended content from the application based on the first data and the content recommendation suggestions. The first data can be generated based on the memory information in the aforementioned device-side profiling module and device-side memory module. Furthermore, if the electronic device obtains multiple recommended content items, it can sort and display the recommended content according to the user's preferences and needs, thereby achieving personalized recommendations.

[0122] See Figure 4 As shown, the server mainly implements the process of receiving requests sent by electronic devices, obtaining content recommendation suggestions, and sending content recommendation suggestions to electronic devices.

[0123] Based on the above, it can be seen that in the content recommendation method provided in this application embodiment, the first data is generated based on memory information. The memory information on electronic devices has a wide range of sources and can comprehensively reflect the user's characteristics, user's preferences and habits in using electronic devices and / or applications. Therefore, based on the first data, the electronic device can also more accurately obtain recommended content that meets the user's needs, achieve the purpose of personalized recommendations for users, and improve the user experience.

[0124] It is understood that the electronic device in the embodiments of this application may be a mobile phone, tablet computer, smartwatch, smart TV, vehicle terminal, handheld computer, laptop computer, ultra-mobile personal computer (UMPC), netbook, as well as cellular phone, personal digital assistant (PDA), augmented reality (AR) / virtual reality (VR) device, etc. The embodiments of this application do not impose any special restrictions on the specific form of the electronic device.

[0125] The following explanation uses a mobile phone as an example to further illustrate the above-mentioned content recommendation method.

[0126] See Figure 5 As shown, the above-mentioned recommended method may include the following steps S501-S506.

[0127] S501, The mobile phone receives the first command input by the user.

[0128] The first instruction is used to indicate the information the user requests. The first instruction can be a voice command, a text command, or other input from the user.

[0129] For example, voice commands can be the content of a user's voice interaction with the voice assistant after waking it up, while text commands can be the text content that the user enters on a page provided by the voice assistant after waking it up.

[0130] In some possible implementations, users can wake up the voice assistant and input voice commands regardless of whether the phone is displaying any page. The page displayed on the phone can be the phone's home screen, an application page, or a system page displayed in response to the user's action.

[0131] In some examples, a user can search for the content in the first image using their mobile phone. In response to this search, the phone displays at least one search result related to the content in the first image. The user then enters a first command into the phone. This first command can instruct the user to request information related to the first image. It is understood that the at least one search result displayed by the phone comes from the same application or different applications on the phone.

[0132] For example, if a user wants to know about a particular water bottle, they can swipe from the left edge of the phone screen to the right, and the phone will display the negative one screen in response to the user's action. Figure 6 As shown in (a), the negative one screen includes a control 601 for implementing the scanning function; when the user clicks the control 601, the phone activates the scanning function and opens the camera, displaying the scanning page, for example... Figure 6 As shown in (b), the scanning page includes an album entry 602; the user clicks the album entry 602, selects a picture of the water cup from the phone's album, and the phone scans the picture of the water cup. After scanning, the phone displays a search results page for the water cup, for example... Figure 6 As shown in (c), the image search results page includes multiple water bottle search results from a shopping app, and different search results may come from different stores. After the image search results page is displayed on the phone, the user can activate the voice assistant and issue a voice command such as "Where can I buy this water bottle for the cheapest price?"

[0133] In the above examples, users can wake up the voice assistant and interact with it in various scenarios, such as when the phone displays the desktop, when the phone displays the system page, or when the phone displays the application page, demonstrating the real-time nature of the interaction and providing users with a better interactive experience.

[0134] S502, the mobile phone sends the first request to the server.

[0135] The first request is used to instruct the retrieval of content recommendation suggestions.

[0136] Among them, content recommendation suggestions are used to indicate at least one of the following factors when obtaining information: the source of information, the content of information, or when recommending information.

[0137] In some possible implementations, after receiving the first request, the server will obtain relatively traditional and basic content recommendation suggestions.

[0138] Taking the shopping scenario as an example, the content recommendation suggestions indicate at least one of the following factors to consider when recommending products: style, material, color, size, and personal preferences.

[0139] In some examples, the first instruction could be, for instance, "Recommend a summer dress," and the first request could be, for instance, "Recommend a summer dress." Based on the first request, the server retrieves content and suggestions, such as "Common considerations for choosing a summer dress." These considerations can specifically point out aspects to pay attention to, such as size, color, style, and user preferences. Information such as size and color can instruct the phone to retrieve images from the camera or user photos from the photo album; information such as style, fashion, and user preferences can instruct the phone to retrieve content browsed or searched by the user in a shopping app.

[0140] In other examples, the first instruction could be something like "What are some recommended children's clothes?", and the first request could be something like "Recommend children's clothes." Based on the first request, the server retrieves content and provides recommendations, such as "Common considerations for choosing children's clothes." These considerations can specifically point out the style, design, and purchase history of the clothes, as well as the child's body shape and height. Information such as style, design, and purchase history can instruct the phone to retrieve application data from the shopping app; information such as the child's body shape and height can instruct the phone to retrieve photos of the child from the photo album app.

[0141] In some possible implementations, the server can plan content recommendation suggestions based on a large language model (LLM). For example, the server can understand the first request, determine the content to be retrieved based on the LLM, and perform the retrieval to obtain at least one retrieval result related to the first instruction. When there are multiple retrieval results, the server can then formulate a more general and comprehensive content recommendation suggestion based on these multiple results.

[0142] See Figure 7 As shown, taking a shopping scenario as an example, the first request is "Recommend a summer dress". The LLM understands the first request and obtains the planned search results, such as searching for "summer dress recommendations" or "summer dress selection suggestions" on the cloud webpage. The server then performs the search and obtains the search results from the webpage. For example, from webpage 1, the search result is "Summer dress recommendations...", and from webpage 2, the search result is "Summer dress selection suggestions are...". Finally, based on these search results, the server generates the final content recommendation suggestions, such as "When buying a summer dress, consider the following suggestions: Choose suitable fabric: Summer dress fabrics should be lightweight and breathable. It is recommended to choose materials such as cotton, linen, chiffon, or silk, which can maintain comfort in hot weather. Regarding style and cut: Choose simple and suitable cuts and styles, such as A-line skirts, fitted styles, ruffles, etc., considering body shape and personal preferences to ensure that the dress is beautiful and comfortable to wear."

[0143] S503, Recommendations and suggestions for receiving content sent by the server on the mobile phone.

[0144] S504: The phone obtains primary data based on content recommendations.

[0145] The first data is generated based on memory information on the mobile phone, and, for example, the memory information comes from at least one of the user's behavioral data on the mobile phone, application data of the mobile phone, images captured by the camera, and sounds captured by the microphone.

[0146] In some possible implementations, before the phone obtains the initial data, the user must authorize or allow the phone to use their stored information. For example, the user may authorize the phone to provide user behavior data, authorize apps on the phone to provide application data, authorize the camera to provide captured images, and authorize the microphone to provide captured sound. With user authorization, the phone then obtains the initial data based on content recommendations. This ensures the security of data on the phone and application data.

[0147] In some possible implementations, users can use a first command to retrieve recommended content or information for themselves. Examples of such first commands include "Recommend a book for me," "Recommend a cup for me," or "Recommend a dress for me." Alternatively, users can also use a first command to recommend content or retrieve information for other users. Examples of such first commands include "Recommend a jacket for a child," "Recommend a dress for my girlfriend," or "Recommend a watch for my boyfriend."

[0148] In some examples, when the first instruction is used to instruct the user to request information for the user, the first data obtained includes the user's usage of the application and first information, wherein the first information includes user identity information and / or the user's current scenario.

[0149] Taking a shopping scenario as an example, in this scenario, the first instruction is used to instruct the mobile phone to recommend products to the user. The mobile phone can obtain information about the user's usage of the shopping app based on the recommended content. For instance, the mobile phone can obtain relevant data from the user's behavioral data and the shopping app's application data, and determine the user's usage of the shopping app based on this data. The usage of the shopping app includes at least one of the following: the duration of use, the frequency of use, the number of times the shopping app is used, or the products viewed within the shopping app. Based on the user's usage of the shopping app, the mobile phone can determine the shopping apps the user prefers to use, the products the user likes to browse within the shopping app, etc., thereby determining the user's preferences.

[0150] Furthermore, the phone also obtains primary information based on content recommendations, which may include user identity information and / or the user's current scenario. For example, the phone can obtain relevant data from images captured by the camera, sounds captured by the microphone, application data from photo album applications, and application data from fitness and health applications, and determine the user's identity information based on this data, such as the user's body shape, height, and appearance characteristics. Additionally, the phone can obtain relevant data from images captured by the camera and sounds captured by the microphone, and determine the user's current scenario based on this data, such as indoors, outdoors, at the beach, in a noisy environment, in a quiet environment, in the rain, during a thunderstorm, or while moving. Based on the user's identity information and the current scenario, the phone can determine the user's needs. For example, if the user is tall, they might need larger-sized clothing; or if the user is outdoors in the rain, they might need a raincoat or waterproof clothing.

[0151] Understandably, the primary data may include user behavior and initial information about the shopping app.

[0152] When users use their mobile phones to obtain recommended content, the phones can obtain primary data from multiple sources. This primary data better reflects the user's preferences, usage habits, and needs. Consequently, based on this primary data, recommended content that better matches the user's preferences, usage habits, and needs can be obtained, bringing a better interactive experience to the user.

[0153] In other examples, when the first instruction is used to instruct a user to request information for another user who is not the user, the first data to be obtained includes the user's usage of the application and second information, which includes the other user's identity information and / or the other user's needs.

[0154] Taking a shopping scenario as an example, in this case, the first instruction is used to direct the phone to recommend products to users other than the user themselves. The phone can obtain information about the user's usage of the shopping app based on the recommended content. For instance, the phone can obtain relevant data from the user's behavioral data and the shopping app's application data, and determine the user's usage of the shopping app based on this data. The usage of the shopping app includes at least one of the following: the duration of use, the frequency of use, the number of times the app was used, or the products viewed within the app. Based on the user's usage of the shopping app, the phone can determine the shopping apps the user prefers, the products they like to browse within the app, etc., thereby determining the user's preferences.

[0155] Furthermore, the phone also obtains secondary information based on content recommendations. This secondary information may include other users' identity information and / or other users' needs. For example, the phone can obtain relevant data from application data in photo album apps and fitness and health apps, and determine other users' identity information based on this data, such as their body shape, height, and appearance. Similarly, the phone can obtain relevant data from memo apps and input method apps, and determine other users' needs based on this data. For instance, if another user is the phone user's girlfriend, based on the user's historical input content and information recorded in memos, the phone can determine the girlfriend's preferences, recent vacation plans, and travel plans; in this case, the girlfriend might need more casual, brightly colored clothing.

[0156] Understandably, the first data may include user usage of the shopping app and second information.

[0157] When a user uses their mobile phone to obtain recommended content for other users, the phone can obtain primary data from multiple sources. This primary data better reflects the user's and other users' preferences, usage habits, and needs. Consequently, based on this primary data, more suitable recommended content can be obtained, bringing a better interactive experience to the user.

[0158] S505: Based on the first data and content recommendation suggestions, the mobile phone obtains recommended content by calling the application.

[0159] The recommended content is used in response to the first instruction.

[0160] In some possible implementations, the mobile phone may first identify at least one application related to the first instruction from among multiple applications installed on the phone, and then obtain recommended content by calling at least one application based on the first data and content recommendation suggestions.

[0161] In some examples, the phone can identify at least one application based on the first instruction. For instance, if the first instruction is "Recommend a summer dress for me," and since the first instruction is related to shopping, the phone can obtain recommendations by calling at least one shopping application.

[0162] In other examples, the phone can identify at least one app based on content recommendations. For example, content recommendations might include... Figure 7 As shown in the figure, based on the content recommendation suggestions, it can be determined that the user's interaction with the mobile phone is related to shopping. Therefore, the mobile phone can obtain recommended content by calling at least one shopping application.

[0163] When the phone identifies only one application, it can retrieve one or more recommended content items by accessing that application. When the phone identifies multiple applications, it retrieves one or more recommended content items from each of those applications. Therefore, recommended content can be obtained from one application or multiple applications. The more recommended content, the more comprehensive the information available to the user, giving them more choices and improving the user's interactive experience.

[0164] S506, the phone displays recommended content.

[0165] In some possible implementations, when the phone receives multiple recommended content items, it can display these items based on the user's app usage. For example, the phone can sort the recommended content items according to the user's app usage and display them in that order.

[0166] The user's usage of the application includes at least one of the following: duration of application use, frequency of application use, number of times the application is used, or content viewed within the application.

[0167] Understandably, user behavior on an app can reflect their preferences and usage habits. In other words, a phone can display multiple recommendations based on a user's preferences and habits when choosing apps, thus providing a better user experience.

[0168] Taking a shopping scenario as an example, the phone obtains recommended content 1 by calling app A, recommended content 2 by calling app B, and recommended content 3 by calling app C. The phone also gathers user preferences for apps A, B, and C. For instance, if the user has used app A the most (or most frequently) over a period of time, used app B less frequently (or less frequently), and used app C the least frequently (or least frequently), then when displaying multiple recommended content items, recommended content 1 from app A can be displayed first, recommended content 2 from app B later, and recommended content 3 from app C last. In other words, the recommended content from the most frequently used app is displayed at the top. Figure 8 As shown in (a) in the figure.

[0169] Alternatively, the phone can retrieve recommended content 1, recommended content 2, recommended content 3, etc., by accessing application A. The phone gathers information about the user's preferences and usage habits within application A. For example, if the user searched for or viewed recommended content 1 most frequently (or most often) within application A over a period of time, searched for or viewed recommended content 2 less frequently (or less often), and searched for or viewed recommended content 3 least frequently (or least often), then when displaying multiple recommended content items, the phone could display recommended content 1 first, recommended content 2 last, and recommended content 3 last. In other words, the most frequently viewed recommended content would be displayed at the beginning. Figure 8 As shown in (b) of the diagram.

[0170] In this way, when the phone receives a lot of recommended content, it displays the recommended content based on the user's preferences and habits, so that the content displayed first can better meet the user's needs, thereby achieving personalized content recommendations for the user.

[0171] As can be seen from the above, in the content recommendation method provided in this application embodiment, the mobile phone can obtain first data from the server based on the content recommendation suggestions. The first data is generated based on memory information. The memory information on electronic devices has a wide range of sources and can comprehensively reflect the user's characteristics, the user's preferences and habits in using electronic devices and / or applications. Therefore, based on the first data, the mobile phone can also more accurately obtain recommended content that meets the user's needs, achieve the purpose of personalized recommendations for users, and improve the user experience.

[0172] In addition, the above method utilizes the memory information provided by the mobile phone, which also improves the resource utilization rate on the mobile phone side.

[0173] In some possible implementations, taking a shopping scenario as an example, the recommended content obtained by the mobile phone can be content corresponding to a certain product. In some examples, the recommended content may include at least one of the following: product display image, brief introduction of the product, product price, application information providing the product, and store information providing the product.

[0174] For example, see Figure 9 As shown, recommendations for dresses can include images of the dress, a brief description of the dress, the price of the dress, apps that offer dresses, and stores that offer dresses.

[0175] The more information included in the recommendations, the more information is presented to the user, which can provide the user with purchasing references and help them choose the products they want to buy more quickly.

[0176] In some possible implementations, if the user's first input does not specify who the content is recommended to, or does not specify the recipient of the recommended content, the phone can determine whether the first instruction is to instruct the phone to recommend content to the user or to other users based on the user's account information, images captured by the camera, and sounds captured by the microphone.

[0177] Taking a shopping scenario as an example, if the first instruction is "recommend a summer dress," the phone determines that the user issuing the instruction is male based on images captured by the camera and sounds captured by the microphone. Alternatively, the phone can determine the user is male based on their mobile account information. If the phone confirms the user is indeed male and wants to recommend a dress, it might be for a girlfriend, mother, etc. Next, the phone uses application data (such as photos, memos, input method data, and fitness data) to identify potential female users and determine their identity information (such as body shape, appearance, height, weight, and age). Finally, based on the female user's identity information and the male user's usage of the shopping app, the phone retrieves recommended dresses by accessing the shopping app.

[0178] Alternatively, if the first instruction is "Recommend a summer dress," the phone determines that the user issuing the instruction is female based on images captured by the camera and sounds captured by the microphone. Alternatively, the phone can determine the user is female based on their logged-in account information and that the user may need to choose a dress. Next, the phone uses images captured by the camera, sounds captured by the microphone, data from photo apps, and data from fitness apps to determine the user's identity information (such as body shape, physical characteristics, height, weight, age, etc.) and the context in which the user is located. Finally, based on the user's identity information, the context, and the user's usage of shopping apps, the phone retrieves recommended dresses by accessing the shopping app.

[0179] It is evident that mobile phones can determine who a user wants to recommend content to in various ways. Furthermore, once the target of the recommendation (such as the user themselves or other users) is determined, the mobile phone can make more targeted recommendations, thereby improving the accuracy of content recommendations.

[0180] In some possible implementations, the phone may also display the analysis process by which it acquires the recommended content before displaying it. For example, see... Figure 10 As shown in (a), the first instruction is "Recommend a summer dress". The analysis process of the mobile phone in response to this instruction may include the following:

[0181] "Understanding your question" means that the phone can analyze the first command to understand the user's intent.

[0182] "Search: Summer dress gift recommendations, dress styles that girls like, dress selection guide..." This process can be the process where the mobile phone sends the first command to the server, and the server searches for dress recommendations on the webpage. The mobile phone can present the server's search process to the user.

[0183] "Search and analyze product information: App A, App B, App C, App D..." During this process, the phone obtains at least one shopping app that offers the dress;

[0184] "Search and analyze personal information: photo album, exercise data..." During this process, the phone obtains initial data from the photo album and exercise data, and analyzes the user's identity information, user's usage habits of shopping apps, etc.

[0185] "Analyze query results". In this process, the mobile phone combines the information obtained from at least one shopping app, the user's identity information, the user's usage habits of the shopping app, etc., to obtain at least one dress recommendation result.

[0186] "Generate Summary" – During this process, the phone generates a summary of the dress recommendations. The summary content might include, for example:

[0187] "When choosing, please consider the following: 1. Color and style... 2. Fabric... 3. Brand and style... Knowing her preferences and style will help you make a more suitable choice. You can also consider checking her collection of fashion magazines or her social media preferences before purchasing."

[0188] For another example, see Figure 10 As shown in (b), after the user sees the image search results page on their phone, their first command is "Where can I buy this cup for the cheapest price?" The phone's analysis process for this command may include the following:

[0189] "Understanding your question" means that the phone can analyze the first command to understand the user's intent.

[0190] "Search: cup price, cup discounts..." This process can be the process where the mobile phone sends the first instruction to the server, and the server searches for cup recommendations on the webpage. The mobile phone can then present the server's search process to the user.

[0191] "Search and analyze product information: App A, App B, App C, App D..." During this process, the phone obtains at least one shopping app that can provide the cup;

[0192] "Search and analyze personal information: color preferences, shopping preferences..." During this process, the phone can obtain primary data from the photo album, exercise data, account information, and shopping applications, and analyze the user's identity information, color preferences, shopping preferences, etc.

[0193] "Analyze query results." In this process, the mobile phone combines the information obtained from at least one shopping application, the user's identity information, the user's color preferences, shopping preferences, etc., to obtain at least one cup recommendation result.

[0194] "Generate Summary"—During this process, the phone generates a summary of the recommended cups. Furthermore, the phone can obtain price and discount information for the cups from various shopping apps, which is then presented to the user as part of the summary. The summary content might include, for example:

[0195] "Considering that you usually prefer to buy from official flagship stores, Xiaoyi has calculated the prices and discounts for this cup on various platforms. The results are as follows. Currently, there are not many differences between the platforms. It is possible that the discount will be even better on platform XX after applying coupons. I hope my suggestion will be helpful to you!"

[0196] Understandably, the above analysis process can be displayed in real time while the mobile phone is acquiring recommended content, so that users can more intuitively understand the process of acquiring recommended content and improve the user experience.

[0197] Based on the above, in some other possible implementations, the process of obtaining recommended content by using a mobile phone as the terminal can be divided into the following steps: retrieval planning based on content recommendation suggestions, implementation of the plan, and display of implementation results.

[0198] For example, in a shopping scenario, see... Figure 11 As shown, the first instruction is "Recommend a summer dress", and the server provides the following recommendations: Figure 7 The following suggestions are provided when purchasing a summer dress: Choose the right fabric: Summer dresses should be made of lightweight and breathable fabrics. Materials such as cotton, linen, chiffon, or silk are recommended as they provide comfort in hot weather. Regarding style and cut: Choose simple and suitable cuts and styles, such as A-line skirts, fitted styles, or ruffles. Consider your body type and personal preferences to ensure a beautiful and comfortable fit.

[0199] Based on content recommendation suggestions, the client performs retrieval planning, considers the content recommendation suggestions, analyzes where to obtain data and what factors need to be considered when obtaining recommended content, and obtains planning results.

[0200] For example, on the client side, based on user profile information and memory information (such as behavioral data, application data, images captured by the camera, and sounds captured by the microphone), the following key points can be derived:

[0201] Gender and age: Based on the images captured by the camera, the user is determined to be a male around 20 years old, which matches the profile information, indicating that the question was asked by the user himself;

[0202] Dating stage: The user has a girlfriend and is in a dating stage;

[0203] Interests and needs: The user has recent vacation plans and shopping preferences, indicating that he may choose vacation clothes for his girlfriend;

[0204] Shopping platform requirements: When users search for clothing products, they prefer to use app A, so more products from this platform can be recommended;

[0205] Customized needs: Analyzing exercise and health body fat and weight information, identifying photos of your girlfriend in her album, and making targeted recommendations.

[0206] After considering the above points, the resulting planning can be, for example:

[0207] "Step 1: Obtain data related to your girlfriend's body shape, appearance features, and clothing style from photo and fitness apps."

[0208] Step 2: Generate search commands for Application A and Application B, send commands to Application A and Application B respectively, and obtain recommended content for dresses from Application A and Application B.

[0209] Step 3: Personalize the sorting and display the recommended content.

[0210] Afterwards, the device implements the plan. During the implementation process, the device obtains data or information sequentially according to the steps in the above planning results, and finally displays the implementation results, that is, displays the sorted recommended content.

[0211] It is understood that the collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application embodiment all comply with the provisions of relevant laws and regulations and do not violate public order and good morals. The user's personal information is not limited to user (or other user) account information, user (or other user) image, user (or other user) voice, user (or other user) body shape, user (or other user) appearance characteristics, user (or other user) weight, user (or other user) height, user (or other user) behavioral data, user (or other user) application usage habits, and preference-related data.

[0212] The above embodiments use a mobile phone recommending content to a user in a shopping scenario as an example to illustrate the content recommendation method. In other embodiments, the content recommendation method can also be applied to other electronic devices, such as tablets, smartwatches, smart TVs, in-vehicle terminals, handheld computers, laptops, UMPCs, netbooks, cellular phones, PDAs, AR and VR devices. Furthermore, in other embodiments, the content recommendation method can also be applied to other scenarios, such as food ordering and ticket booking.

[0213] In some solutions, multiple embodiments of this application can be combined, and the combined solution can be implemented. Optionally, some operations in the processes of each method embodiment may be combined, and / or the order of some operations may be changed. Furthermore, the execution order between the steps of each process is merely exemplary and does not constitute a limitation on the execution order between steps; other execution orders are also possible. It is not intended to indicate that the execution order is the only possible order in which these operations can be performed. Those skilled in the art will conceive of various ways to reorder the operations described in the embodiments of this application. In addition, it should be noted that the process details involved in one embodiment of this application are also applicable to other embodiments in a similar manner, or different embodiments may be combined.

[0214] Furthermore, some steps in the method embodiments can be equivalently replaced with other possible steps. Alternatively, some steps in the method embodiments may be optional and can be deleted in certain use cases. Or, other possible steps may be added to the method embodiments.

[0215] Furthermore, the various method embodiments can be implemented individually or in combination.

[0216] It is understood that, in order to achieve the above functions, the aforementioned electronic device includes hardware and / or software modules corresponding to perform each function. Based on the algorithmic steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in conjunction with the embodiments, but such implementation should not be considered beyond the scope of this application.

[0217] This embodiment can divide the electronic device into functional modules according to the above method example. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0218] This application also provides an electronic device, such as... Figure 12 As shown, the electronic device may include one or more processors 1201, memory 1202 and communication interface 1203.

[0219] The memory 1202, communication interface 1203, and processor 1201 are coupled together. For example, the memory 1202, communication interface 1203, and processor 1201 can be coupled together via bus 1204.

[0220] The communication interface 1203 is used for data transmission with other devices. The memory 1202 stores computer program code. The computer program code includes computer instructions, which, when executed by the processor 1201, cause the electronic device to perform the recommended method described in this embodiment.

[0221] The processor 1201 may be a processor or controller, such as a CPU, a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with this disclosure. The processor may also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0222] Bus 1204 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Bus 1204 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 12 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0223] This application also provides a computer-readable storage medium that includes computer instructions. When the computer instructions are executed on an electronic device, the electronic device performs the relevant method steps described in the above method embodiments.

[0224] This application also provides a computer program product that, when run on a computer, causes the computer to execute the relevant method steps described in the above method embodiments.

[0225] The electronic devices, computer-readable storage media, or computer program products provided in this application are all used to perform the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0226] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, 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.

[0227] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0228] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0229] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0230] If the integrated unit is implemented as 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 embodiments of this application, in essence, or the part that contributes, or all or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0231] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A content recommendation method, characterized in that, Applied to electronic devices, the method includes: Receive a first instruction input by the user; the first instruction is used to indicate the information requested by the user. Send a first request to the server; the first request is used to instruct the server to retrieve content recommendation suggestions; Receive content recommendation suggestions sent by the server; the content recommendation suggestions are used to indicate at least one of the following: the source of the information, the content of the information, or the reference factors when recommending the information; Based on the content recommendation suggestions, first data is obtained; the first data is generated based on the memory information on the electronic device. Based on the first data and the content recommendation suggestions, recommended content is obtained by invoking the application; the recommended content is used to respond to the first instruction. The recommended content is displayed.

2. The method according to claim 1, characterized in that, The application being invoked may be multiple; each application may retrieve recommended content.

3. The method according to claim 1 or 2, characterized in that, The recommended content includes multiple items; displaying the recommended content includes: The recommended content is displayed based on the user's usage of the application.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: In response to a user's search operation on the content of the first image via the electronic device, at least one search result related to the content of the first image is displayed; the at least one search result comes from the same application or different applications of the electronic device; the first instruction is used to instruct the user to request information related to the first image.

5. The method according to any one of claims 1-4, characterized in that, The step of obtaining the first data based on the content recommendation suggestions includes: If the user authorizes the use of the memory information, the first data is obtained based on the content recommendation suggestions.

6. The method according to any one of claims 1-5, characterized in that, When the first instruction is used to instruct the user to request information for the user, the first data obtained includes the user's usage of the application and first information, which includes user identity information and / or the user's current scenario.

7. The method according to any one of claims 1-5, characterized in that, When the first instruction is used to instruct a user to request information for another user who is not the user, the first data obtained includes the user's usage of the application and second information, the second information including the other user's identity information and / or the other user's needs.

8. The method according to any one of claims 1-7, characterized in that, The application is a shopping application, and the content recommendation suggestions indicate at least one of the following factors when recommending products: style, material, color, size, and personal preference.

9. The method according to claim 8, characterized in that, The recommended content includes at least one of the following: product display images, brief product descriptions, product prices, application information for the product, and store information for the product.

10. The method according to any one of claims 1-9, characterized in that, The display of the recommended content also includes: This describes the process by which the electronic device analyzes and recommends content.

11. A content recommendation method, characterized in that, The method is applied to a communication system, which includes electronic devices and servers; the method includes: The electronic device receives a first instruction input by the user; the first instruction is used to indicate the information requested by the user. The electronic device sends a first request to the server; the first request is used to instruct the user to obtain content recommendation suggestions. The server receives the first request and obtains content recommendation suggestions; it sends the content recommendation suggestions to the electronic device; the content recommendation suggestions are used to indicate at least one of the following: the source of the information, the content of the information, or the reference factors when recommending the information; The electronic device receives the content recommendation suggestions sent by the server and obtains first data based on the content recommendation suggestions; the first data is generated based on the memory information on the electronic device. The electronic device retrieves recommended content by invoking an application based on the first data and the content recommendation suggestions; the recommended content is used to respond to the first instruction. The electronic device displays the recommended content.

12. A communication system, characterized in that, Including electronic devices and servers; The electronic device is used to perform the content recommendation method according to any one of claims 1-10; The server is used to receive the first request and obtain content recommendation suggestions; Send the content recommendation suggestions to the electronic device.

13. An electronic device, characterized in that, The device includes a memory and one or more processors; the memory is coupled to the processors; wherein the memory stores computer program code, the computer program code including computer instructions, which, when executed by the processor, cause the electronic device to perform the content recommendation method as described in any one of claims 1-10.

14. A computer-readable storage medium, characterized in that, Includes computer instructions that, when executed on an electronic device, cause the electronic device to perform the content recommendation method as described in any one of claims 1-10.

15. A computer program product, characterized in that, When the computer program product is run on a computer, the computer performs the content recommendation method as described in any one of claims 1-10.

Images