WO2022111726A1 - 一种信息排序方法及电子设备 - Google Patents

一种信息排序方法及电子设备 Download PDF

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Publication number
WO2022111726A1
WO2022111726A1 PCT/CN2021/134377 CN2021134377W WO2022111726A1 WO 2022111726 A1 WO2022111726 A1 WO 2022111726A1 CN 2021134377 W CN2021134377 W CN 2021134377W WO 2022111726 A1 WO2022111726 A1 WO 2022111726A1
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candidate objects
devices
target object
candidate
labels
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PCT/CN2021/134377
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English (en)
French (fr)
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方荣杰
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华为技术有限公司
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Priority to EP21897226.3A priority Critical patent/EP4250137A4/en
Publication of WO2022111726A1 publication Critical patent/WO2022111726A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9032—Query formulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/338—Presentation of query results
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/38—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9038—Presentation of query results
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/907—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • G06F40/216—Parsing using statistical methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/284—Lexical analysis, e.g. tokenisation or collocates

Definitions

  • the present application relates to the field of terminal technologies, and in particular, to an information sorting method and an electronic device.
  • Harmony operating system (operating system, OS) is a distributed operating system that is "future-oriented" and oriented to all scenarios (mobile office, sports health, social communication, media entertainment, etc.).
  • Harmony OS proposes a distributed concept based on the same set of system capabilities, adapting to a variety of terminal forms, and can support a variety of electronic devices.
  • the application layer in Harmony OS can include applications and services, and services refer to feature capability (FA) service and basic capability (particle ability, PA) service.
  • the application is composed of one or more FA services and/or PA services.
  • the FA service has a UI interface, providing the ability to interact with users; while the PA service has no UI interface, providing the ability to run tasks in the background and a unified data access abstraction.
  • Applications developed based on FA/PA can implement specific business functions, support cross-device scheduling and distribution, and provide users with a consistent and efficient application experience.
  • the application based on FA/PA service has the characteristics of small amount of data and can be used without downloading and installing, realizing the dream of application "at your fingertips", so it has a very broad application prospect.
  • the present application provides an information sorting method and an electronic device, which are used to solve the problem that a user cannot find a desired application or a desired service in a timely and accurate manner due to too many applications or services.
  • an embodiment of the present application provides an information sorting method, which can be applied to an electronic device.
  • the method includes: the electronic device receives a user's search operation, the search operation includes keywords input by the user, and in response to the search operation, a recommendation interface is displayed, and among the candidate objects in the recommendation interface, the labels of the K candidate objects correspond to the target objects of the same attribute installed on the K devices.
  • the ranking of the K candidate objects is determined according to the semantic similarity between the keywords and the labels of the K candidate objects, and the device states of the K devices.
  • the method can find multiple candidate objects from the electronic device and other devices connected to the electronic device, and compare the application or application on the device more relevant to the multiple candidate objects.
  • the services are ranked first, which is convenient for users to find, which can improve search efficiency and user experience.
  • the sorting of the K candidate objects may be implemented in the following manner. Specifically, the electronic device may obtain the labels of the N candidate objects according to the keywords, and calculate the key The semantic similarity between the word and the labels of the N candidate objects; then, from the labels of the N candidate objects, the labels of the M candidate objects corresponding to the semantic similarity greater than the set threshold are determined.
  • the labels of the K candidate objects in the labels correspond to the target objects of the same attribute installed on the K devices; M ⁇ N, M and N are positive integers greater than or equal to 2; therefore, according to the keywords and K
  • the semantic similarity between the labels of the candidates, and the device states of the K devices can rank the K candidates.
  • the existing search results are usually obtained from the local device or the network side, while the present application can search for candidate objects from the electronic device and other devices connected to the electronic device , and this method is more aimed at sorting the candidate objects of the target object corresponding to the same attribute in the search results, and combines the device status in the sorting process, so as to sort the applications or services of more relevant devices to the front, which is convenient for searching and can improve the search efficiency. , to improve the user experience.
  • the device states of the K devices may include at least one of the following states: the power supply type of the device, the screen size of the device, the available computing resources of the device, and the correlation between the device performance and the target object. If some speakers are plug-in devices, smart TVs are plug-in devices or large-screen devices. The audio playback performance of speakers is strongly related to music applications, and the audio playback performance of speakers is weakly related to video applications.
  • applications or services on more related devices can be ranked first, which facilitates searching, improves search efficiency, and improves user experience.
  • the target object with the same attribute on the K devices can be the target object with the same name on the K devices, such as WeChat on mobile phones and tablets Application, or, the target object of the same attribute on K devices is the target object of the same supplier on K devices, such as mobile phone Apps and Douyin on Tablet Apps can be ByteDance from the same vendor or, the target object of the same attribute on K devices can be the target object of the same installation package on K devices, for example, WeChat on mobile phones and tablets The installation package name of the application is the same.
  • the target object of the same attribute on the K devices may be the target object of the same function on the K devices, for example, the mobile phone Apps and Douyin on Tablet All apps have a short video sharing function.
  • the electronic device ranks the K candidate objects according to the semantic similarity between the keywords and the labels of the K candidate objects, as well as the device states of the K devices, including: the electronic device according to the keywords
  • the semantic similarity with the labels of the K candidate objects determines the first weights corresponding to the K candidate objects respectively; and the matching between the device states of the K devices according to the constraints of the prior knowledge related to the target objects degree, determine the second weights corresponding to the K candidate objects respectively; and then sort the K candidate objects according to the first weight and the second weight.
  • a possible implementation may be to sort the K candidates according to the product of the first weight and the second weight.
  • the electronic device determines the first weights corresponding to the K candidate objects according to the semantic similarity between the keywords and the labels of the K candidate objects; Check the matching degree between the constraints of the knowledge and the device states of the K devices, and determine the second weights corresponding to the K candidate objects respectively.
  • the K candidate objects can be comprehensively sorted .
  • Such sorting results can more accurately match the application or service that the user wants to search, which helps to improve search efficiency and user experience.
  • the above-mentioned constraints on the prior knowledge related to the target object may include at least one of the following conditions: the target object preferentially runs on a large-screen device, the target object preferentially runs on a plug-in type device, The target object is preferentially run on devices with high computing power, and the target object is preferentially run on devices with good audio playback performance.
  • video FA services or video applications run preferentially on large-screen devices
  • TV FA services or TV applications run preferentially on plug-in devices
  • music FA services or music applications run preferentially on speakers.
  • the constraints of prior knowledge can be manually set in advance, and an association relationship between applications or services and device states can be established through the above-mentioned conditions, thereby helping to use device states to sort applications or services.
  • the electronic device may determine the second weight in any of the following ways:
  • the target object preferentially runs on a plug-in type device
  • the second weight of the candidate object is greater than the second weight of the corresponding candidate object of the device that does not support the plug-in type
  • the constraint condition of the prior knowledge related to the target object is that the target object preferentially runs on a large-screen device, determine the candidate corresponding to the device with the larger screen among the K devices corresponding to the K candidate objects. The greater the second weight of the object;
  • the constraint condition of the prior knowledge related to the target object is that the target object preferentially runs on a device with strong computing power
  • the constraint condition of the prior knowledge related to the target object is that the target object preferentially runs on a device with good audio playback performance
  • the second weight of the device is larger.
  • the sorting method of the K candidate objects displayed by the electronic device in the preset recommendation interface follows: the candidate object with the larger product of the first weight and the second weight is ranked higher, and vice versa. , the smaller the product of the first weight and the second weight is, the later the candidate object is ranked.
  • the ranking result of the applications or services recommended according to the above method more accurately matches the applications or services that the user wants to search, which helps to improve search efficiency and user experience.
  • the electronic device obtains the labels of the N candidate objects according to the keywords, including: obtaining detailed information of the L candidate objects on the K devices from a database; Extract the original keywords from the detailed information, perform semantic analysis on the original keywords, and obtain the labels of L candidate objects from the analysis results.
  • the labels of N candidate objects are obtained from the labels of the candidate objects.
  • the detailed information of the application includes, but is not limited to, the title of the application, the description text of the application, the comment information of the application, the recommended words of the application, the latest update feature of the application and other information.
  • the label of the application includes, but is not limited to, information such as the name of the application, the category to which the application belongs, and the characteristics of the application.
  • the detailed information of the service includes, but is not limited to, the title of the service, the description text of the service, the comment information of the service, the recommended words of the service, and the latest update features of the service and other information.
  • the label of the service includes, but is not limited to, information such as the name of the service, the category of the service, and the characteristics of the service.
  • an electronic device provided by an embodiment of the present application includes: one or more processors and a memory, wherein program instructions are stored in the memory, and when the program instructions are executed by the device, the above aspects of the embodiments of the present application are implemented and any possible design method involved in the various aspects.
  • a chip provided by an embodiment of the present application is coupled to a memory in a device, so that the chip invokes program instructions stored in the memory when running, so as to implement the above aspects of the embodiments of the present application and A method of any possible design to which the various aspects relate.
  • a computer-readable storage medium stores program instructions, and when the program instructions are executed on an electronic device, the device enables the device to perform the above aspects of the embodiments of the present application. and any possible design method involved in the various aspects.
  • a fifth aspect is a computer program product of an embodiment of the present application, when the computer program product is run on an electronic device, the electronic device is made to execute the above-mentioned aspects and any possibility involved in the various aspects of the embodiments of the present application. method of design.
  • FIG. 1 is a schematic structural diagram of a mobile phone according to an embodiment of the present application.
  • FIG. 2 is a schematic structural diagram of an Android operating system provided by an embodiment of the present application.
  • FIG. 3 is a schematic diagram of an application scenario provided by an embodiment of the present application.
  • 4A to 4E are another set of interface schematic diagrams provided by the embodiments of the present application.
  • FIG. 5A is a schematic diagram of another application scenario provided by an embodiment of the present application.
  • 5B is another set of interface schematic diagrams provided by an embodiment of the present application.
  • 6A to 6B are schematic interface diagrams provided by embodiments of the present application.
  • FIG. 7 is a schematic flowchart of another information sorting method provided by an embodiment of the present application.
  • FIG. 8 is a schematic flowchart of another information sorting method provided by an embodiment of the present application.
  • FIG. 9 is a schematic flowchart of another information sorting method provided by an embodiment of the present application.
  • FIG. 10 is a schematic flowchart of another information sorting method provided by an embodiment of the present application.
  • FIG. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • the electronic device can perform semantic matching through the keywords input by the user to obtain search results of related applications, and sort them according to the semantic similarity.
  • the above search results do not involve application information on other devices, so the search result interface of the electronic device only displays application information related to the input keyword on its own device. It can be seen that the current application search method of electronic devices does not involve searching and sorting application information or service information on multiple devices.
  • the embodiments of the present application provide an information sorting method and an electronic device, which can implement accurate sorting of applications and/or services in the search results of the device itself and other devices connected to the device, and can effectively improve information search efficiency, so that users can find the desired application or service in a timely and accurate manner.
  • the electronic device may be a portable terminal including functions such as a personal digital assistant and/or a music player, such as a mobile phone, a tablet computer, a wearable device (such as a smart watch) with wireless communication capabilities, a vehicle-mounted device, etc. .
  • portable terminals include but are not limited to carrying Or portable terminals of other operating systems.
  • the aforementioned portable terminal may also be, for example, a laptop computer (Laptop) having a touch-sensitive surface (eg, a touch panel). It should also be understood that, in some other embodiments, the above-mentioned terminal may also be a desktop computer having a touch-sensitive surface (eg, a touch panel).
  • FIG. 1 shows a schematic structural diagram of an electronic device 100 .
  • 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 , mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, sensor module 180, buttons 190, motor 191, indicator 192, camera 193, display screen 194, and Subscriber identification module (subscriber identification module, SIM) card interface 195 and so on.
  • SIM Subscriber identification module
  • the sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, and ambient light. Sensor 180L, bone conduction sensor 180M, etc.
  • the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 100 .
  • the electronic device 100 may include more or less components than shown, or combine some components, or separate some components, or arrange different components.
  • the illustrated components may be implemented in hardware, software, or a combination of software and hardware.
  • the processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), controller, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural-network processing unit (neural-network processing unit, NPU), etc. Wherein, different processing units may be independent devices, or may be integrated in one or more processors.
  • application processor application processor, AP
  • modem processor graphics processor
  • ISP image signal processor
  • controller video codec
  • digital signal processor digital signal processor
  • baseband processor baseband processor
  • neural-network processing unit neural-network processing unit
  • the electronic device 100 implements a display function through a GPU, a display screen 194, an application processor, and the like.
  • the GPU is a microprocessor for image processing, and is connected to the display screen 194 and the application processor.
  • the GPU is used to perform mathematical and geometric calculations for graphics rendering.
  • Processor 110 may include one or more GPUs that execute program instructions to generate or alter display information.
  • the electronic device 100 may implement a shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, an application processor, and the like.
  • the SIM card interface 195 is used to connect a SIM card.
  • the SIM card can be contacted and separated from the electronic device 100 by inserting into the SIM card interface 195 or pulling out from the SIM card interface 195 .
  • the electronic device 100 may support 1 or N SIM card interfaces, where N is a positive integer greater than 1.
  • the SIM card interface 195 can support Nano SIM card, Micro SIM card, SIM card and so on. Multiple cards can be inserted into the same SIM card interface 195 at the same time. The types of the plurality of cards may be the same or different.
  • the SIM card interface 195 can also be compatible with different types of SIM cards.
  • the SIM card interface 195 is also compatible with external memory cards.
  • the electronic device 100 interacts with the network through the SIM card to implement functions such as call and data communication.
  • the electronic device 100 employs an eSIM, ie: an embedded SIM card.
  • the wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modulation and demodulation processor, the baseband processor, and the like.
  • Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals.
  • Each antenna in electronic device 100 may be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization.
  • the antenna 1 can be multiplexed as a diversity antenna of the wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.
  • the mobile communication module 150 may provide wireless communication solutions including 2G/3G/4G/5G etc. applied on the electronic device 100 .
  • the mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), and the like.
  • the mobile communication module 150 can receive electromagnetic waves from the antenna 1, filter and amplify the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation.
  • the mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and then turn it into an electromagnetic wave for radiation through the antenna 1 .
  • at least part of the functional modules of the mobile communication module 150 may be provided in the processor 110 .
  • at least part of the functional modules of the mobile communication module 150 may be provided in the same device as at least part of the modules of the processor 110 .
  • the wireless communication module 160 can provide applications on the electronic device 100 including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), global navigation satellites Wireless communication solutions such as global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (infrared radiation, IR) technology.
  • WLAN wireless local area networks
  • BT Bluetooth
  • GNSS global navigation satellite system
  • FM frequency modulation
  • NFC near field communication
  • IR infrared radiation
  • the wireless communication module 160 may be one or more devices integrating at least one communication processing module.
  • the wireless communication module 160 receives electromagnetic waves via the antenna 2 , frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110 .
  • the wireless communication module 160 can also receive the signal to be sent from the processor 110 , perform frequency modulation on it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2 .
  • the antenna 1 of the electronic device 100 is coupled with the mobile communication module 150, and the antenna 2 is coupled with the wireless communication module 160, so that the electronic device 100 can communicate with the network and other devices through wireless communication technology.
  • the wireless communication technologies may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), broadband Code Division Multiple Access (WCDMA), Time Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN, NFC , FM, and/or IR technology, etc.
  • FIG. 1 do not constitute a specific limitation on the electronic device 100, and the electronic device 100 may also include more or less components than those shown in the figure, or combine some components, or separate some components components, or a different arrangement of components.
  • the combination/connection relationship between the components in FIG. 1 can also be adjusted and modified.
  • the software system of the electronic device may adopt a layered architecture, an event-driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture.
  • the embodiments of the present application take Harmony OS with a layered architecture as an example to exemplarily describe the software structure of an electronic device.
  • FIG. 2 is a block diagram of a software structure of an electronic device according to an embodiment of the present application.
  • the layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Layers communicate with each other through software interfaces.
  • the Android system is divided into four layers, which are an application layer, an application framework layer, a system service layer, and a kernel layer from top to bottom.
  • the application layer includes applications and services, wherein applications include system applications and third-party applications, services include FA services and PA services, for example, system applications include applications, FA services and PA services, for example, applications such as desktop, control bar, phone , settings, etc., FA services such as soybean milk machine services, PA services such as video conferencing services, third-party applications such as Douyin application.
  • An application of Harmony OS is composed of one or more feature capability (FA) services and/or basic capability (particle ability, PA) services. In other words, when the application is composed of one FA service, the application is equivalent to the FA service, and when the application is composed of one PA service, the application is equivalent to the PA service.
  • FA feature capability
  • PA particle ability
  • the FA service has a UI interface, providing the ability to interact with users; while the PA service has no UI interface, providing the ability to run tasks in the background and a unified data access abstraction.
  • Applications developed based on FA/PA can implement specific business functions, support cross-device scheduling and distribution, and provide users with a consistent and efficient application experience.
  • the application framework layer provides multi-language user program frameworks and Ability (ability) frameworks such as Java/C/C++/JS for Harmony OS applications, as well as multi-language framework application programming interfaces (application programming interfaces) open to various software and hardware services. interface, API); at the same time, multi-language framework APIs such as C/C++/JS are provided for devices using Harmony OS.
  • the APIs supported by different devices are related to the degree of componentization of the system.
  • the system service layer is the core capability set of Harmony OS, which provides services to applications through the framework layer.
  • the system service layer may include a system basic capability subsystem set, a basic software service subsystem set, an enhanced software service subsystem set, a hardware service subsystem set, and the like.
  • System Basic Capability Subsystem Set Provides basic capabilities for the operation, scheduling, migration and other operations of distributed applications on Harmony OS multi-devices. It is composed of subsystems such as time, common base library, multi-mode input, graphics, security, AI and so on.
  • Ark runtime provides C/C++/JS multi-language runtime and basic system class library, and also provides static Java programs using Ark compiler (that is, the part of application or framework layer developed using Java language) Runtime.
  • Basic software service subsystem set Provide public and general software services for Harmony OS, consisting of subsystems such as event notification, telephony, multimedia, and design for each link of the product life cycle (design for X, DFX).
  • Enhanced software service subsystem set Provide Harmony OS with differentiated capability-enhanced software services for different devices, including smart screen proprietary business, wearable proprietary business, Internet of things (IoT) proprietary business, etc. Subsystem composition.
  • Hardware service subsystem set Provide hardware services for Harmony OS, which consists of subsystems such as location services, biometric identification, wear-specific hardware services, and IoT-specific hardware services.
  • the basic software service subsystem set, the enhanced software service subsystem set, and the hardware service subsystem set can be tailored according to the granularity of subsystems, and each subsystem can be tailored according to the granularity of functions.
  • the core library consists of two parts: one part is the kernel subsystem, Linux kernel (open source computer operating system kernel) and Lite OS (lightweight operating system), etc.; the other part is the driver subsystem.
  • Kernel subsystem Harmony OS adopts a multi-kernel design, which supports the selection of suitable OS kernels for different resource-constrained devices.
  • the kernel abstract layer (KAL) provides basic kernel capabilities to the upper layer by shielding the differences between multiple kernels, including process/thread management, memory management, file system, network management, and peripheral management.
  • Harmony OS driver framework (Harmony OS driver foundation, HDF) is the open foundation of Harmony OS hardware ecosystem, providing unified peripheral access capability and driver development and management framework.
  • the kernel layer is the layer between hardware and software.
  • the kernel layer contains at least display drivers, camera drivers, audio drivers, and sensor drivers.
  • the hardware may refer to various types of sensors, such as an acceleration sensor, a gyroscope sensor, a touch sensor, a pressure sensor, and the like involved in the embodiments of the present application.
  • the embodiments of the present application provide an information sorting method, which can realize the sorting of information on the device itself. Search and sort with applications or FA services on other devices connected to the device, so that users can find the desired application or service in a timely and accurate manner.
  • the methods provided by the embodiments of the present application are exemplarily introduced below in different scenarios.
  • Each scenario is described by taking the smart home shown in FIG. 3 as an example.
  • the smart home devices shown in FIG. 3 include: smart speakers, mobile phones, tablets, and living rooms. smart screen, etc.
  • Smart screens are large-screen products in home terminals. Compared with traditional TVs, smart screens can not only watch TV programs, but also watch online videos online, and some even support voice control to control smart home appliances.
  • the interface of the mobile phone displays a negative one-screen interface 400 as shown in (a) of FIG. 4A , and a search box 401 of the negative one screen of the mobile phone can receive keywords input by the user.
  • a search box 401 of the negative one screen of the mobile phone can receive keywords input by the user.
  • the user may have multiple devices at the same time, for example, the user has a mobile phone, a smart screen, and a tablet at the same time, applications and services may be installed on multiple devices respectively. Therefore, when the user enters a keyword in the search box on the lower screen of the mobile phone, application and FA service information related to the keyword can be searched from the user's mobile phone and other devices connected to the user's mobile phone.
  • the Welink application consists of one or more FA services and PA services.
  • the FA service may include Welink-video FA service and/or Welink-chat FA service
  • the PA service may include Welink - Video PA service and/or Welink-chat PA service.
  • the Welink-Video FA service and the Welink-Video PA service can run independently of the Welink application, and similarly, the Welink-Chat FA service and the Welink-Chat PA service can also run independently of the Welink application.
  • the mobile phone displays as shown in (b) of FIG.
  • the mobile phone After the user completes the input operation of the keyword, the mobile phone receives the operation that the user acts on the search control 411, and in response to this operation, the mobile phone performs the query operation. Specifically, the mobile phone first checks whether there are other devices connected to the mobile phone from the near field through the interconnection protocol. If there is, then according to the search keyword, the mobile phone and other devices are searched for application and service information related to the keyword. , and relevant search results are displayed on the interface 410 .
  • the interface 410 in addition to the “Welink” application related to “Welink” on the mobile phone, the interface 410 also displays “Welink” related applications on the smart screen in the living room.
  • the interface 410 may also include other "Welink” related applications or services, which are not shown one by one in the figure. Because the smart screen is a plug-in device and has a large screen, the "Welink-Video FA " service related to "video call” on the smart screen has the highest priority, so it is ranked first.
  • the mobile phone can also display only the FA service information related to the keyword on the mobile phone on the interface 410, for example , only the "Welink-Jetta" app related to "Welink” on the mobile phone is displayed.
  • the mobile phone checks from the near field that there is no other device connected to the mobile phone through the interconnection protocol, but when the mobile phone determines that there are other devices that can be connected, the mobile phone can also actively establish a connection with other devices. Then search the FA service information related to the keyword from the mobile phone and other connected devices.
  • the mobile phone displays the interface 430 shown in (b) of FIG. 4B , that is, The user can pull up the control interface of the "Welink-Video FA " service on the mobile phone to dial the video conference.
  • the mobile phone displays the interface 440 shown in (c) of FIG. 4B .
  • the smart screen in the living room also invokes the relevant hardware (such as camera, microphone, etc.) to pull up the "Welink-Video PA " service on the smart screen to create a video
  • the session is connected, and finally the interface shown in Figure 4C is displayed.
  • the user can operate the "Welink-Video FA " service on the living room smart screen on the mobile phone, so as to achieve the purpose of using the living room smart screen to initiate a video session.
  • the mobile phone displays the interface 460 shown in (b) of FIG. 4D, That is, the user can pull up the control interface of the "Welink-Chat FA " service on the mobile phone.
  • the smart screen in the living room also calls the relevant hardware (such as the camera). , microphone, etc.) pull up the "Welink-chat PA " service on the smart screen to establish a short message session connection, and display the interface shown in Figure 4E.
  • the user can operate the "Welink-Chat FA " service on the living room smart screen on the mobile phone, so as to achieve the purpose of using the living room smart screen to initiate a short message conversation.
  • the user's smart screen is installed with the Welink application, and the Welink application includes the Welink-video FA service and the Welink-chat FA service.
  • the WeChat application is also installed on the smart screen, and the WeChat includes WeChat-video FA service and WeChat-chat FA service.
  • the mobile phone displays the display as shown in Figure 4A (c ) shown in the interface 410. After the user completes the input operation of the keyword, the mobile phone receives the operation that the user acts on the search control 411, and in response to this operation, the mobile phone performs the query operation.
  • the mobile phone first checks whether there are other devices that are connected to the mobile phone from the near field through the interconnection protocol. If there is, then according to the search keyword, the mobile phone and other devices are searched for keywords-related applications and FA services. information, and more relevant search results are displayed on the interface 410 .
  • the interface 410 in addition to the “Welink-Video FA ” service related to “video call” on the smart screen, the interface 410 also displays the “Welink-Video FA” service on the smart screen in the living room. WeChat -FA” service, as well as the "Welink” application on the mobile phone and the "WeChat” application on the mobile phone.
  • the interface 410 may also include other applications or services related to "video calling", which are not the same in the figure. One shows. Because the smart screen is a plug-in device and the screen is large, the "Welink-Video FA " service related to "video call" on the smart screen has the highest priority, so the ranking is the highest.
  • the Welink application is a conference application, and the Welink application may be composed of one or more FA services and PA services.
  • the FA services may include Welink-video FA services and/or Welink- Chat FA service composition.
  • WeChat The application is a social application, WeChat An application can consist of one or more FA services and PA services, for example, FA services can include WeChat - Video FA service and/or WeChat - Chat FA service composition, PA service can include WeChat - Video PA service and/or WeChat - Chat PA service.
  • WeChat Video FA service and WeChat Video PA service can be independent of WeChat Apps run separately, likewise, WeChat Chat FA service and WeChat Chat PA service can also be independent of WeChat The application runs alone. Because the user may have multiple devices at the same time, for example, the user has a mobile phone, a smart screen, and a tablet at the same time, applications and services may be installed on multiple devices respectively. Therefore, when the user enters a keyword in the search box on the lower screen of the mobile phone, application and FA service information related to the keyword can be searched from the user's mobile phone and other devices connected to the user's mobile phone.
  • the label of the FA service includes not only the name of the FA service, but also device attributes, device types, function descriptions, and FA service package names
  • the device attributes may be large-screen devices or small-screen devices
  • the device type It can be the type of smart screen or the serial number of the smart screen device
  • the function description of the FA service can be a video service or a music service, etc.
  • the FA service will be artificially marked with labels related to device attributes, device type, function description, and FA service package name. Based on this, in addition to searching by entering the name of the FA service in the search box, the user can also enter the attribute of the FA service in the search box.
  • the attribute of the FA service can be the functional characteristic of the FA service. Enter “video call” in the search box, you can search for "Welink video FA ", “WeChat-Video FA “, etc. related to "video call”; or, the attribute of the FA service can be the service type of the FA service. Enter “music” in the search box, you can search for "music FA ", "hiaraya” related to "music” FA ", etc.; or, the attribute of the FA service can be the name of the device strongly related to the FA service. Suppose you enter "smart screen” in the search box, you can search for "Welink-video FA” related to the "smart screen” , "WeChat-Video FA ", etc.
  • the method for sorting the search results by the mobile phone may specifically be any one or a combination of the following manners.
  • Method 1 The mobile phone can obtain the labels of N candidate FA services related to the keywords according to the keywords, and then calculate the semantic similarity between the keywords and the labels of the N candidate FA services; according to the size of the semantic similarity, determine The FA service corresponding to the semantic similarity greater than the set threshold, among which the FA service with the greater semantic similarity is ranked higher. For example, displayed in the interface 410 are 4 FA services whose semantic similarity is greater than the set threshold.
  • Method 2 The mobile phone can obtain the tags of N candidate FA services related to the keyword according to the keyword, and then calculate the word frequency distribution of the keyword in the tags of the N candidate FA services. If there are many related FA services, in the search results under all devices in the interface 410, the search results of the mobile phone are higher than the search results of other devices. That is, devices with more FA services related to keywords are ranked higher. On the other hand, if FA services related to keywords are evenly distributed in mobile phones and other devices, the ranking of the FA services is relatively low. On the smart screen in the living room), the FA service of the device is ranked higher.
  • the mobile phone can obtain the device status of the mobile phone and other devices, such as the power supply type of the device, the screen size of the device, the available computing resources of the device, the correlation between the device performance and the target FA service, and the prioritization of obtaining the FA service. Then, according to the prior knowledge constraints related to the device status and FA services, the FA services in the search results are sorted.
  • the prior knowledge constraints related to the FA service may include that the FA service is preferentially run on a large-screen device, the FA service is preferentially run on a plug-in type device, the FA service is preferentially run on a device with strong computing power, or the FA service is preferentially run Runs on devices with good audio playback performance.
  • the prior knowledge constraints of the "Welink-Video FA” service are to run on large-screen devices and plug-in devices preferentially, because the device status of the smart screen in the living room is a large-screen device and the power supply type is Plug-in type, so the smart screen in the living room has a high degree of matching with the "Welink-Video FA” service, so the "Welink-Video FA” service on the smart screen in the living room is the most advanced.
  • the devices shown in FIG. 5A include: a vehicle terminal, a mobile phone, a smart watch, and the like. Assuming that family member A in the back row of the car needs to navigate, then family member A can operate his mobile phone and control the vehicle terminal to perform map navigation.
  • the interface of the mobile phone displays a negative one-screen interface 500 as shown in (a) of FIG. 5B .
  • the user touches the search box ie, the touch focus falls on the search box
  • the user is ready to input
  • the mobile phone displays the interface 510 as shown in (b) in FIG.
  • the mobile phone receives the user's action on the search control
  • the operation of 511 in response to this operation, search for application information related to the keyword "navigation” from mobile phones and other devices (such as smart watches in the car and on-board terminals), and then display on the interface 510 according to the query result. Search results related to the search term "navigation”.
  • the interface 510 includes “Tencent Maps” related to “navigation” on the mobile phone. ” app, which also shows the “Navigation” related “Google Maps” on the smartwatch ” application, and the “Baidu map” related to “navigation” on the vehicle terminal "application.
  • the mobile phone receives the user's action on the “Baidu map” "Apply the operation of the control 512, the mobile phone runs the program locally to control the "Baidu map” on the vehicle terminal "The purpose of the application. In this way, the user can pull up the “Baidu map” on the vehicle terminal by operating on the mobile phone ” navigation service.
  • the method for sorting the search results by the mobile phone may specifically be as follows: after the mobile phone establishes a connection with the vehicle terminal and the smart watch, in addition to the status of the device itself, the device status of the vehicle terminal and the device status of the smart watch can also be acquired.
  • the device status of the vehicle terminal is in the running state, plug-in type device, and sufficient computing resources; the device status of the smart watch includes battery-powered devices and insufficient computing resources.
  • the mobile phone also obtains the "Baidu Map" "Apply the relevant prior knowledge constraints, for example, the mobile phone obtains the "Baidu map" from the cloud server "Application-related prior knowledge constraints are preferential plug-in type devices, and preferentially run on devices with strong computing power.
  • the example shown in the above scenario 2 is also applicable to the search and sorting of navigation FA services. That is to say, if the user enters "navigation" in the search box, the search results can also include the “navigation” on the smart watch.
  • Navigation”-related FA services, and FA services related to “navigation” on the vehicle terminal the user can also operate the FA service of the vehicle terminal on the mobile phone, and pull up the navigation-related PA service on the vehicle terminal.
  • the interface of the mobile phone displays a negative one-screen interface 600 as shown in (a) of FIG. 6A
  • the search box 601 of the negative one-screen of the mobile phone can receive keywords input by the user.
  • the mobile phone displays an interface 610 as shown in (b) in FIG. 6A , assuming that the user has entered “music” in the interface 610 , after the user completes the input operation of the keyword, the mobile phone receives the operation of the user acting on the search control 611, and in response to this operation, the mobile phone executes the query operation.
  • the mobile phone first checks whether there are other devices connected to the mobile phone from the near field through the interconnection protocol. If there is, then according to the search keyword, the mobile phone and other devices are searched for the application related to the keyword "music". information, and more relevant search results are displayed on the interface 610 .
  • the interface 610 in addition to the controls of the “Music” application on the mobile phone, the interface 610 also displays the controls of the “Music” application on the tablet, and the “Music” application on the smart speaker. Controls for the Music app.
  • the method for sorting the search results in the interface 610 by the mobile phone may specifically be: after the mobile phone establishes a connection with the smart speaker and the tablet, in addition to acquiring the state of the device itself, the device state of the tablet and the status of the smart speaker can also be acquired.
  • Device status for example, the device status of a smart speaker is a plug-in type device with good audio playback performance; the device status of a tablet includes a battery-powered device with good video playback performance.
  • the mobile phone also obtains the prior knowledge constraints related to the "music" application. For example, the mobile phone obtains the prior knowledge constraints related to the "music" application from the cloud server. A device with good audio playback performance.
  • the mobile phone sorts the “music” applications in the search results. Because the device status of the smart speaker is good audio playback performance and the power supply type is plug-in type, the matching degree between the smart speaker and the "music” application is high, so the "music” application on the smart speaker is the most advanced, followed by the mobile phone. , followed by the Music app on your tablet.
  • the mobile phone runs the program locally on the mobile phone to control the "music" application on the smart speaker.
  • the goal of. That is to say, the user can pull up the control interface of the "music” application on the mobile phone, and the user can remotely operate the "music” application on the smart speaker by operating the control interface on the mobile phone, so that the smart speaker can respond accordingly.
  • the mobile phone displays the interface 630 shown in (b) of FIG. 6B , that is, Users can pull up the control interface of the "Music” application on their mobile phones and control the smart speaker to start playing music.
  • the smart speaker in response to the operation of the play control 621 in the interface 620, the smart speaker also invokes the relevant hardware (such as a speaker, etc.) to launch the "music" application to play music. In this way, the user can operate the "music" application on the smart speaker on the mobile phone to achieve the purpose of controlling the smart speaker to play music.
  • the example shown in the above scenario 3 is also applicable to the search and sorting of music FA services. That is to say, if the user enters "music" in the search box, the search results can also include the For the FA service related to "music” and the FA service related to "music” on the tablet, the user can also operate the FA service on the speaker on the mobile phone, and pull up the PA service related to the music on the speaker.
  • the example shown in the above-mentioned scenario 1 which is not shown one by one with a diagram.
  • the specific method for the mobile phone to search for the application information or service information related to the keyword from the mobile phone and other devices according to the search keyword may be any one or more of the following methods. combination.
  • the mobile phone can obtain the labels of N candidate objects according to the keywords, and then calculate the semantic similarity between the keywords and the labels of the N candidate objects; according to the size of the semantic similarity, determine the semantic similarity greater than the set threshold.
  • Method 2 The mobile phone can obtain the tags of N candidate objects according to the keywords, and then calculate the word frequency distribution of the keywords in the tags of the N candidate objects.
  • the mobile phone is higher than the search results of other devices. That is, devices with more applications or services related to keywords are ranked higher.
  • the application or service is ranked relatively low.
  • the application or service related to the keyword only appears in some devices (such as on the smart screen in the living room), the application or service is ranked higher.
  • the mobile phone can obtain the device status of the mobile phone and other devices, such as the power supply type of the device, the screen size of the device, the available computing resources of the device, the correlation between the device performance and the target object, and the prioritization of obtaining applications or services. Then, the applications or services in the search results are ranked according to the device state and the prior knowledge constraints related to the application or service.
  • the prior knowledge constraints related to the application or service may include that the application or service is preferentially run on a large-screen device, the application or service is preferentially run on a plug-in type device, and the application or service is preferentially run on a device with strong computing power. Or apps or services run preferentially on devices with good audio playback performance.
  • the search results obtained by sorting according to the third method may have the following characteristics:
  • Feature 1 if a certain device is being used by a user, the ranking of applications or services related to keywords on the device is higher. For example, if the user is browsing the video information on the smart screen in the living room, if the user searches for some applications or services related to video information through the mobile phone, the applications or services related to the large screen will be ranked higher in the search results. In this way, it helps to save the startup time of the application or service on the device, and the large screen makes it easier for users to view information.
  • the second feature is that if an application or service has a better use experience in device A, the search information of device A is ranked higher. Taking the application of music playback as an example, when there are applications of speakers, large screens, mobile phones, and tablets in the search results, the applications on the speakers are ranked higher.
  • the third feature is that if a certain type of application or service consumes a lot of power, the related applications or services on plug-in devices that can support high power consumption are ranked higher. Taking games as an example, when the mobile phone, tablet, and large screen are supported at the same time, the game applications on the large screen are ranked higher, because the large screen is usually a plug-in device, and there is no need to consider the power consumption issue.
  • the fourth characteristic is that a certain type of application or service needs to occupy higher computing resources when used, and the related applications or services on the device with relatively sufficient computing resources are ranked higher.
  • the mobile phone can obtain the device status of the mobile phone and other devices, and obtain the prior knowledge constraints related to the application or service, and then according to the device status and the prior knowledge constraints related to the application or service, on the one hand, according to the keyword and The semantic similarity or word frequency distribution between the tags of the application or service determines the first weight corresponding to the application or service respectively.
  • the second weight corresponding to the application or service is determined; then, according to the first weight and the second weight, the search results are applications or services.
  • the search result includes application tags and/or service tags of multiple devices corresponding to the same application or service, it is necessary to match the state of the device with the constraints of prior knowledge related to the application or service. degree, to sort application tags and/or service tags for multiple devices.
  • the "Welink-Video FA " service is searched on mobile phones, tablets and smart screens. Because the prior knowledge related to the "Welink-Video FA " application or service is restricted by the priority of large screens and plug-in devices, smart The "Welink-Video FA " app or service tab on the screen is higher in the search results.
  • an embodiment of the present application provides an information sorting method, and the method can be applied to a device in a distributed system. Specifically, as shown in FIG. 7 , the method includes the following steps.
  • Step 701 The electronic device receives a search request from a user, where the search request includes a keyword input by the user.
  • the search request may be content input by the user through touch, or content input through a voice command.
  • the electronic device in the process of the user inputting content, can use the information input by the user to perform broad keyword matching, and after the user completes the input of the keyword, the electronic device can perform keyword precision based on the keyword input by the user. match.
  • Step 702 the electronic device obtains the labels of the N candidate objects according to the keywords, and calculates the semantic similarity between the keywords and the labels of the N candidate objects.
  • the electronic device may calculate the semantic similarity between the search term and the multiple candidate object programs respectively according to the deep neural network model.
  • the deep neural network model may be a machine model generated in advance by training on the training corpus obtained from the candidate object.
  • the electronic device obtains the detailed information of the L candidate objects from the database, then extracts the original keywords from the detailed information of the L candidate objects, and performs semantic analysis on the original keywords , get the labels of L candidate objects from the parsing result.
  • the detailed information of the application includes, but is not limited to, the title of the application, the description text of the application, the comment information of the application, the recommendation words of the application, the latest update characteristics of the application, and other information.
  • the label of the application includes, but is not limited to, information such as the name of the application, the category to which the application belongs, and the characteristics of the application.
  • the detailed information of the service includes, but is not limited to, the title of the service, the description text of the service, the comment information of the service, the recommended words of the service, and the latest update features of the service and other information.
  • the label of the service includes, but is not limited to, information such as the name of the service, the category of the service, and the characteristics of the service.
  • the detailed information of the candidate objects may be segmented first. For example, you can build a custom dictionary, and match the Chinese character string to be analyzed with the entry in the custom dictionary according to the preset strategy. If a certain string can be found in the custom dictionary, the match is successful (that is, a word is recognized ).
  • the string matching word segmentation method can be divided into forward matching and reverse matching. According to the situation of priority matching of different lengths, the string matching word segmentation method can be divided into maximum (longest) matching and minimum (shortest) matching. , select a specific word segmentation method according to the needs.
  • stop words, invalid words, etc. can be filtered out.
  • a regular filtering rule can be constructed to filter out words matching the regular filtering rule. For example, by constructing regular filtering rules: "contact information", "mail”, "phone”, etc., the contact information, email, phone and other information in the detailed information of the object can be filtered out.
  • the obtained words can be screened, for example, part of speech screening is performed, and verbs, nouns, etc. are selected to obtain at least one keyword.
  • the term frequency (TF) of each original keyword may be calculated, and the term frequency represents the frequency of occurrence of a certain word in the document, and calculate the term frequency (TF) of each original keyword.
  • the inverse document frequency (IDF) of each keyword is calculated by dividing the total number of documents in the database by the number of documents containing the word, and then taking the logarithm of the obtained quotient.
  • the product of the word frequency and the reverse document frequency is used as the TF-IDF value of the corresponding keyword, and the keyword whose TF-IDF value is greater than the preset threshold is selected as the original keyword.
  • the preset threshold can be customized according to actual needs.
  • the electronic device uses the semantic parsing model to perform semantic parsing on the original keywords to generate the tags of the objects.
  • Step 703 the electronic device determines, from the labels of the N candidate objects, the labels of the M candidate objects corresponding to the semantic similarity greater than the set threshold.
  • the labels of the K candidate objects correspond to the target objects of the same attribute installed on the K devices; M ⁇ N, M, N and K are positive integers greater than or equal to 2.
  • the target object with the same attribute on the K devices can be the target object with the same name on the K devices, such as WeChat on mobile phones and tablets Application, or, the target object of the same attribute on K devices can be the target object of the same supplier on K devices, such as mobile phone Apps and Douyin on Tablet App for the same vendor ByteDance or, the target object of the same attribute on K devices can be the target object of the same installation package on K devices, for example, WeChat on mobile phones and tablets
  • the installation package name of the application is the same.
  • the target object of the same attribute on the K devices may be the target object of the same function on the K devices, for example, the mobile phone Apps and Douyin on Tablet All apps have a short video sharing function.
  • the labels of the M candidate objects include the label of the "Welink” object on the mobile phone, the label of the "Welink” object on the smart screen, and the label of the "Welink” object on the tablet.
  • Step 704 the electronic device sorts the K candidate objects according to the semantic similarity between the keywords and the labels of the K candidate objects, and the device states of the K devices.
  • the electronic device may determine the first weight and the second weight respectively corresponding to the K candidate objects, and sort the K candidate objects according to the first weight and the second weight.
  • the electronic device determines that the greater the semantic similarity between the keyword and the labels of the K candidate objects, the greater the first weight; on the contrary, the smaller the semantic similarity is, the lower the first weight.
  • the mobile phone determines the first weight of the "Welink” service on the mobile phone as K1 according to the semantic similarity between the keyword and the label of the "Welink” service on the mobile phone;
  • the first weight of the “Welink” service on the smart screen is determined to be K2;
  • the mobile phone determines the “Welink” service on the tablet according to the semantic similarity between the keyword and the label of the “Welink” service on the tablet.
  • the first weight is K3.
  • the electronic device determines the second weights corresponding to the K candidate objects according to the matching degree between the prior knowledge related to the target object and the device states of the K devices.
  • the constraints of the prior knowledge related to the target object include at least one of the following conditions: the target object is preferentially run on a large-screen device, the target object is preferentially run on a plug-in type device, and the target object is preferentially run on a computer with strong computing power. Run on the device, and the target object preferentially runs on the device with good audio playback performance.
  • the target object is the "Welink-Video FA " service in the above scenario 1.
  • the "Welink-Video FA " service is a kind of office conference software. Therefore, the priori Knowledge constraints include prioritizing running on large-screen devices. For another example, suppose the target object is "music" in scene 3, because "music" is a kind of music software, therefore, the constraints of prior knowledge related to the "music” service include giving priority to devices with good audio playback performance. run on.
  • the constraint condition of the prior knowledge related to the target object may be a condition preset by the developer, the electronic device may obtain the constraint condition while downloading the application or service from the server, or the electronic device may periodically download the application or service from the cloud.
  • the server obtains the constraint, which is not limited in this embodiment of the present application.
  • the state of the device includes the power supply type of at least one of the following states, the screen size of the device, the available computing resources of the device, and the correlation between the device performance and the target object.
  • the power supply type of the mobile phone is usually a battery
  • the power supply type of the smart screen in the living room is the plug-in type
  • the audio playback performance of the speaker is more related to music applications or services.
  • the constraints of the prior knowledge of the Welink-Video FA service are to run on a large screen and run on a plug-in device first.
  • the device status of the mobile phone is battery-powered, and the screen size is 7 inches; the living room
  • the device status of the smart screen is plug-in power supply type, and the screen size is 55 inches;
  • the device status of the tablet is battery power supply type, and the screen size is 7.9 inches.
  • the mobile phone and the Welink-Video FA service are based on the device status of the mobile phone.
  • the second weight of the "Welink-Video FA " service on the mobile phone is determined to be L1; the mobile phone matches the constraints of the prior knowledge of the Welink-Video FA service based on the device status of the smart screen in the living room and the Welink-Video FA "service. determine the second weight of the “Welink-Video FA ” service on the mobile phone as L2; the mobile phone determines the “Welink-Video FA” service on the mobile phone according to the matching degree of the device state of the tablet and the constraints of the prior knowledge of the Welink-Video FA ” service.
  • the second weight of the FA " service is L3.
  • the manner in which the electronic device determines the second weights respectively corresponding to the K candidate objects may be any one of the following manners or a combination of multiple manners.
  • Mode 1 When the constraint condition of the prior knowledge related to the target object is that the target object preferentially runs on the plug-in type device, determine the candidate object corresponding to the device supporting the plug-in type among the K devices corresponding to the K candidate objects.
  • the second weight of is greater than the second weight of the corresponding candidate object of the device that does not support the plug-in type.
  • the search result of the above mobile phone includes the "Welink-Video FA " service of the smart screen in the living room, the ranking of "Welink-Video FA " on the smart screen in the living room is higher in the column of all devices, and The "Welink-Video FA " service on a mobile phone or tablet is on the back. Because the smart screen in the living room is a plug-in device that can support high power consumption, there is basically no problem of insufficient power.
  • Method 2 When the constraint condition of the prior knowledge related to the target object is that the target object preferentially runs on a large-screen device, determine the second weight of the candidate object corresponding to the device with the larger screen among the K devices corresponding to the K candidate objects. bigger.
  • the search result includes the "Welink-Video FA " service of the smart screen in the living room
  • the ranking of "Welink-Video FA " on the smart screen in the living room is higher in the column of all devices, while the mobile phone or tablet is ranked higher in the column of all devices.
  • the "Welink-Video FA " service on the Internet is behind. This is because the smart screen in the living room is a large-screen device, which is more convenient for multiple users to view information on the large screen at the same time.
  • Mode 3 When the constraint condition of the prior knowledge related to the target object is that the target object preferentially runs on a device with strong computing power, determine the candidate object corresponding to the device with stronger computing power among the K devices corresponding to the K candidate objects.
  • the second weight is larger.
  • the search result includes the "AI photo” service on the smart screen in the living room
  • the "AI photo” service on the smart screen in the living room is ranked higher in the column of all devices
  • the "AI photo” on the smart screen in the living room is ranked higher in the column of all devices.
  • “Photo” service is on the back. This is because the smart screen in the living room is a device with strong processing power, and the data processing efficiency is higher.
  • Mode 4 When the constraint condition of the prior knowledge related to the target object is that the target object preferentially runs on a device with good audio playback performance, determine the second device with the better audio playback performance among the K devices corresponding to the K candidate objects. the greater the weight.
  • the search result includes the "music" service of the smart speaker
  • the "music" on the smart speaker is ranked higher in the device column
  • the "music" service on the mobile phone or tablet is ranked by back. This is because smart speakers have good audio playback capabilities and are devices that are strongly related to the "music" service.
  • the electronic device may calculate the product of the first weight and the second weight, and sort the K candidate objects according to the size of the product, for example, the larger the product, the higher the ranking, or the smaller the product, The higher the order.
  • the electronic device may also adjust the product of the first weight and the second weight in combination with the recommendation result of the situational intelligence in the device and the user's usage habits and other information, and use the adjusted second weight and The product of the first weights to sort the K candidates.
  • the embodiment of the present application may further include step 705, where the electronic device displays the sorted K candidate objects in a preset recommendation interface, wherein the first weight and the second The higher the product of weights, the higher the ranking of candidates.
  • the “Welink-Video FA ” service and the “Welink-Chat FA ” service of the smart screen in the living room are displayed in the recommendation result of the column of all devices on the negative one-screen interface 600 The most advanced, followed by the tablet “Welink-Video FA " service, and finally the mobile phone's "Welink-Video FA " service.
  • the electronic device can also obtain the device label from the database or server, and then calculate the similarity between the keyword and the device label, so as to determine the corresponding K devices according to the similarity.
  • the third weight of the K candidates Further, the electronic device may sort the K candidate objects according to the first weight, the second weight and the third weight.
  • the labels of the smart screen in the living room include video, conference, etc.
  • the labels of the mobile phone include making calls, surfing the Internet, etc.
  • the mobile phone can obtain the labels of the above-mentioned devices from the cloud server.
  • the label can be preset by the developer, or can be If the user actively marks and then uploads it to the cloud server, this application is not limited.
  • an embodiment of the present application provides a method flowchart as shown in FIG. 8 , and the method includes the following steps.
  • Step 801 The electronic device receives a search request from a user, where the search request includes a keyword input by the user.
  • step 701 For details, refer to step 701 above.
  • Step 802 During the process of receiving the input word by the electronic device, the electronic device can determine in real time whether the user ends the input, if not, execute step 803a; otherwise, execute step 803b.
  • the mobile phone determines whether the input will be finished during the process of receiving each character.
  • Step 803a if not, the electronic device may perform broad matching on the received keyword, and calculate the similarity between the keyword and the tag of the candidate object.
  • the electronic device performs broad matching on the received keyword "We", and calculates the similarity between the keyword “We” and the tag of the candidate object.
  • Step 803b if yes, the electronic device can accurately match the received keyword, calculate the similarity between the keyword and the label of the candidate object, and calculate the similarity between the constraints of the prior knowledge related to the candidate object and the state of the device Spend.
  • Step 804 the electronic device determines K candidate objects in the labels of the M candidate objects corresponding to the semantic similarity greater than the set threshold, and the K candidate objects correspond to the target objects of the same attribute.
  • Step 805 for any candidate object among the K candidate objects, the electronic device determines the first weight according to the similarity between the keyword and the label of the candidate object, and the electronic device determines the first weight according to the constraints of the prior knowledge related to the candidate object.
  • the similarity with the state of the device determines the second weight, and the electronic device determines the third weight according to the similarity between the keyword and the tag of the device.
  • Step 806 the electronic device sorts each candidate object according to the first weight, the second weight and the third weight.
  • the search results after such sorting have the following characteristics: an application or service whose label of the application or service is semantically similar to the keyword, the application or service is ranked higher; the label of the device and the keyword The search result of the device with closer semantics is higher in the ranking; the state of the device matches the constraints of the prior knowledge related to the candidate object better, the search result of the device is higher in the ranking.
  • an embodiment of the present application further provides a method for sorting information. Specifically, as shown in FIG. 9 , the method includes the following steps.
  • Step 901 The electronic device receives a search request from a user, where the search request includes a keyword input by the user.
  • the search request may be content input by the user through touch, or content input through a voice command.
  • the electronic device in the process of the user inputting content, can use the information input by the user to perform broad keyword matching, and after the user completes the input of the keyword, the electronic device can perform keyword precision based on the keyword input by the user. match.
  • Step 902 the electronic device obtains the labels of the N candidate objects according to the keywords, and calculates the semantic similarity between the keywords and the labels of the N candidate objects.
  • Step 903 the electronic device determines, from the labels of the N candidate objects, the labels of the M candidate objects corresponding to the semantic similarity greater than the set threshold.
  • the labels of the M candidate objects correspond to the target objects with different attributes installed on the K devices; M ⁇ N, M, N and K are positive integers greater than or equal to 2.
  • target objects with different attributes can be target objects with different names, such as WeChat Apps and Alipay Application, or, target objects with different attributes can be target objects of different suppliers, such as Apps and Kuaishou
  • the applications are applications of different suppliers; or, the target objects with different attributes can be the target objects of different installation packages, for example, WeChat
  • the name of the installation package of the application is different from that of the Alipay application.
  • target objects with different properties can be targeted for different functions, for example, Apps and WeChat Apps function differently.
  • Step 904 the electronic device sorts the M candidate objects according to the semantic similarity between the keywords and the labels of the M candidate objects, and the device states of the M devices.
  • the electronic device may determine the first weight and the second weight corresponding to the M candidate objects respectively, and sort the M candidate objects according to the first weight and the second weight.
  • the electronic device determines that the greater the semantic similarity between the keyword and the labels of the M candidate objects, the greater the first weight; on the contrary, the smaller the semantic similarity is, the lower the first weight.
  • the electronic device determines the second weights corresponding to the M candidate objects according to the matching degree between the prior knowledge related to the M candidate objects and the device states of the K devices.
  • the constraints of the prior knowledge related to the M candidate objects include at least one of the following conditions: the candidate object is preferentially run on a large-screen device, the candidate object is preferentially run on a plug-in type device, and the candidate object is preferentially run on a computing power Run on devices with strong audio performance, and candidates run on devices with good audio playback performance.
  • the candidate object is the "Baidu Map" service in the above-mentioned second scenario, which is a kind of navigation software. Therefore, the constraints of the prior knowledge related to the "Baidu Map” service include priority in It runs on the in-vehicle device, so the “Baidu Map” service has the highest match with the device status of the in-vehicle device.
  • the manner in which the electronic device determines the second weights respectively corresponding to the M candidate objects may be any one of the following manners or a combination of multiple manners.
  • Manner 1 For any candidate object among the M candidate objects, when the constraint condition of the prior knowledge related to the candidate object is to run on a plug-in type device preferentially, the electronic device determines whether the device in which the candidate object is located supports or not. The device of the plug-in type determines the second weight, wherein the second weight in the case where the device in which the candidate object is located is a device supporting the plug-in type is higher than the second weight in the case where the device in which the candidate object is located is a device supporting the battery type Weights.
  • the search result of the mobile phone in the above scenario 2 includes the "Baidu Map” service of the vehicle terminal
  • the "Baidu Map” on the vehicle terminal is ranked higher in the column of all devices
  • the "Baidu Map” on the mobile phone is ranked higher in the column of all devices.
  • the Maps service is on the back. Because the vehicle terminal is a plug-in device that can support high power consumption, there is basically no problem of insufficient power.
  • Mode 2 For any candidate object among the M candidate objects, when the constraint condition of the prior knowledge related to the candidate object is that the candidate object preferentially runs on a large-screen device, the electronic device determines the size of the screen in the device where the candidate object is located.
  • the second weight wherein the second weight when the device where the candidate object is located is a large-screen device is higher than the second weight when the device where the candidate object is located is a small-screen device.
  • Mode 3 For any candidate object among the M candidate objects, when the constraint condition of the prior knowledge related to the candidate object is that the candidate object is preferentially run on a device with strong computing power, the electronic device will be based on the device in which the candidate object is located. Whether the computing resources are sufficient determines the second weight, wherein the second weight when the device where the candidate object is located has sufficient computing resources is higher than the second weight when the device where the candidate object is located has insufficient computing resources.
  • Mode 4 For any candidate object among the M candidate objects, when the constraint condition of the prior knowledge related to the candidate object is that the candidate object is preferentially run on a device with good audio playback performance, the electronic device is based on the device in which the candidate object is located.
  • the audio playback performance determines the second weight, wherein the second weight when the device where the candidate object is located has good audio playback performance is higher than the second weight when the device where the candidate object is located has poor audio playback performance.
  • the embodiment of the present application may further include step 905, where the electronic device displays the sorted M candidate objects on a preset recommendation interface.
  • the electronic device can also obtain the device label from the database or server, and then calculate the similarity between the keyword and the device label, so as to determine the corresponding K devices according to the similarity.
  • the third weight of the K candidates Further, the electronic device may sort the K candidate objects according to the first weight, the second weight and the third weight.
  • the labels of the smart screen in the living room include video, conference, etc.
  • the labels of the mobile phone include making calls, surfing the Internet, etc.
  • the mobile phone can obtain the labels of the above-mentioned devices from the cloud server.
  • the label can be preset by the developer, or can be If the user actively marks and then uploads it to the cloud server, this application is not limited.
  • the embodiment of the present application provides a method flowchart as shown in FIG. 10 , and the method includes the following steps.
  • Step 1001 The electronic device receives a search request from a user, where the search request includes a keyword input by the user.
  • step 701 For details, refer to step 701 above.
  • Step 1002 During the process of receiving the input word by the electronic device, the electronic device can determine in real time whether the user ends the input, and if not, execute step 1003a; otherwise, execute step 1003b.
  • the mobile phone determines whether the input will be finished during the process of receiving each character.
  • Step 1003a if not, the electronic device can perform broad matching on the received keywords, and calculate the similarity between the keywords and the tags of the candidate objects.
  • the electronic device performs broad matching on the received keyword "Guide”, calculates the similarity between the keyword “Guide” and the label of the application, and calculates the similarity between the keyword “Guide” and the label of the device. similarity.
  • Step 1003b if yes, the electronic device can accurately match the received keyword, calculate the similarity between the keyword and the label of the candidate object, and calculate the similarity between the constraints of the prior knowledge related to the candidate object and the state of the device Spend.
  • the electronic device performs an exact match on the received keyword "navigation”, calculates the similarity between the keyword “navigation” and the label of the application, and calculates the similarity between the keyword “navigation” and the label of the device. similarity.
  • Step 1004 the electronic device determines the labels of the M candidate objects corresponding to the semantic similarity greater than the set threshold.
  • Step 1005 for any candidate object among the M candidate objects, the electronic device determines the first weight according to the similarity between the keyword and the label of the candidate object, and the electronic device determines the first weight according to the constraints of the prior knowledge related to the candidate object.
  • the similarity with the state of the device determines the second weight, and the electronic device determines the third weight according to the similarity between the keyword and the tag of the device.
  • Step 1006 the electronic device sorts each candidate object according to the first weight, the second weight and the third weight.
  • the search results after such sorting have the following characteristics: an application whose label of an application or service is more semantically similar to the keyword, the application or service is ranked higher; the label of the device is more semantically similar to the keyword.
  • the search results of similar devices are higher in the ranking; the state of the device matches the constraints of the prior knowledge related to the candidate object, and the search results of the device are higher in the ranking.
  • the embodiments of the present application can comprehensively sort applications or services according to the device status, constraints of pre-verified knowledge related to applications or services, and the relevance of user input content, so as to achieve precise sorting of applications or services.
  • the constraints of the pre-verified knowledge related to the target object and the matching of the device state can be used to achieve the purpose of accurately sorting the applications or services corresponding to the same target object on different devices.
  • Such sorting results can more accurately match the application or service that the user wants to search, which helps to improve search efficiency and user experience.
  • the embodiments of the present application disclose an electronic device.
  • the electronic device may include: a touch screen 1101 , wherein the touch screen 1101 includes a touch panel 1106 and a display screen 1107 one or more processors 1102; memory 1103; one or more application programs (not shown); wherein the one or more computer programs 1104 are stored in the aforementioned memory 1103 and configured to be executed by the one or more processors 1102, the one or more computer programs 1104 include instructions that can be used to perform the execution as shown in FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 for each step in the corresponding embodiment.
  • Embodiments of the present application further provide a computer-readable storage medium, where computer instructions are stored in the computer-readable storage medium.
  • the computer instructions When the computer instructions are executed on an electronic device, the electronic device executes the above-mentioned related method steps to achieve the above-mentioned embodiments. information sorting method.
  • Embodiments of the present application also provide a computer program product, which, when the computer program product runs on a computer, causes the computer to execute the above-mentioned relevant steps, so as to implement the information sorting method in the above-mentioned embodiments.
  • the embodiments of the present application also provide an apparatus, which may specifically be a chip, a component or a module, and the apparatus may include a connected processor and a memory; wherein, the memory is used for storing computer execution instructions, and when the apparatus is running, The processor can execute the computer-executed instructions stored in the memory, so that the chip executes the information sorting method in the above method embodiments.
  • the electronic devices, computer storage media, computer program products or chips provided in the embodiments of the present application are all used to execute the corresponding methods provided above. Therefore, for the beneficial effects that can be achieved, reference may be made to the corresponding methods provided above. The beneficial effects of the method are not repeated here.
  • the disclosed apparatus and method may be implemented in other manners.
  • the apparatus embodiments described above are only illustrative.
  • the division of modules or units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or It may be integrated into another device, or some features may be discarded, or not implemented.
  • the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.
  • Units described as separate components may or may not be physically separated, and components shown as units may be one physical unit or multiple physical units, that is, may be located in one place, or may be distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium.
  • a readable storage medium including several instructions to make a device (which may be a single chip microcomputer, a chip, etc.) or a processor (processor) to execute all or part of the steps of the methods in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read only memory (ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program codes.

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Abstract

本申请提供了一种信息排序方法及电子设备，涉及终端人工智能领域，该方法包括：电子设备先根据用户的搜索请求中的关键词进行搜索，获取N个候选对象的标签，候选对象可以为候选应用和/或候选服务，然后计算关键词与N个候选对象的标签之间的语义相似度，从N个候选对象的标签中，确定大于设定阈值的语义相似度对应的M个候选对象的标签。因M个候选对象的标签中有K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象，所以电子设备可以根据关键词与K个候选对象的标签之间的语义相似度，以及K个设备的设备状态，对K个候选对象进行排序，显示包括该排序结果的推荐界面。这样有助于提升搜索效率，改善用户体验。

Description

一种信息排序方法及电子设备
相关申请的交叉引用
本申请要求在2020年11月30日提交中国专利局、申请号为202011375972.0、申请名称为“一种信息排序方法及电子设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及终端技术领域，尤其涉及一种信息排序方法及电子设备。
背景技术
随着智能终端的发展，一个用户拥有多个终端的情况变得越来越普及，比如一个用户可同时拥有智能手机、平板电脑以及智能手表三个终端，三个终端可能分别支持不同的功能。目前，鸿蒙(Harmony)操作系统(operating system，OS)是一款“面向未来”、面向全场景(移动办公、运动健康、社交通信、媒体娱乐等)的分布式操作系统。在传统的单设备系统能力的基础上，Harmony OS提出了基于同一套系统能力、适配多种终端形态的分布式理念，能够支持多种电子设备。
其中，Harmony OS中应用层可以包括应用和服务，服务指的是特性能力(feature ability，FA)服务和基本能力(particle ability，PA)服务。其中应用是由一个或多个FA服务和/或PA服务组成。其中，FA服务有UI界面，提供与用户交互的能力；而PA服务无UI界面，提供后台运行任务的能力以及统一的数据访问抽象。基于FA/PA开发的应用，能够实现特定的业务功能，支持跨设备调度与分发，为用户提供一致、高效的应用体验。基于FA/PA服务的应用具有数据量小，不需要下载安装就可以使用的特点，实现了应用“触手可及”的梦想，因此有着非常广阔的使用前景。基于Harmony OS这一特点，在一个设备进行搜索就能够搜索得到多个设备上的相关应用标签或者服务标签，如果仍基于传统的语义分析的方式对搜索结果进行排序，则很可能因应用或服务数量太多，导致用户无法及时准确地查找到想要的应用或想要的服务，影响用户的使用体验。
发明内容
本申请提供一种信息排序方法及电子设备，用以解决因应用或服务数量太多，导致用户无法及时准确地查找到想要的应用或想要的服务。
第一方面，本申请实施例提供一种信息排序方法，该方法可以应用于电子设备，该方法包括：电子设备接收用户的搜索操作，该搜索操作中包括用户输入的关键词，响应于该搜索操作，显示推荐界面，该推荐界面中的候选对象中有K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象。其中，K个候选对象的排序是根据关键词与K个候选对象的标签之前的语义相似度，以及K个设备的设备状态确定的。
本申请实施例中，与现有的技术相比，该方法可以从电子设备和与电子设备连接的其它设备上查找到多个候选对象，并且将多个候选对象中更相关设备上的应用或服务靠前排 序，方便用户查找，可以提升搜索效率，改善用户体验。
在一种可能的设计中，在显示推荐界面之前，可以按照如下方式实现对K个候选对象的排序，具体地，电子设备可以根据所述关键词，获取N个候选对象的标签，以及计算关键词与N个候选对象的标签之间的语义相似度；然后从N个候选对象的标签中，确定大于设定阈值的语义相似度所对应的M个候选对象的标签，因M个候选对象的标签中有所述K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象；M≤N，M和N为大于或等于2的正整数；因此，根据关键词与K个候选对象的标签之间的语义相似度，以及K个设备的设备状态，可以对K个候选对象进行排序。
本申请实施例中，与现有的技术相比，现有的搜索结果通常是从设备本地或者网络侧获取的，而本申请可以从电子设备和与电子设备连接的其它设备上查找到候选对象，而且该方法更针对搜索结果中对应同一属性的目标对象的候选对象的排序，在排序过程中结合设备状态，从而将更相关的设备的应用或服务靠前排序，方便查找，可以提升搜索效率，改善用户体验。
在一种可能的设计中，K个设备的设备状态可以包括如下状态中的至少一个：设备的供电类型、设备的屏幕大小、设备的可用计算资源、设备性能与目标对象的相关性。如有的音箱是插电类型的设备，智能电视是插电类型的设备，还是大屏设备。音箱的音频播放性能与音乐类应用强相关，音箱的音频播放性能与视频类应用弱相关。
本申请实施例中，通过考虑设备状态与目标对象之间的关联关系，可以实现将更相关设备上的应用或服务靠前排序，方便查找，可以提升搜索效率，改善用户体验。
在一种可能的设计中，K个设备上的同一属性的目标对象可以为K个设备上的同一名称的目标对象，例如手机和平板上的微信
Figure PCTCN2021134377-appb-000001
应用，或者，K个设备上的同一属性的目标对象为K个设备上的同一供应商的目标对象，例如手机的
Figure PCTCN2021134377-appb-000002
应用与平板上抖音
Figure PCTCN2021134377-appb-000003
应用可以为同一供应商字节跳动
Figure PCTCN2021134377-appb-000004
的应用；或者，K个设备上的同一属性的目标对象可以为K个设备上的同一安装包的目标对象，例如，手机和平板上的微信
Figure PCTCN2021134377-appb-000005
应用的安装包名称相同。或者，K个设备上的同一属性的目标对象可以为K个设备上的同一功能的目标对象，例如，手机的
Figure PCTCN2021134377-appb-000006
应用与平板上抖音
Figure PCTCN2021134377-appb-000007
应用均具有短视频分享功能。
在一种可能的设计中，电子设备根据关键词与K个候选对象的标签之间的语义相似度，以及K个设备的设备状态，对K个候选对象进行排序，包括：电子设备根据关键词与K个候选对象的标签之间的语义相似度，确定K个候选对象分别对应的第一权重；以及根据目标对象相关的先验知识的约束条件，与K个设备的设备状态之间的匹配度，确定K个候选对象分别对应的第二权重；然后根据第一权重和第二权重，对K个候选对象进行排序。例如，一种可能的实现方式可以是根据第一权重和第二权重的乘积对K个候选对象进行排序。
本申请实施例中，一方面，电子设备根据关键词与K个候选对象的标签之间的语义相似度，确定K个候选对象分别对应的第一权重；另一方面，根据目标对象相关的先验知识的约束条件与K个设备的设备状态之间的匹配度，确定K个候选对象分别对应的第二权重，这样，根据第一权重和第二权重，可以对K个候选对象进行综合排序。这样的排序结果可以更加精准地匹配用户想要搜索的应用或服务，有助于提升搜索效率，改善用户体验。
在一种可能的设计中，上述目标对象相关的先验知识的约束条件可以包括如下条件中的至少一个：目标对象优先在大屏设备上运行、目标对象优先在插电类型的设备上运行、 目标对象优先在计算能力强的设备上运行，以及目标对象优先在音频播放性能佳的设备上运行。示例性地，视频类FA服务或视频类应用优先在大屏设备上运行，电视类FA服务或电视类应用优先在插电设备上运行，音乐类FA服务或音乐类应用优先在音箱上运行。
本申请实施例中，先验知识的约束条件可以预先人为设置，通过上述条件可以建立应用或服务与设备状态之间的关联关系，从而有助于利用设备状态进行应用或服务的排序。
在一种可能的设计中，电子设备可以采用如下任意一种方式确定第二权重：
当所述目标对象相关的先验知识的约束条件为所述目标对象优先在插电类型的设备上运行时，确定所述K个候选对象对应的K个设备中支持插电类型的设备的对应的候选对象的第二权重大于不支持插电类型的设备的对应的候选对象的第二权重；
或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在大屏设备上运行时，确定所述K个候选对象对应的K个设备中屏幕越大的设备对应的候选对象的第二权重越大；
或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在计算能力强的设备上运行时，确定所述K个候选对象对应的K个设备中计算能力越强的设备对应的候选对象的第二权重越大；
或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在音频播放性能佳的设备上运行时，确定所述K个候选对象对应的K个设备中音频播放性能越佳的设备的第二权重越大。
在一种可能的设计中，电子设备在预设的推荐界面中所显示的K个候选对象的排序方式遵循：第一权重和第二权重的乘积越大的候选对象的排序越靠前，反之，第一权重和第二权重的乘积越小的候选对象的排序越靠后。
本申请实施例中，按照上述方法推荐的应用或服务的排序结果更加精准地匹配用户想要搜索的应用或服务，有助于提升搜索效率，改善用户体验。
在一种可能的设计中，电子设备根据所述关键词，获取N个候选对象的标签，包括：从数据库获取所述K个设备上的L个候选对象的详情信息；从L个候选对象的详情信息中提取原始关键词，对所述原始关键词进行语义解析，从解析结果中获取L个候选对象的标签，根据所述关键词与所述L个候选对象的标签的匹配度，从L个候选对象的标签中获取N个候选对象的标签。其中，应用的详情信息包括但不限于：应用的标题、应用的描述文本、应用的评论信息、应用的推荐语、应用的最近更新特性等信息。应用的标签包括但不限于：应用的名称、应用所属类别、应用的特性等信息。服务的详情信息包括但不限于：服务的标题、服务的描述文本、服务的评论信息、服务的推荐语、服务的最近更新特性等信息。服务的标签包括但不限于：服务的名称、服务所属类别、服务的特性等信息。
第二方面，本申请实施例提供的一种电子设备，包括：一个或多个处理器和存储器，其中存储器中存储有程序指令，当程序指令被设备执行时，实现本申请实施例上述各个方面以及各个方面涉及的任一可能设计的方法。
第三方面，本申请实施例提供的一种芯片，所述芯片与设备中的存储器耦合，使得所述芯片在运行时调用所述存储器中存储的程序指令，实现本申请实施例上述各个方面以及各个方面涉及的任一可能设计的方法。
第四方面，本申请实施例的一种计算机可读存储介质，该计算机可读存储介质存储有程序指令，当所述程序指令在电子设备上运行时，使得设备执行本申请实施例上述各个方 面以及各个方面涉及的任一可能设计的方法。
第五方面，本申请实施例的一种计算机程序产品，当所述计算机程序产品在电子设备上运行时，使得所述电子设备执行实现本申请实施例上述各个方面以及各个方面涉及的任一可能设计的方法。
另外，第二方面至第五方面中任一种可能设计方式所带来的技术效果可参见方法部分相关中不同设计方式所带来的技术效果，此处不再赘述。
附图说明
图1为本申请实施例提供的一种手机结构示意图；
图2为本申请实施例提供的一种安卓操作系统结构示意图；
图3为本申请实施例提供的一种应用场景示意图；
图4A至图4E为本申请实施例提供的另一组界面示意图；
图5A为本申请实施例提供的另一种应用场景示意图；
图5B为本申请实施例提供的另一组界面示意图；
图6A至图6B为本申请实施例提供的界面示意图；
图7为本申请实施例提供的另一种信息排序方法流程示意图；
图8为本申请实施例提供的另一种信息排序方法流程示意图；
图9为本申请实施例提供的另一种信息排序方法流程示意图；
图10为本申请实施例提供的另一种信息排序方法流程示意图；
图11为本申请实施例提供的一种电子设备结构示意图。
具体实施方式
为了使本申请实施例的目的、技术方案和优点更加清楚，下面将结合说明书附图以及具体的实施方式对本申请实施例中的技术方案进行详细的说明。
目前，电子设备虽然可以通过用户输入的关键词，进行语义匹配得到相关的应用的搜索结果，并根据语义相似度进行排序。但受限于电子设备所安装的安卓操作系统，上述搜索结果并不涉及其它设备上的应用信息，所以电子设备的搜索结果界面上只展示自身设备上与输入的关键词相关的应用信息。可见，目前电子设备的应用搜索方式尚不涉及对多个设备上应用信息或服务信息的搜索和排序。
考虑到在鸿蒙(Harmony)操作系统(operating system，OS)上，如果仍基于传统的语义分析的方式对搜索结果进行排序，则很可能因应用或服务的数量太多，导致用户无法及时准确地查找到想要的应用或服务，影响用户的使用体验。为此，本申请实施例提供一种信息排序方法及电子设备，该方法可以实现对设备自身和设备所连接的其它设备的搜索结果中的应用和/或服务进行准确排序，可有效提升信息搜索效率，从而方便用户及时准确地查找到想要的应用或服务。
本申请实施例提供的信息排序方法可以应用于电子设备中。在一些实施例中，电子设备可以是包含诸如个人数字助理和/或音乐播放器等功能的便携式终端，诸如手机、平板电脑、具备无线通讯功能的可穿戴设备(如智能手表)、车载设备等。便携式终端的示例性实施例包括但不限于搭载
Figure PCTCN2021134377-appb-000008
或者其它操作系 统的便携式终端。上述便携式终端也可以是诸如具有触敏表面(例如触控面板)的膝上型计算机(Laptop)等。还应当理解的是，在其他一些实施例中，上述终端也可以是具有触敏表面(例如触控面板)的台式计算机。
图1示出了电子设备100的结构示意图。
电子设备100可包括处理器110、外部存储器接口120、内部存储器121、通用串行总线(universal serial bus，USB)接口130、充电管理模块140、电源管理模块141，电池142、天线1、天线2、移动通信模块150、无线通信模块160、音频模块170、扬声器170A、受话器170B、麦克风170C、耳机接口170D、传感器模块180、按键190、马达191、指示器192、摄像头193、显示屏194、以及用户标识模块(subscriber identification module，SIM)卡接口195等。其中传感器模块180可以包括压力传感器180A、陀螺仪传感器180B、气压传感器180C、磁传感器180D、加速度传感器180E、距离传感器180F、接近光传感器180G、指纹传感器180H、温度传感器180J、触摸传感器180K、环境光传感器180L、骨传导传感器180M等。
可以理解的是，本申请实施例示意的结构并不构成对电子设备100的具体限定。在本申请另一些实施例中，电子设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。
处理器110可以包括一个或多个处理单元，例如：处理器110可以包括应用处理器(application processor，AP)、调制解调处理器、图形处理器(graphics processing unit，GPU)、图像信号处理器(image signal processor，ISP)、控制器、视频编解码器、数字信号处理器(digital signal processor，DSP)、基带处理器、和/或神经网络处理器(neural-network processing unit，NPU)等。其中，不同的处理单元可以是独立的器件，也可以集成在一个或多个处理器中。
电子设备100通过GPU，显示屏194，以及应用处理器等实现显示功能。GPU为图像处理的微处理器，连接显示屏194和应用处理器。GPU用于执行数学和几何计算，用于图形渲染。处理器110可包括一个或多个GPU，其执行程序指令以生成或改变显示信息。
电子设备100可以通过ISP、摄像头193、视频编解码器、GPU、显示屏194以及应用处理器等实现拍摄功能。
SIM卡接口195用于连接SIM卡。SIM卡可以通过插入SIM卡接口195，或从SIM卡接口195拔出，实现和电子设备100的接触和分离。电子设备100可以支持1个或N个SIM卡接口，N为大于1的正整数。SIM卡接口195可以支持Nano SIM卡、Micro SIM卡、SIM卡等。同一个SIM卡接口195可以同时插入多张卡。所述多张卡的类型可以相同，也可以不同。SIM卡接口195也可以兼容不同类型的SIM卡。SIM卡接口195也可以兼容外部存储卡。电子设备100通过SIM卡和网络交互，实现通话以及数据通信等功能。在一些实施例中，电子设备100采用eSIM，即：嵌入式SIM卡。
电子设备100的无线通信功能可以通过天线1、天线2、移动通信模块150、无线通信模块160、调制解调处理器以及基带处理器等实现。天线1和天线2用于发射和接收电磁波信号。电子设备100中的每个天线可用于覆盖单个或多个通信频带。不同的天线还可以复用，以提高天线的利用率。例如：可以将天线1复用为无线局域网的分集天线。在另外一些实施例中，天线可以和调谐开关结合使用。
移动通信模块150可以提供应用在电子设备100上的包括2G/3G/4G/5G等无线通信的解决方案。移动通信模块150可以包括至少一个滤波器、开关、功率放大器、低噪声放大器(low noise amplifier，LNA)等。移动通信模块150可以由天线1接收电磁波，并对接收的电磁波进行滤波，放大等处理，传送至调制解调处理器进行解调。移动通信模块150还可以对经调制解调处理器调制后的信号放大，经天线1转为电磁波辐射出去。在一些实施例中，移动通信模块150的至少部分功能模块可以被设置于处理器110中。在一些实施例中，移动通信模块150的至少部分功能模块可以与处理器110的至少部分模块被设置在同一个器件中。
无线通信模块160可以提供应用在电子设备100上的包括无线局域网(wireless local area networks，WLAN)(如无线保真(wireless fidelity，Wi-Fi)网络)、蓝牙(bluetooth，BT)、全球导航卫星系统(global navigation satellite system，GNSS)、调频(frequency modulation，FM)、近距离无线通信技术(near field communication，NFC)、红外线(infrared radiation，IR)技术等无线通信的解决方案。无线通信模块160可以是集成至少一个通信处理模块的一个或多个器件。无线通信模块160经由天线2接收电磁波，将电磁波信号调频以及滤波处理，将处理后的信号发送到处理器110。无线通信模块160还可以从处理器110接收待发送的信号，对其进行调频，放大，经天线2转为电磁波辐射出去。
在一些实施例中，电子设备100的天线1和移动通信模块150耦合，天线2和无线通信模块160耦合，使得电子设备100可以通过无线通信技术与网络以及其他设备通信。所述无线通信技术可以包括全球移动通讯系统(global system for mobile communications，GSM)、通用分组无线服务(general packet radio service，GPRS)、码分多址接入(code division multiple access，CDMA)、宽带码分多址(wideband code division multiple access，WCDMA)、时分码分多址(time-division code division multiple access，TD-SCDMA)、长期演进(long term evolution，LTE)、BT、GNSS、WLAN、NFC、FM、和/或IR技术等。
可以理解的是，图1所示的部件并不构成对电子设备100的具体限定，电子设备100还可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。此外，图1中的部件之间的组合/连接关系也是可以调整修改的。
电子设备的软件系统可以采用分层架构，事件驱动架构，微核架构，微服务架构，或云架构。本申请实施例以分层架构的Harmony OS为例，示例性说明电子设备的软件结构。图2是本申请实施例的电子设备的软件结构框图。
分层架构将软件分成若干个层，每一层都有清晰的角色和分工。层与层之间通过软件接口通信。在一些实施例中，将Android系统分为四层，从上至下分别为应用层，应用框架层，系统服务层，以及内核层。
应用层包括应用和服务，其中应用包括系统应用和第三方应用，服务包括FA服务和PA服务，例如系统应用中包括应用、FA服务和PA服务，示例性地，应用如桌面、控制栏、电话、设置等，FA服务如豆浆机服务，PA服务如视频会议服务，第三方应用如抖音
Figure PCTCN2021134377-appb-000009
应用。Harmony OS的应用是由一个或多个特性能力(feature ability，FA)服务和/或基本能力(particle ability，PA)服务组成。换句话说，当应用由一个FA服务组成，该应用相当于是FA服务，当应用由一个PA服务组成，该应用相当于PA服务。
其中，FA服务有UI界面，提供与用户交互的能力；而PA服务无UI界面，提供 后台运行任务的能力以及统一的数据访问抽象。基于FA/PA开发的应用，能够实现特定的业务功能，支持跨设备调度与分发，为用户提供一致、高效的应用体验。
应用框架层为Harmony OS的应用程序提供了Java/C/C++/JS等多语言的用户程序框架和Ability(能力)框架，以及各种软硬件服务对外开放的多语言框架应用程序接口(application programming interface，API)；同时为采用Harmony OS的设备提供了C/C++/JS等多语言的框架API，不同设备支持的API与系统的组件化裁剪程度相关。
系统服务层是Harmony OS的核心能力集合，通过框架层对应用程序提供服务。如图2所示，系统服务层可以包括系统基本能力子系统集、基础软件服务子系统集、增强软件服务子系统集、硬件服务子系统集等。
系统基本能力子系统集：为分布式应用在Harmony OS多设备上的运行、调度、迁移等操作提供了基础能力，由分布式软总线、分布式数据管理、分布式任务调度、方舟多语言运行时、公共基础库、多模输入、图形、安全、AI等子系统组成。其中，方舟运行时提供了C/C++/JS多语言运行时和基础的系统类库，也为使用方舟编译器静态化的Java程序(即应用程序或框架层中使用Java语言开发的部分)提供运行时。
基础软件服务子系统集：为Harmony OS提供公共的、通用的软件服务，由事件通知、电话、多媒体、面向产品生命周期各环节的设计(design for X，DFX)等子系统组成。
增强软件服务子系统集：为Harmony OS提供针对不同设备的、差异化的能力增强型软件服务，由智慧屏专有业务、穿戴专有业务、物联网(internet of things，IoT)专有业务等子系统组成。
硬件服务子系统集：为Harmony OS提供硬件服务，由位置服务、生物特征识别、穿戴专有硬件服务、IoT专有硬件服务等子系统组成。
根据不同设备形态的部署环境，基础软件服务子系统集、增强软件服务子系统集、硬件服务子系统集内部可以按子系统粒度裁剪，每个子系统内部又可以按功能粒度裁剪。
核心库包含两部分：一部分是内核子系统、Linux kernel(开源电脑操作系统内核)和Lite OS(轻量级操作系统)等；另一部分是驱动子系统。
内核子系统：Harmony OS采用多内核设计，支持针对不同资源受限设备选用适合的OS内核。内核抽象层(kernel abstract layer，KAL)通过屏蔽多内核差异，对上层提供基础的内核能力，包括进程/线程管理、内存管理、文件系统、网络管理和外设管理等。
驱动子系统：Harmony OS驱动框架(Harmony OS driver foundation，HDF)是Harmony OS硬件生态开放的基础，提供统一外设访问能力和驱动开发、管理框架。
内核层是硬件和软件之间的层。内核层至少包含显示驱动，摄像头驱动，音频驱动，传感器驱动。其中，硬件可以指的是各类传感器，例如本申请实施例中涉及的加速度传感器、陀螺仪传感器、触摸传感器、压力传感器等。
以上图1和图2分别为本申请实施例适用的电子设备的硬件结构和软件结构，为解决背景技术中提出的问题，本申请实施例提供一种信息排序方法，该方法可以实现对设备自身和该设备所连接的其它设备上的应用或FA服务进行搜索和排序，从而方便用户及时准确地查找到想要的应用或服务。
下面分场景示例性地介绍本申请实施例所提供的方法，各场景是以图3所示的智能家居为例展开说明的，图3所述智能家居设备包括：智能音箱、手机、平板、客厅的智慧屏 等。智慧屏是家庭终端中的大屏产品，相对于传统的电视，智慧屏除了可以观看电视节目，还可以联网观看网络视频，甚至有些支持语音控制，控制家里的智能家电等。
场景一
手机的界面显示如图4A中的(a)所示的负一屏界面400，手机的负一屏的搜索框401可以接收用户输入的关键词。因用户可能同时拥有多个设备，例如用户同时拥有手机、智慧屏和平板等，多个设备上可以分别安装有应用和服务。所以，当用户在手机负一屏的搜索框输入关键词，可以从用户的手机和与用户的手机连接的其它设备上搜索到与关键词相关的应用和FA服务信息。
假设用户的智慧屏安装有Welink应用，该Welink应用由一个或多个FA服务和PA服务组成，例如FA服务可以包括Welink-视频FA服务和/或Welink-聊天FA服务组成，PA服务可以包括Welink-视频PA服务和/或Welink-聊天PA服务。Welink-视频FA服务和Welink-视频PA服务可以独立于Welink应用单独运行，同样地，Welink-聊天FA服务和Welink-聊天PA服务也可以独立于Welink应用单独运行。一种可能的情况下，示例性的，当用户触控搜索框(即触控焦点落入搜索框)，在搜索框输入关键词“Welink”时，手机显示如图4A中的(b)所示的界面410。当用户完成关键词的输入操作之后，手机接收到用户作用于搜索控件411的操作，响应于这一操作，手机执行查询操作。具体地，手机先通过互联互通协议从近场查询是否存在与手机处于连接状态的其它设备，若存在，则再根据搜索关键词，从手机和其它设备上查找与关键词相关的应用和服务信息，在界面410上显示相关的搜索结果。
示例性地，如图4A中的(b)所示，该界面410中除了包括手机上的与“Welink”相关的“Welink”应用，还显示有客厅的智慧屏上的与“Welink”相关的“Welink-视频FA”服务和智慧屏上的“Welink-聊天FA”服务，以及手机上的与“Welink”相关的“趣驾Welink-Jetta”应用等等。需要说明的是，界面410中还可以包括其它与“Welink”相关的应用或服务，图中不再一一示出。因智慧屏属于插电设备且屏幕较大，因此智慧屏上的与“视频通话”相关的“Welink-视频 FA”服务的优先级最高，所以排序最靠前。
另外，需要说明的是，若手机通过互联互通协议从近场查询不存在与手机处于连接状态的其它设备，则手机也可以在界面410上只显示手机上与关键词相关的FA服务信息，例如，只显示手机上与“Welink”相关的“趣驾Welink-Jetta”应用。另一种可能的情况下，若手机通过互联互通协议从近场查询不存在与手机处于连接状态的其它设备，但手机确定存在可连接的其它设备时，手机也可以主动与其它设备建立连接，然后从手机和连接的其它设备中查找与关键词相关的FA服务信息。
在一种可能的情况下，假设用户选择触控“Welink-视频 FA”服务对应的打开控件412时，即目标对象为客厅的智慧屏上的“Welink-视频 FA”服务，手机在手机本地运行该程序，达到控制客厅智慧屏上“Welink-视频 FA”服务的目的。也就是说，用户可以在手机上拉起此“Welink-视频 FA”服务的控制界面，用户通过操作手机上的控制界面，达到远程操作客厅智慧屏上的“Welink-视频 FA”服务的效果，使得客厅智慧屏作出对应的响应。示例性地，如图4B中的(a)所示，假设用户作用于界面420中的视频控件421，响应于这一操作，手机显示如图4B中的(b)所示的界面430，即用户可以在手机上拉起此“Welink-视频 FA”服务的控制界面，进行视频会议的拨打，当视频会话接通，手机显示如图4B中的(c)所示的界面440。另外，响应于作用于界面420中的视频控件421这一操作，客厅的智慧屏上也 调用相关硬件(如摄像头、麦克风等)拉起智慧屏上的“Welink-视频 PA”服务，以建立视频会话连接，最终显示如图4C所示的界面。这样，用户就可以在手机上操作客厅智慧屏上的“Welink-视频 FA”服务，达到使用客厅智慧屏发起视频会话的目的。
在另一种可能的情况下，假设用户选择触控“Welink-聊天 FA”服务对应的打开控件413时，即目标对象为客厅的智慧屏上的“Welink-聊天 FA”服务，手机在手机本地运行该程序，达到控制客厅智慧屏上“Welink-聊天 FA”服务的目的。也就是说，用户可以在手机上拉起此“Welink-聊天 FA”服务的控制界面，用户通过操作手机上的控制界面，达到远程操作客厅智慧屏上的“Welink-聊天 FA”服务的效果，使得客厅智慧屏作出对应的响应。示例性地，如图4D中的(a)所示，假设用户作用于界面450中的联系人控件451，响应于这一操作，手机显示如图4D中的(b)所示的界面460，即用户可以在手机上拉起此“Welink-聊天 FA”服务的控制界面，另外，响应于作用于界面450中的联系人控件451这一操作，客厅的智慧屏上也调用相关硬件(如摄像头、麦克风等)拉起智慧屏上的“Welink-聊天 PA”服务，以建立短消息会话连接，并显示如图4E所示的界面。这样，用户就可以在手机上操作客厅智慧屏上的“Welink-聊天 FA”服务，达到使用客厅智慧屏发起短消息会话的目的。
假设用户的智慧屏安装有Welink应用，以及该Welink应用包括Welink-视频FA服务和Welink-聊天FA服务。另外，智慧屏上还安装有微信应用，以及该微信包括微信-视频FA服务和微信-聊天FA服务。另一种可能的情况下，示例性的，当用户触控搜索框(即触控焦点落入搜索框)，在搜索框输入关键词“视频通话”时，手机显示如图4A中的(c)所示的界面410。当用户完成关键词的输入操作之后，手机接收到用户作用于搜索控件411的操作，响应于这一操作，手机执行查询操作。具体地，手机先通过互联互通协议从近场查询是否存在与手机处于连接状态的其它设备，若存在，则再根据搜索关键词，从手机和其它设备上查找与关键词相关的应用和FA服务信息，在界面410上显示比较相关的搜索结果。示例性地，如图4A中的(c)所示，该界面410中除了包括智慧屏上的与“视频通话”相关的“Welink-视频 FA”服务，还显示有客厅的智慧屏上的“微信
Figure PCTCN2021134377-appb-000010
-FA”服务，以及手机上的“Welink”应用和手机上的“微信”应用。需要说明的是，界面410中还可以包括其它与“视频通话”相关的应用或服务，图中不再一一示出。因智慧屏属于插电设备且屏幕较大，因此智慧屏上的与“视频通话”相关的“Welink-视频 FA”服务的优先级最高，所以排序最靠前。
需要说明的是，如上文所述，Welink应用为一款会议类应用程序，Welink应用可以由一个或多个FA服务和PA服务组成，例如FA服务可以包括Welink-视频FA服务和/或Welink-聊天FA服务组成。同样地，微信
Figure PCTCN2021134377-appb-000011
应用为一款社交类应用程序，微信
Figure PCTCN2021134377-appb-000012
应用可以由一个或多个FA服务和PA服务组成，例如FA服务可以包括微信
Figure PCTCN2021134377-appb-000013
-视频FA服务和/或微信
Figure PCTCN2021134377-appb-000014
-聊天FA服务组成，PA服务可以包括微信
Figure PCTCN2021134377-appb-000015
-视频PA服务和/或微信
Figure PCTCN2021134377-appb-000016
-聊天PA服务。微信
Figure PCTCN2021134377-appb-000017
视频FA服务和微信
Figure PCTCN2021134377-appb-000018
视频PA服务可以独立于微信
Figure PCTCN2021134377-appb-000019
应用单独运行，同样地，微信
Figure PCTCN2021134377-appb-000020
聊天FA服务和微信
Figure PCTCN2021134377-appb-000021
聊天PA服务也可以独立于微信
Figure PCTCN2021134377-appb-000022
应用单独运行。因用户可能同时拥有多个设备，例如用户同时拥有手机、智慧屏和平板等，多个设备上可以分别安装有应用和服务。所以，当用户在手机负一屏的搜索框输入关键词，可以从用户的手机和与用户的手机连接的其它设备上搜索到与关键词相关的应用和FA服务信息。
在一种可能的情况下，假设用户选择触控“Welink-视频FA”控件对应的打开控件414时，即目标对象为客厅的智慧屏上的“Welink-视频FA”服务，手机在手机本地运行该程序， 达到控制客厅智慧屏上“Welink-视频FA”服务的目的。也就是说，用户可以在手机上拉起此“WelinkFA-视频FA”服务的控制界面，用户通过操作手机上的控制界面，达到远程操作客厅智慧屏上的“WelinkFA-视频FA”服务的效果，使得客厅智慧屏作出对应的响应。具体示例可以参见上文关于图4B至图4D所示的示例，在此不再重复赘述。
本实施例中，考虑到FA服务的标签除了包括FA服务的名称，还包括设备属性、设备类型、功能描述、FA服务包名等，如设备属性可以是大屏设备或小屏设备，设备类型可以是智慧屏类型或智慧屏设备的编号，FA服务的功能描述可以是视频类服务还是音乐类服务等。通常，在应用市场上架该FA服务时，FA服务会被人为地标注与设备属性、设备类型、功能描述、FA服务包名相关的标签。基于此，用户除了可以通过在搜索框输入FA服务的名称进行搜索之外，还可以在搜索框中输入FA服务的属性，比如说，FA服务的属性可以是FA服务的功能特性，假设说在搜索框中输入“视频通话”，可以搜索到与“视频通话”相关的“Welink视频 FA”、“微信-视频 FA”等；或者，FA服务的属性可以是FA服务的服务类型，假设说在搜索框中输入“音乐”，可以搜索到与“音乐”相关的“音乐 FA”、“喜雅拉雅
Figure PCTCN2021134377-appb-000023
FA”等；再或者，FA服务的属性可以是与FA服务强相关的设备名称，假设说在搜索框中输入“智慧屏”，可以搜索到与“智慧屏”相关的“Welink-视频FA”、“微信-视频 FA”等。当用户在手机的搜索结果中选择打开其它设备上的FA服务时，手机运行FA服务的过程，显示控制界面，以及如何拉起其它设备对应的PA服务的过程与上述图4B至图4E所描述的过程类似，在此不再一一举例示出。
本实施例中，手机对搜索结果的排序方法具体可以是如下方式中的任意一种或者多种的组合。
方式一，手机可以根据关键词，获取与关键词相关的N个候选FA服务的标签，然后计算关键词与N个候选FA服务的标签之间的语义相似度；根据语义相似度的大小，确定大于设定阈值的语义相似度所对应的FA服务，其中语义相似度越大的FA服务，排序越靠前。例如，界面410中所显示的是筛选出的语义相似度大于设定阈值的4个FA服务。
方式二，手机可以根据关键词，获取与关键词相关的N个候选FA服务的标签，然后计算关键词在N个候选FA服务的标签中的词频分布，一方面，若手机中与该关键词相关的FA服务较多，则在界面410中所有设备下面的搜索结果中，手机的搜索结果相比其它设备的搜索结果更靠前。也就是说，与关键词相关的FA服务越多的设备的排序越靠前。另一方面，若与关键词相关的FA服务在手机和其它设备中均匀分布，则该FA服务的排序相对靠后，反之，若与关键词相关的FA服务只在部分设备中高频分布(如客厅的智慧屏上)，则该设备的FA服务的排序更靠前。
方式三，手机可以获取手机和其它设备的设备状态，如设备的供电类型、设备的屏幕大小、设备的可用计算资源、设备性能与所述目标FA服务的相关性，以及获取FA服务相关的先验知识约束条件，然后根据设备状态和FA服务相关的先验知识约束条件，对搜索结果中的FA服务进行排序。其中，FA服务相关的先验知识约束条件可以包括FA服务优先在大屏设备上运行、FA服务优先在插电类型的设备上运行、FA服务优先在计算能力强的设备上运行或FA服务优先在音频播放性能佳的设备上运行。示例性地，“Welink-视频FA”服务的先验知识约束条件为优先在大屏设备上运行且优先在插电设备上运行，因客厅的智慧屏的设备状态为大屏设备且供电类型为插电类型，因此客厅的智慧屏与“Welink-视 频FA”服务的匹配度较高，故客厅的智慧屏上的“Welink-视频FA”服务最靠前。
场景二
该场景是以图5A所示的驾驶场景为例展开说明的，图5A所述设备包括：车载终端、手机、智能手表等。假设，车内后排乘坐的家庭成员A需要进行导航，那么家庭成员A可以操作自己的手机，控制车载终端进行地图导航。
示例性地，如图5B所示，手机的界面显示如图5B中的(a)所示的负一屏界面500，当用户触控搜索框(即触控焦点落入搜索框)，准备输入关键词时，手机显示如图5B中的(b)所示的界面510，假设用户在界面510中输入了“导航”，当用户完成关键词的输入操作之后，手机接收到用户作用于搜索控件511的操作，响应于这一操作，从手机和其它设备上(如车内的智能手表和车载终端上)查找与关键词“导航”相关的应用信息，然后根据查询结果，在界面510上显示与搜索关键词“导航”相关的搜索结果。示例性地，如图5B中的(b)所示，该界面510中除了包括手机上的与“导航”相关的“腾讯地图
Figure PCTCN2021134377-appb-000024
”应用，还显示有智能手表上的与“导航”相关的“谷歌地图
Figure PCTCN2021134377-appb-000025
”应用，以及车载终端上的与“导航”相关的“百度地图
Figure PCTCN2021134377-appb-000026
”应用。
假设说，用户确定选择触控手机上的“百度地图
Figure PCTCN2021134377-appb-000027
”应用，手机接收到用户作用于“百度地图
Figure PCTCN2021134377-appb-000028
”应用控件512的操作，手机在本地运行该程序，达到控制车载终端上“百度地图
Figure PCTCN2021134377-appb-000029
”应用的目的。这样，用户就可以通过在手机上操作，拉起车载终端上的“百度地图
Figure PCTCN2021134377-appb-000030
”的导航服务。
本实施例中，手机对搜索结果的排序方法具体可以是：手机在与车载终端、智能手表建立连接后，除了获取设备自身状态之外，还可以获取车载终端的设备状态、智能手表的设备状态，例如车载终端是设备状态为处于开机运行状态、插电类型设备、计算资源充足；智能手表的设备状态包括电池供电设备、计算资源不足。除此之外，手机还获取“百度地图
Figure PCTCN2021134377-appb-000031
”应用相关的先验知识约束条件，例如，手机从云服务器获取“百度地图
Figure PCTCN2021134377-appb-000032
”应用相关的先验知识约束条件为优先插电类型的设备，且优先运行在计算能力强的设备。基于“百度地图
Figure PCTCN2021134377-appb-000033
”应用相关的先验知识约束条件，以及各个设备的设备状态，手机对搜索结果中的“百度地图
Figure PCTCN2021134377-appb-000034
”应用进行排序。因车载终端的设备状态为计算资源充足且供电类型为插电类型，因此车载终端与“百度地图
Figure PCTCN2021134377-appb-000035
”应用的匹配度较高，故车载终端上的“百度地图
Figure PCTCN2021134377-appb-000036
”应用最靠前，其次是手机上的“腾讯地图
Figure PCTCN2021134377-appb-000037
”应用，再其次是智能手表上的“谷歌地图
Figure PCTCN2021134377-appb-000038
”应用。
需要说明的是，上述场景二所示的示例同样适用于导航类FA服务的搜索和排序，也就是说，若用户在搜索框输入“导航”，搜索结果中也可以包括智能手表上的与“导航”相关的FA服务，以及车载终端上的与“导航”相关的FA服务，用户同样可以在手机上操作该车载终端的FA服务，拉起车载终端上与导航相关的PA服务。具体可以参照上述场景一所示的示例，在此不再一一用图例示出。
场景三
该场景仍是以图3所示的智能家居为例展开说明的。
示例性地，手机的界面显示如图6A中的(a)所示的负一屏界面600，手机的负一屏的搜索框601可以接收用户输入的关键词。当用户触控搜索框(即触控焦点落入搜索框)，准备输入关键词时，手机显示如图6A中的(b)所示的界面610，假设用户在界面610中 输入了“音乐”，当用户完成关键词的输入操作之后，手机接收到用户作用于搜索控件611的操作，响应于这一操作，手机执行查询操作。具体地，手机先通过互联互通协议从近场查询是否存在与手机处于连接状态的其它设备，若存在，则再根据搜索关键词，从手机和其它设备上查找与关键词“音乐”相关的应用信息，在界面610上显示比较相关的搜索结果。示例性地，如图6A中的(b)所示，该界面610中除了包括手机上的“音乐”应用的控件，还显示有平板上的“音乐”应用的控件，以及智能音箱上的“音乐”应用的控件。
本实施例中，手机对界面610中搜索结果的排序方法具体可以是：手机在与智能音箱、和平板建立连接后，除了获取设备自身状态之外，还可以获取平板的设备状态和智能音箱的设备状态，例如智能音箱的设备状态为插电类型设备、音频播放性能佳；平板的设备状态包括电池供电设备、视频播放性能佳。除此之外，手机还获取“音乐”应用相关的先验知识约束条件，例如，手机从云服务器获取“音乐”应用相关的先验知识约束条件为优先插电类型的设备，且优先运行在音频播放性能佳的设备。基于“音乐”应用相关的先验知识约束条件，以及各个设备的设备状态，手机对搜索结果中的“音乐”应用进行排序。因智能音箱的设备状态为音频播放性能佳且供电类型为插电类型，因此智能音箱与“音乐”应用的匹配度较高，故智能音箱上的“音乐”应用最靠前，其次是手机上的“音乐”应用，再其次是平板上的“音乐”应用。
进一步地，假设用户选择触控“音乐”应用的对应的打开控件612时，即目标对象为智能音箱上的“音乐”应用，手机在手机本地运行该程序，达到控制智能音箱上“音乐”应用的目的。也就是说，用户可以在手机上拉起此“音乐”应用的控制界面，用户通过操作手机上的控制界面，达到远程操作智能音箱上的“音乐”应用的效果，使得智能音箱作出对应的响应。
示例性地，如图6B中的(a)所示，假设用户作用于界面620中的播放控件621，响应于这一操作，手机显示如图6B中的(b)所示的界面630，即用户可以在手机上拉起此“音乐”应用的控制界面，控制智能音箱开始播放音乐。另外，响应于作用于界面620中的播放控件621这一操作，智能音箱上也调用相关硬件(如扬声器等)拉起此“音乐”应用，以播放音乐。这样，用户就可以在手机上操作智能音箱上的“音乐”应用，达到控制智能音箱播放音乐的目的。
需要说明的是，上述场景三所示的示例同样适用于音乐类FA服务的搜索和排序，也就是说，若用户在搜索框输入的是“音乐”，搜索结果中也可以包括音箱上的与“音乐”相关的FA服务，以及平板上的与“音乐”相关的FA服务，用户同样可以在手机上操作该音箱上的FA服务，拉起音箱上与音乐相关的PA服务。具体可以参照上述场景一所示的示例，在此不再一一用图例示出。
结合上述场景一至场景三，具体来说，手机根据搜索关键词，从手机和其它设备上查找与关键词相关的应用信息或服务信息的具体方法可以是如下方式中的任意一种或者多种的组合。
方式一，手机可以根据关键词，获取N个候选对象的标签，然后计算关键词与N个候选对象的标签之间的语义相似度；根据语义相似度的大小，确定大于设定阈值的语义相似度所对应的应用或服务，其中语义相似度越大的应用或服务，排序越靠前。
方式二，手机可以根据关键词，获取N个候选对象的标签，然后计算关键词在N个候 选对象的标签中的词频分布，一方面，若手机中与该关键词相关的应用或服务较多，则在界面中所有设备下面的搜索结果中，手机相比其它设备的搜索结果更靠前。也就是说，与关键词相关的应用或服务越多的设备的排序越靠前。另一方面，若与关键词相关的应用或服务在手机和其它设备中均出现，则该应用或服务的排序相对靠后，反之，若与关键词相关的应用或服务只在部分设备中出现(如客厅的智慧屏上)，则该应用或服务的排序更靠前。
方式三，手机可以获取手机和其它设备的设备状态，如设备的供电类型、设备的屏幕大小、设备的可用计算资源、设备性能与所述目标对象的相关性，以及获取应用或服务相关的先验知识约束条件，然后根据设备状态和应用或服务相关的先验知识约束条件，对搜索结果中的应用或服务进行排序。其中，应用或服务相关的先验知识约束条件可以包括应用或服务优先在大屏设备上运行、应用或服务优先在插电类型的设备上运行、应用或服务优先在计算能力强的设备上运行或应用或服务优先在音频播放性能佳的设备上运行。
这样，按照上述方式三排序得到的搜索结果可以具有如下特点：
特点一，若某一设备正处于被用户使用的状态，则该设备上与关键词相关的应用或服务的排序更靠前。例如，用户正在浏览客厅的智慧屏上的视频信息，则此时若用户通过手机搜索一些视频资讯相关的应用或服务，搜索结果中大屏相关的应用或服务的排序更靠前。这样，有助于节省应用或服务在设备上的启动时长，而且大屏更便于用户查看信息。
特点二，若某一应用或服务在设备A中使用体验更佳，则设备A的搜索信息排序更靠前。以音乐播放的应用为例，在搜索结果中存在音箱、大屏、手机、平板的应用的情况下，音箱上的应用的排序更靠前。
特点三，若某一类应用或服务使用时功耗较大，则能够支持高功耗的插电设备上的相关应用或服务排序更靠前。以游戏为例，手机、平板、大屏同时支持的情况下，大屏上的游戏应用的排序更靠前，这是因为大屏通常是插电设备，无需考虑功耗问题。
特点四，某一类应用或服务使用时需要占用较高的计算资源，则计算资源相对充足的设备上相关应用或服务的排序更靠前。
方式四，手机可以获取手机和其它设备的设备状态，以及获取应用或服务相关的先验知识约束条件，然后根据设备状态和应用或服务相关的先验知识约束条件，一方面，根据关键词与应用或服务的标签之间的语义相似度或词频分布情况，确定应用或服务分别对应的第一权重。另一方面，根据应用或服务相关的先验知识的约束条件，与设备状态之间的匹配度，确定应用或服务分别对应的第二权重；然后根据第一权重和第二权重，对搜索到的应用或服务进行排序。具体来说，如果搜索结果中包括对应同一个应用或服务的多个设备的应用标签和/或服务标签，则需要按照应用或服务相关的先验知识的约束条件，与设备状态之间的匹配度，对多个设备的应用标签和/或服务标签进行排序。例如，手机、平板和智慧屏上均搜索到“Welink-视频 FA”服务，因“Welink-视频 FA”应用或服务相关的先验知识的约束条件是大屏优先、插电设备优先，所以智慧屏上的“Welink-视频 FA”应用或服务标签在搜索结果中更靠前。
结合上述场景一的示例，归纳来说，本申请实施例提供一种信息排序方法，该方法可以应用于分布式系统中的设备。具体来说，如图7所示，该方法包括如下步骤。
步骤701，电子设备接收用户的搜索请求，该搜索请求包括用户输入的关键词。
示例性地，该搜索请求可以是用户通过触控输入的内容，或者通过语音指令输入的内容。其中，在用户输入内容的过程中，电子设备就可以利用用户已输入的信息进行关键词的广泛匹配，当用户完成了关键词的输入之后，电子设备可以基于用户输入的关键词进行关键词精确匹配。
步骤702，电子设备根据关键词，获取N个候选对象的标签，以及计算关键词与N个候选对象的标签之间的语义相似度。
具体来说，一种可能的实施例中，电子设备可以依据深度神经网络模型分别计算搜索词与多个候选对象程序之间的语义相似度。其中，深度神经网络模型可以是预先根据对从候选对象获得的训练语料进行训练所生成的机器模型。
在一种可能的实施例中，在执行步骤702之前，电子设备从数据库获取L个候选对象的详情信息，然后从L个候选对象的详情信息中提取原始关键词，对原始关键词进行语义解析，从解析结果中获取L个候选对象的标签。示例性地，应用的详情信息包括但不限于：应用的标题、应用的描述文本、应用的评论信息、应用的推荐语、应用的最近更新特性等信息。应用的标签包括但不限于：应用的名称、应用所属类别、应用的特性等信息。服务的详情信息包括但不限于：服务的标题、服务的描述文本、服务的评论信息、服务的推荐语、服务的最近更新特性等信息。服务的标签包括但不限于：服务的名称、服务用所属类别、服务用的特性等信息。
具体地，第一步，从数据库获取L个候选对象的详情信息之后，可以先对候选对象的详情信息进行分词。例如：可以构建自定义词典，按照预设策略将待分析汉字串与自定义词典中的词条进行匹配，若在自定义词典中能够找到某个字符串，则匹配成功(即识别出一个词)。按照扫描方向的不同，串匹配分词方法可以分为正向匹配和逆向匹配，按照不同长度优先匹配的情况，串匹配分词方法可以分为最大(最长)匹配和最小(最短)匹配，实际应用中，可视需求选取具体的分词方法。第二步，在完成分词之后，可以过滤掉停用词、无效词等。例如：可以过滤掉对象描述文本中描述的与对象无关的信息，比如开发者的自我介绍、开发者留下的联系方式；过滤掉广告或者促销信息，比如购物应用中的促销广告、游戏应用中的游戏币营销信息；另外还可以过滤掉数字、拼音等。具体的过滤方法，例如：可以构建正则过滤规则，过滤掉与该正则过滤规则匹配的词。比如，构建正则过滤规则：“联系方式”、“邮件”、“电话”等，则可以将对象的详情信息中的联系方式、邮件、电话等信息过滤掉。第三步，过滤掉停用词、无效词之后，可以对得到的词进行筛选处理，例如进行词性筛选，选取动词、名词等，得到至少一个关键词。
在另一种可能的实施例中，如果筛选得到的原始关键词比较多，则可以计算每个原始关键词的词频(term frequency，TF)，词频表示文档中某个词出现的频率，并计算每个关键词的逆向文档频率(inverse document frequency，IDF)，逆向文档频率由数据库中的文档总数除以包含该词语之文档的数目，再将得到的商取对数得到，将每个关键词的词频与逆向文档频率的乘积作为对应关键词的TF-IDF值，选取TF-IDF值大于预设阈值的关键词作为原始关键词，预设阈值可视实际需求自定义取值。另外，如果筛选得到的关键词不多，则可以只进行相似度的匹配。然后电子设备利用语义解析模型对原始关键词进行语义解析，生成对象的标签。
步骤703，电子设备从N个候选对象的标签中，确定大于设定阈值的语义相似度所对应的M个候选对象的标签。
其中，M个候选对象的标签中有K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象；M≤N，M、N和K为大于或等于2的正整数。K个设备上的同一属性的目标对象可以为K个设备上的同一名称的目标对象，例如手机和平板上的微信
Figure PCTCN2021134377-appb-000039
应用，或者，K个设备上的同一属性的目标对象可以为K个设备上的同一供应商的目标对象，例如手机的
Figure PCTCN2021134377-appb-000040
应用与平板上抖音
Figure PCTCN2021134377-appb-000041
应用为同一供应商字节跳动
Figure PCTCN2021134377-appb-000042
的应用；或者，K个设备上的同一属性的目标对象可以为K个设备上的同一安装包的目标对象，例如，手机和平板上的微信
Figure PCTCN2021134377-appb-000043
应用的安装包名称相同。或者，K个设备上的同一属性的目标对象可以为K个设备上的同一功能的目标对象，例如，手机的
Figure PCTCN2021134377-appb-000044
应用与平板上抖音
Figure PCTCN2021134377-appb-000045
应用均具有短视频分享功能。
示例性地，M个候选对象的标签中包括手机上“Welink”对象的标签、智慧屏上“Welink”对象的标签，以及平板上“Welink”对象的标签。
步骤704，电子设备根据关键词与K个候选对象的标签之间的语义相似度，以及K个设备的设备状态，对K个候选对象进行排序。
一种可能的实施例中，电子设备可以分别确定K个候选对象分别对应的第一权重和第二权重，根据第一权重和第二权重，对K个候选对象进行排序。
具体来说，一方面，电子设备确定关键词与K个候选对象的标签之间的语义相似度越大，第一权重越大；反之，语义相似度越小，第一权重越小。例如，手机根据关键词与手机上“Welink”服务的标签之间的语义相似度，确定手机上“Welink”服务的第一权重为K1；手机根据关键词与智慧屏上“Welink”服务的标签之间的语义相似度，确定智慧屏上“Welink”服务的第一权重为K2；手机根据关键词与平板上“Welink”服务的标签之间的语义相似度，确定平板上“Welink”服务的第一权重为K3。
另一方面，电子设备根据目标对象相关的先验知识的约束条件，与K个设备的设备状态之间的匹配度，确定K个候选对象分别对应的第二权重。
其中，目标对象相关的先验知识的约束条件包括如下条件中的至少一个：目标对象优先在大屏设备上运行、目标对象优先在插电类型的设备上运行、目标对象优先在计算能力强的设备上运行，目标对象优先在音频播放性能佳的设备上运行。示例性地，假设目标对象为上述场景一中的“Welink-视频 FA”服务，该“Welink-视频 FA”服务为一种办公会议软件，因此，与“Welink-视频 FA”服务相关的先验知识的约束条件包括优先在大屏设备上运行。再比如，假设目标对象为场景三中的“音乐”，因“音乐”是一种音乐类软件，因此，与“音乐”服务相关的先验知识的约束条件包括优先在音频播放性能佳的设备上运行。
需要说明的是，目标对象相关的先验知识的约束条件可以是开发人员预设的条件，电子设备可以从服务器下载应用或服务的同时获取该约束条件，也可以是电子设备周期性地从云服务器获取该约束条件，对此，本申请实施例并不作限定。
再者，设备的状态包括如下状态中的至少一个设备的供电类型、设备的屏幕大小、设备的可用计算资源、设备性能与所述目标对象的相关性。示例性地，手机的供电类型通常为电池，客厅的智慧屏的供电类型为插电类型，音箱的音频播放性能与音乐类应用或服务更相关等。
示例性地，假设Welink-视频 FA”服务的先验知识的约束条件为优先在大屏上运行，优先在插电设备上运行。手机的设备状态为电池供电类型、屏幕尺寸为7英寸；客厅的智慧屏的设备状态为插电供电类型，屏幕尺寸为55英寸；平板的设备状态为电池供电类型、 屏幕尺寸为7.9英寸。这样，手机根据手机的设备状态与Welink-视频 FA”服务的先验知识的约束条件的匹配度，确定手机上“Welink-视频 FA”服务的第二权重为L1；手机根据客厅智慧屏的设备状态与Welink-视频 FA”服务的先验知识的约束条件的匹配度，确定手机上“Welink-视频 FA”服务的第二权重为L2；手机根据平板的设备状态与Welink-视频 FA”服务的先验知识的约束条件的匹配度，确定手机上“Welink-视频 FA”服务的第二权重为L3。
在一种可能的实施例中，电子设备确定K个候选对象分别对应的第二权重的方式可以是如下任意一种方式或多种方式的组合。
方式一，当目标对象相关的先验知识的约束条件为目标对象优先在插电类型的设备上运行时，确定K个候选对象对应的K个设备中支持插电类型的设备的对应的候选对象的第二权重大于不支持插电类型的设备的对应的候选对象的第二权重。示例性地，若上述手机的搜索结果包括客厅的智慧屏的“Welink-视频 FA”服务，则客厅的智慧屏上“Welink-视频 FA”在所有设备这一栏中的排序更靠前，而手机或平板上的“Welink-视频 FA”服务则靠后。因为客厅的智慧屏是能够支持高功耗的插电设备，所以就基本不存在电量不足的问题。
方式二，当目标对象相关的先验知识的约束条件为目标对象优先在大屏设备上运行时，确定K个候选对象对应的K个设备中屏幕越大的设备对应的候选对象的第二权重越大。示例性地，若搜索结果包括客厅的智慧屏的“Welink-视频 FA”服务，则客厅的智慧屏上“Welink-视频 FA”在所有设备这一栏中的排序更靠前，而手机或平板上的“Welink-视频 FA”服务则靠后。这是因为客厅的智慧屏属于大屏设备，更方便多个用户同时查看大屏上的信息。
方式三，当目标对象相关的先验知识的约束条件为目标对象优先在计算能力强的设备上运行时，确定K个候选对象对应的K个设备中计算能力越强的设备对应的候选对象的第二权重越大。示例性地，若搜索结果包括客厅的智慧屏的“AI拍照”服务，则客厅的智慧屏上“AI拍照”在所有设备这一栏中的排序更靠前，而手机或平板上的“AI拍照”服务则靠后。这是因为客厅的智慧屏属于处理能力较强的设备，数据处理效率更高。
方式四，当目标对象相关的先验知识的约束条件为目标对象优先在音频播放性能佳的设备上运行时，确定K个候选对象对应的K个设备中音频播放性能越佳的设备的第二权重越大。示例性地，若搜索结果包括智能音箱的“音乐”服务，则智能音箱上的“音乐”在所述设备这一栏中的排序更靠前，而手机或平板上的“音乐”服务则靠后。这是因为智能音箱的音频播放能力佳，属于与“音乐”服务强相关的设备。
需要说明的，随着应用市场中应用类型的扩展，以及应用市场中服务类型的扩展，未来市场中还可能存在其它类型的应用或服务，或者说，应用或服务相关的先验知识的约束条件也可能会随着应用或服务的更新而发生更新，所以本申请实施例并不限定电子设备确定K个候选对象分别对应的第二权重的方式，未来还可能存在利用其它的先验知识的约束条件来确定第二权重的方式。
一种可能的情况下，电子设备可以计算第一权重和第二权重的乘积，根据乘积的大小，对K个候选对象进行排序，例如，乘积越大，排序越靠前，或者乘积越小，排序越靠前。
在另一种可能的情况下，电子设备还可以结合设备中情景智能的推荐结果，以及用户的使用习惯等信息，调整上述第一权重和第二权重的乘积，利用调整后的第二权重和第一权重的乘积，对K个候选对象进行排序。
可选地，当对K个候选对象进行排序之后，本申请实施例还可以包括步骤705，电子设备将排序后K个候选对象显示到预设的推荐界面中，其中，第一权重和第二权重的乘积 越大的候选对象的排序越靠前。示例性地，如图4A中的(b)所示，在负一屏界面600上所有设备这一栏的推荐结果中显示客厅智慧屏的“Welink-视频 FA”服务和Welink-聊天 FA”服务最靠前，其次是平板的“Welink-视频 FA”服务，最后是手机的“Welink-视频 FA”服务。
在另一种可能的情况下，电子设备还可以从数据库或服务器上获取设备的标签，然后计算关键词与设备的标签之间的相似度，从而根据该相似度大小，确定K个设备对应的K个候选对象的第三权重。进一步地，电子设备可以根据第一权重、第二权重和第三权重，对K个候选对象进行排序。例如，客厅的智慧屏的标签包括视频、会议等，手机的标签包括打电话、上网等，手机可以从云服务器获取上述设备的标签，该标签可以是由开发商预设的内容，也可以是用户主动标记然后上传至云服务器的，对此，本申请并不限定。
具体来说，本申请实施例提供如图8所示的方法流程图，该方法包括如下步骤。
步骤801，电子设备接收用户的搜索请求，该搜索请求包括用户输入的关键词。
具体可以参照上述步骤701。
步骤802，在电子设备接收到输入词的过程中，电子设备可以实时判断用户是否结束输入，若否，则执行步骤803a，否则执行步骤803b。
示例性地，用户在输入“Welink”的过程中，手机在接收到每一个字符的过程中，判断是否会已结束输入。
步骤803a，若否，电子设备可以对已接收到的关键词进行广泛匹配，计算关键词与候选对象的标签之间的相似度。
示例性地，电子设备对已接收到的关键词“We”进行广泛匹配，计算关键词“We”与候选对象的标签之间的相似度。
步骤803b，若是，电子设备可以对接收的关键词进行精确匹配，计算关键词与候选对象的标签之间的相似度，计算候选对象相关的先验知识的约束条件与设备的状态之间的相似度。
步骤804，电子设备确定大于设定阈值的语义相似度所对应的M个候选对象的标签中K个候选对象，该K个候选对象对应同一属性的目标对象。
步骤805，针对K个候选对象中的任意一个候选对象，电子设备根据关键词与该候选对象的标签之间的相似度确定第一权重，电子设备根据该候选对象相关的先验知识的约束条件与设备的状态之间的相似度确定第二权重，以及电子设备根据关键词与设备的标签之间的相似度确定第三权重。
步骤806，电子设备根据第一权重、第二权重和第三权重，对各个候选对象进行排序。
本实施例中，这样排序之后的搜索结果具有如下特点：应用的标签或服务的标签与关键词语义更相近的应用或服务，则该应用或服务的排序更靠前；设备的标签与关键词语义更相近的设备的搜索结果在排序中更靠前；设备的状态与候选对象相关的先验知识的约束条件更匹配，则该设备的搜索结果在排序中更靠前。
结合上述场景二所示的示例，归纳来说，本申请实施例还提供一种信息排序方法，具体来说，如图9所示，该方法包括如下步骤。
步骤901，电子设备接收用户的搜索请求，该搜索请求包括用户输入的关键词。
示例性地，该搜索请求可以是用户通过触控输入的内容，或者通过语音指令输入的内容。其中，在用户输入内容的过程中，电子设备就可以利用用户已输入的信息进行关键词 的广泛匹配，当用户完成了关键词的输入之后，电子设备可以基于用户输入的关键词进行关键词精确匹配。
步骤902，电子设备根据关键词，获取N个候选对象的标签，以及计算关键词与N个候选对象的标签之间的语义相似度。
具体可以参见上述步骤702，在此不再重复赘述。
步骤903，电子设备从N个候选对象的标签中，确定大于设定阈值的语义相似度所对应的M个候选对象的标签。其中，M个候选对象的标签中有K个候选对象的标签对应于安装在K个设备上的不同属性的目标对象；M≤N，M、N和K为大于或等于2的正整数。
具体地，不同属性的目标对象可以为不同名称的目标对象，例如微信
Figure PCTCN2021134377-appb-000046
应用和支付宝
Figure PCTCN2021134377-appb-000047
应用，或者，不同属性的目标对象可以为不同供应商的目标对象，例如
Figure PCTCN2021134377-appb-000048
应用与快手
Figure PCTCN2021134377-appb-000049
应用为不同供应商的应用；或者，不同属性的目标对象可以为不同安装包的目标对象，例如，微信
Figure PCTCN2021134377-appb-000050
应用的安装包名称和支付宝应用的安装包名称不同。或者，不同属性的目标对象可以为不同功能的目标对准，例如，
Figure PCTCN2021134377-appb-000051
应用与微信
Figure PCTCN2021134377-appb-000052
应用的功能不同。
步骤904，电子设备根据关键词与M个候选对象的标签之间的语义相似度，以及M个设备的设备状态，对M个候选对象进行排序。
一种可能的实施例中，电子设备可以分别确定M个候选对象分别对应的第一权重和第二权重，根据第一权重和第二权重，对M个候选对象进行排序。
具体来说，一方面，电子设备确定关键词与M个候选对象的标签之间的语义相似度越大，第一权重越大；反之，语义相似度越小，第一权重越小。
另一方面，电子设备根据M个候选对象相关的先验知识的约束条件，与K个设备的设备状态之间的匹配度，确定M个候选对象分别对应的第二权重。
其中，M个候选对象相关的先验知识的约束条件包括如下条件中的至少一个：候选对象优先在大屏设备上运行、候选对象优先在插电类型的设备上运行、候选对象优先在计算能力强的设备上运行，候选对象优先在音频播放性能佳的设备上运行。示例性地，假设候选对象为上述场景二中的“百度地图”服务，该“百度地图”服务为一种导航软件，因此，与“百度地图”服务相关的先验知识的约束条件包括优先在车载设备上运行，因此该“百度地图”服务与车载设备的设备状态匹配度最高。
在一种可能的实施例中，电子设备确定M个候选对象分别对应的第二权重的方式可以是如下任意一种方式或多种方式的组合。
方式一，针对M个候选对象中的任意一个候选对象，当候选对象相关的先验知识的约束条件为优先在插电类型的设备上运行时，电子设备根据该候选对象所在的设备是否是支持插电类型的设备确定第二权重，其中，候选对象所在的设备是支持插电类型的设备的情况下的第二权重高于候选对象所在的设备是支持电池类型的设备的情况下的第二权重。
示例性地，若上述场景二中手机的搜索结果包括车载终端的“百度地图”服务，则车载终端上“百度地图”在所有设备这一栏中的排序更靠前，而手机上的“百度地图”服务则靠后。因为车载终端是能够支持高功耗的插电设备，所以就基本不存在电量不足的问题。
方式二，针对M个候选对象中的任意一个候选对象，当候选对象相关的先验知识的约束条件为候选对象优先在大屏设备上运行时，电子设备根据该候选对象所在设备中屏幕大小确定第二权重，其中，候选对象所在的设备是大屏设备的情况下的第二权重高于候选对象所在的设备是小屏设备的情况下的第二权重。
方式三，针对M个候选对象中的任意一个候选对象，当候选对象相关的先验知识的约束条件为候选对象优先在计算能力强的设备上运行时，电子设备根据该候选对象所在设备中的计算资源是否充足确定第二权重，其中，候选对象所在的设备是计算资源充足的情况下的第二权重高于候选对象所在的设备是计算资源不足的情况下的第二权重。
方式四，针对M个候选对象中的任意一个候选对象，当候选对象相关的先验知识的约束条件为候选对象优先在音频播放性能佳的设备上运行时，电子设备根据候选对象所在设备中的音频播放性能高低确定第二权重，其中，候选对象所在的设备是音频播放性能佳的情况下的第二权重高于候选对象所在的设备是音频播放性能差的情况下的第二权重。
可选地，当对M个候选对象进行排序之后，本申请实施例还可以包括步骤905，电子设备将排序后M个候选对象显示到预设的推荐界面中。
在另一种可能的情况下，电子设备还可以从数据库或服务器上获取设备的标签，然后计算关键词与设备的标签之间的相似度，从而根据该相似度大小，确定K个设备对应的K个候选对象的第三权重。进一步地，电子设备可以根据第一权重、第二权重和第三权重，对K个候选对象进行排序。例如，客厅的智慧屏的标签包括视频、会议等，手机的标签包括打电话、上网等，手机可以从云服务器获取上述设备的标签，该标签可以是由开发商预设的内容，也可以是用户主动标记然后上传至云服务器的，对此，本申请并不限定。
具体来说，本申请实施例提供如图10所示的方法流程图，该方法包括如下步骤。
步骤1001，电子设备接收用户的搜索请求，该搜索请求包括用户输入的关键词。
具体可以参照上述步骤701。
步骤1002，在电子设备接收到输入词的过程中，电子设备可以实时判断用户是否结束输入，若否，则执行步骤1003a，否则执行步骤1003b。
示例性地，用户在输入“导航”的过程中，手机在接收到每一个字符的过程中，判断是否会已结束输入。
步骤1003a，若否，电子设备可以对已接收到的关键词进行广泛匹配，计算关键词与候选对象的标签之间的相似度。
示例性地，电子设备对已接收到的关键词“导”进行广泛匹配，计算关键词“导”与应用的标签之间的相似度，以及计算关键词“导”与设备的标签之间的相似度。
步骤1003b，若是，电子设备可以对接收的关键词进行精确匹配，计算关键词与候选对象的标签之间的相似度，计算候选对象相关的先验知识的约束条件与设备的状态之间的相似度。
示例性地，电子设备对已接收到的关键词“导航”进行精确匹配，计算关键词“导航”与应用的标签之间的相似度，以及计算关键词“导航”与设备的标签之间的相似度。
步骤1004，电子设备确定大于设定阈值的语义相似度所对应的M个候选对象的标签。
步骤1005，针对M个候选对象中的任意一个候选对象，电子设备根据关键词与该候选对象的标签之间的相似度确定第一权重，电子设备根据该候选对象相关的先验知识的约束条件与设备的状态之间的相似度确定第二权重，以及电子设备根据关键词与设备的标签之间的相似度确定第三权重。
步骤1006，电子设备根据第一权重、第二权重和第三权重，对各个候选对象进行排序。
本实施例中，这样排序之后的搜索结果具有如下特点：应用的标签或服务的标签与关键词语义更相近的应用，则该应用或服务的排序更靠前；设备的标签与关键词语义更相近 的设备的搜索结果在排序中更靠前；设备的状态与候选对象相关的先验知识的约束条件更匹配，则该设备的搜索结果在排序中更靠前。
综上，本申请实施例可以依据设备状态、应用或服务相关的先验证知识的约束条件和用户输入内容词义相关度综合排序，实现应用或服务的精准排序，当搜索结果中包括不同设备上的对应同一目标对象的应用标签或服务标签时，利用目标对象相关的先验证知识的约束条件和设备状态的匹配，可以实现对不同设备上的对应同一目标对象的应用或服务精准排序的目的。这样的排序结果可以更加精准地匹配用户想要搜索的应用或服务，有助于提升搜索效率，改善用户体验。
在本申请的另一些实施例中，本申请实施例公开了一种电子设备，如图11所示，该电子设备可以包括：触摸屏1101，其中，该触摸屏1101包括触控面板1106和显示屏1107；一个或多个处理器1102；存储器1103；一个或多个应用程序(未示出)；以及一个或多个计算机程序1104，上述各器件可以通过一个或多个通信总线1105连接。其中该一个或多个计算机程序1104被存储在上述存储器1103中并被配置为被该一个或多个处理器1102执行，该一个或多个计算机程序1104包括指令，上述指令可以用于执行如图7或图8或图9或图10相应实施例中的各个步骤。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机指令，当该计算机指令在电子设备上运行时，使得电子设备执行上述相关方法步骤实现上述实施例中的信息排序方法。
本申请实施例还提供了一种计算机程序产品，当该计算机程序产品在计算机上运行时，使得计算机执行上述相关步骤，以实现上述实施例中的信息排序方法。
另外，本申请的实施例还提供一种装置，这个装置具体可以是芯片，组件或模块，该装置可包括相连的处理器和存储器；其中，存储器用于存储计算机执行指令，当装置运行时，处理器可执行存储器存储的计算机执行指令，以使芯片执行上述各方法实施例中的信息排序方法。
其中，本申请实施例提供的电子设备、计算机存储介质、计算机程序产品或芯片均用于执行上文所提供的对应的方法，因此，其所能达到的有益效果可参考上文所提供的对应的方法中的有益效果，此处不再赘述。
通过以上实施方式的描述，所属领域的技术人员可以了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其他的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个装置，或一些特征可以丢弃，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其他的形式。
作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是一个物理单元或多个物理单元，即可以位于一个地方，或者也可以分布到多个不同地方。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该软件产品存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请各个实施例方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上内容，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (17)

  1. 一种信息排序方法，其特征在于，包括：
    接收用户的搜索请求，所述搜索请求包括用户输入的关键词；
    响应于所述搜索操作，显示推荐界面，所述推荐界面中的候选对象中有K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象，所述候选对象为候选应用和/或候选服务，K为大于或等于2的正整数；
    其中，所述K个候选对象的排序是根据所述关键词与所述K个候选对象的标签之间的语义相似度，以及所述K个设备的设备状态确定的。
  2. 根据权利要求1所述的方法，其特征在于，显示推荐界面之前，还包括：
    根据所述关键词，获取N个候选对象的标签，以及计算所述关键词与所述N个候选对象的标签之间的语义相似度；
    从所述N个候选对象的标签中，确定大于设定阈值的语义相似度所对应的M个候选对象的标签，其中，所述M个候选对象的标签中有所述K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象；M≤N，M和N为大于或等于2的正整数；
    根据所述关键词与所述K个候选对象的标签之间的语义相似度，以及所述K个设备的设备状态，对所述K个候选对象进行排序。
  3. 根据权利要求1或2所述的方法，其特征在于，所述K个设备的设备状态包括如下状态中的至少一个：
    设备的供电类型、设备的屏幕大小、设备的可用计算资源、设备性能与所述目标对象的相关性。
  4. 根据权利要求1至3任一项所述的方法，其特征在于，所述K个设备上的同一属性的目标对象为K个设备上的同一名称的目标对象；或者所述K个设备上的同一属性的目标对象为同一供应商的目标对象；或者所述K个设备上的同一属性的目标对象为K个设备上的同一安装包的目标对象；或者所述K个设备上的同一属性的目标对象为K个设备上的同一功能的目标对象。
  5. 根据权利要求2至4任一项所述的方法，其特征在于，所述根据所述关键词与所述K个候选对象的标签之间的语义相似度，以及所述K个设备的设备状态，对所述K个候选对象进行排序，包括：
    根据所述关键词与所述K个候选对象的标签之间的语义相似度，确定所述K个候选对象分别对应的第一权重；
    根据所述目标对象相关的先验知识的约束条件，与所述K个设备的设备状态之间的匹配度，确定所述K个候选对象分别对应的第二权重；
    根据所述第一权重和所述第二权重，对所述K个候选对象进行排序，其中，所述第一权重和所述第二权重的乘积越大的候选对象的排序越靠前。
  6. 根据权利要求5所述的方法，其特征在于，所述目标对象相关的先验知识的约束条件包括如下条件中的至少一个：
    所述目标对象优先在大屏设备上运行、所述目标对象优先在插电类型的设备上运行、所述目标对象优先在计算能力强的设备上运行，所述目标对象优先在音频播放性能佳的设备上运行。
  7. 根据权利要求5所述的方法，其特征在于，所述根据所述目标对象相关的先验知识的约束条件，与所述K个设备的设备状态之间的匹配度，确定所述K个候选对象分别对应的第二权重，包括：
    当所述目标对象相关的先验知识的约束条件为所述目标对象优先在插电类型的设备上运行时，确定所述K个候选对象对应的K个设备中支持插电类型的设备的对应的候选对象的第二权重大于不支持插电类型的设备的对应的候选对象的第二权重；
    或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在大屏设备上运行时，确定所述K个候选对象对应的K个设备中屏幕越大的设备对应的候选对象的第二权重越大；
    或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在计算能力强的设备上运行时，确定所述K个候选对象对应的K个设备中计算能力越强的设备对应的候选对象的第二权重越大；
    或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在音频播放性能佳的设备上运行时，确定所述K个候选对象对应的K个设备中音频播放性能越佳的设备的第二权重越大。
  8. 根据权利要求1至7任一项所述的方法，其特征在于，根据所述关键词，获取N个候选对象的标签，包括：
    从数据库获取所述K个设备上的L个候选对象的详情信息；
    从L个候选对象的详情信息中提取原始关键词，对所述原始关键词进行语义解析，从解析结果中获取L个候选对象的标签，
    根据所述关键词与所述L个候选对象的标签的匹配度，从L个候选对象的标签中获取N个候选对象的标签。
  9. 一种电子设备，其特征在于，所述电子设备包括处理器和存储器；
    所述存储器存储有程序指令；
    所述处理器用于运行所述存储器存储的所述程序指令，使得所述电子设备执行：
    接收用户的搜索请求，所述搜索请求包括用户输入的关键词；
    响应于所述搜索操作，显示推荐界面，所述推荐界面中的候选对象中有K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象，所述候选对象为候选应用和/或候选服务，K为大于或等于2的正整数；
    其中，所述K个候选对象的排序是根据所述关键词与所述K个候选对象的标签之间的语义相似度，以及所述K个设备的设备状态确定的。
  10. 根据权利要求9所述的电子设备，其特征在于，显示推荐界面之前，还包括：
    根据所述关键词，获取N个候选对象的标签，以及计算所述关键词与所述N个候选对象的标签之间的语义相似度；
    从所述N个候选对象的标签中，确定大于设定阈值的语义相似度所对应的M个候选对象的标签，其中，所述M个候选对象的标签中有所述K个候选对象的标签对应于安装在K个设备上的同一属性的目标对象；M≤N，M和N为大于或等于2的正整数；
    根据所述关键词与所述K个候选对象的标签之间的语义相似度，以及所述K个设备的设备状态，对所述K个候选对象进行排序。
  11. 根据权利要求9或10所述的电子设备，其特征在于，所述K个设备的设备状态包括如下状态中的至少一个：
    设备的供电类型、设备的屏幕大小、设备的可用计算资源、设备性能与所述目标对象的相关性。
  12. 根据权利要求9至11任一项所述的电子设备，其特征在于，所述K个设备上的同一属性的目标对象为K个设备上的同一名称的目标对象；或者所述K个设备上的同一属性的目标对象为同一供应商的目标对象；或者所述K个设备上的同一属性的目标对象为K个设备上的同一安装包的目标对象；或者所述K个设备上的同一属性的目标对象为K个设备上的同一功能的目标对象。
  13. 根据权利要求10至12任一项所述的电子设备，其特征在于，所述处理器用于运行所述存储器存储的所述程序指令，使得所述电子设备具体执行：
    根据所述关键词与所述K个候选对象的标签之间的语义相似度，确定所述K个候选对象分别对应的第一权重；
    根据所述目标对象相关的先验知识的约束条件，与所述K个设备的设备状态之间的匹配度，确定所述K个候选对象分别对应的第二权重；
    根据所述第一权重和所述第二权重，对所述K个候选对象进行排序，其中，所述第一权重和所述第二权重的乘积越大的候选对象的排序越靠前。
  14. 根据权利要求13所述的电子设备，其特征在于，所述目标对象相关的先验知识的约束条件包括如下条件中的至少一个：
    所述目标对象优先在大屏设备上运行、所述目标对象优先在插电类型的设备上运行、所述目标对象优先在计算能力强的设备上运行，所述目标对象优先在音频播放性能佳的设备上运行。
  15. 根据权利要求13所述的电子设备，其特征在于，所述处理器用于运行所述存储器存储的所述程序指令，使得所述电子设备在确定所述K个候选对象分别对应的第二权重时，具体执行：
    当所述目标对象相关的先验知识的约束条件为所述目标对象优先在插电类型的设备上运行时，确定所述K个候选对象对应的K个设备中支持插电类型的设备的对应的候选对象的第二权重大于不支持插电类型的设备的对应的候选对象的第二权重；
    或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在大屏设备上运行时，确定所述K个候选对象对应的K个设备中屏幕越大的设备对应的候选对象的第二权重越大；
    或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在计算能力强的设备上运行时，确定所述K个候选对象对应的K个设备中计算能力越强的设备对应的候选对象的第二权重越大；
    或者，当所述目标对象相关的先验知识的约束条件为所述目标对象优先在音频播放性能佳的设备上运行时，确定所述K个候选对象对应的K个设备中音频播放性能越佳的设备的第二权重越大。
  16. 根据权利要求9至15任一项所述的电子设备，其特征在于，所述处理器用于运行所述存储器存储的所述程序指令，使得所述电子设备具体执行：
    从数据库获取所述K个设备上的L个候选对象的详情信息；
    从L个候选对象的详情信息中提取原始关键词，对所述原始关键词进行语义解析，从解析结果中获取L个候选对象的标签，
    根据所述关键词与所述L个候选对象的标签的匹配度，从L个候选对象的标签中获取N个候选对象的标签。
  17. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质包括程序指令，当所述程序指令在电子设备上运行时，使得所述电子设备执行如权利要求1至8任一项所述的方法。
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