WO2022100221A1 - 检索处理方法、装置及存储介质 - Google Patents

检索处理方法、装置及存储介质 Download PDF

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Publication number
WO2022100221A1
WO2022100221A1 PCT/CN2021/115824 CN2021115824W WO2022100221A1 WO 2022100221 A1 WO2022100221 A1 WO 2022100221A1 CN 2021115824 W CN2021115824 W CN 2021115824W WO 2022100221 A1 WO2022100221 A1 WO 2022100221A1
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WIPO (PCT)
Prior art keywords
data
search
target
search term
index table
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PCT/CN2021/115824
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English (en)
French (fr)
Inventor
毕浩
杨俊拯
钟卫东
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Oppo广东移动通信有限公司
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Publication of WO2022100221A1 publication Critical patent/WO2022100221A1/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
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/31—Indexing; Data structures therefor; Storage structures
    • G06F16/316—Indexing structures
    • 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
    • G06F16/335—Filtering based on additional data, e.g. user or group profiles
    • 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
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/253—Grammatical analysis; Style critique
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Definitions

  • the present application relates to the technical field of information processing, and in particular, to a retrieval processing method, device and storage medium.
  • Embodiments of the present application provide a retrieval processing method, device, and storage medium, which can implement a retrieval function, realize the retrieval function, and improve user experience.
  • an embodiment of the present application provides a retrieval processing method, which is applied to an electronic device, and the method includes:
  • Data collection is performed according to the search terms to obtain target data
  • the first index table is queried according to the query expression to obtain at least one search result.
  • an embodiment of the present application provides a retrieval processing apparatus, which is applied to an electronic device.
  • the apparatus includes: an acquisition unit, a processing unit, a collection unit, an update unit, and a search unit, wherein,
  • the obtaining unit is used to obtain the input search term
  • the processing unit configured to process the search term to obtain a query expression
  • the collection unit is configured to collect data according to the search term to obtain target data
  • the updating unit configured to update the preset index table according to the target data to obtain the first index table
  • the search unit is configured to query the first index table according to the query expression to obtain at least one search result.
  • embodiments of the present application provide an electronic device, the electronic device includes a processor and a memory, the memory is configured to store one or more programs, and is configured to be executed by the processor, the programs include Instructions for performing steps in a method as claimed in any one of the first aspects of claim.
  • an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the computer program as described in the first embodiment of the present application.
  • an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute as implemented in the present application. Examples include some or all of the steps described in the first aspect.
  • the computer program product may be a software installation package.
  • FIG. 1 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • FIG. 2 is a schematic diagram of a software structure of an electronic device provided by an embodiment of the present application.
  • 3A is a schematic flowchart of a retrieval processing method provided by an embodiment of the present application.
  • 3B is a schematic flowchart of another retrieval processing method provided by an embodiment of the present application.
  • 3C is a schematic diagram illustrating a word segmentation process provided by an embodiment of the present application.
  • 3D is a schematic flowchart of another retrieval processing method provided by an embodiment of the present application.
  • 3E is a schematic diagram illustrating a merge tree structure provided by an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of another retrieval processing method provided by an embodiment of the present application.
  • FIG. 5 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • 6A is a block diagram of functional units of a retrieval processing apparatus provided by an embodiment of the present application.
  • FIG. 6B is a block diagram of functional units of a retrieval processing apparatus provided by an embodiment of the present application.
  • Electronic devices may include devices with various ultra wide band (UWB) modules, such as smartphones, in-vehicle devices (navigators, driving recorders, radar rangefinders, ETC payment mounts, etc.), wearable devices, Smart watches, base station equipment, tag equipment, walkie-talkies, smart glasses, wireless Bluetooth headsets, computing equipment or other processing equipment connected to wireless modems, and various forms of user equipment (User Equipment, UE), mobile stations (Mobile Station, MS), virtual reality/augmented reality devices, terminal devices, etc.
  • UWB ultra wide band
  • 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, compass 190, motor 191, indicator 192, camera 193, display screen 194 and user Identity module (subscriber identification module, SIM) card interface 195 and so on.
  • SIM subscriber identification module
  • 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 AP, a modem processor, a graphics processor GPU, an image signal processor (image signal processor, ISP), a controller, Video codec, digital signal processor (DSP), baseband processor, and/or neural network processor NPU, etc. Wherein, different processing units may be independent components, or may be integrated in one or more processors.
  • the electronic device 101 may also include one or more processors 110 .
  • the controller can generate an operation control signal according to the instruction operation code and the timing signal, and complete the control of fetching and executing instructions.
  • a memory may also be provided in the processor 110 for storing instructions and data.
  • the memory in the processor 110 may be a cache memory. This memory may hold instructions or data that have just been used or recycled by the processor 110 . If the processor 110 needs to use the instruction or data again, it can be called directly from memory. In this way, repeated access is avoided, and the waiting time of the processor 110 is reduced, thereby improving the efficiency of the electronic device 101 in processing data or executing instructions.
  • the processor 110 may include one or more interfaces.
  • the interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous transceiver (universal) asynchronous receiver/transmitter, UART) interface, mobile industry processor interface (mobile industry processor interface, MIPI), general-purpose input/output (GPIO) interface, SIM card interface and/or USB interface, etc.
  • the USB interface 130 is an interface that conforms to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, and the like.
  • the USB interface 130 can be used to connect a charger to charge the electronic device 101, and can also be used to transmit data between the electronic device 101 and peripheral devices.
  • the USB interface 130 can also be used to connect an earphone, and play audio through the earphone.
  • the interface connection relationship between the modules illustrated in the embodiments of the present application is only a schematic illustration, and does not constitute a structural limitation of the electronic device 100 .
  • the electronic device 100 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.
  • the charging management module 140 is used to receive charging input from the charger.
  • the charger may be a wireless charger or a wired charger.
  • the charging management module 140 may receive charging input from the wired charger through the USB interface 130 .
  • the charging management module 140 may receive wireless charging input through a wireless charging coil of the electronic device 100 . While the charging management module 140 charges the battery 142 , it can also supply power to the electronic device through the power management module 141 .
  • the power management module 141 is used for connecting the battery 142 , the charging management module 140 and the processor 110 .
  • the power management module 141 receives input from the battery 142 and/or the charging management module 140, and supplies power to the processor 110, the internal memory 121, the external memory, the display screen 194, the camera 193, the wireless communication module 160, and the like.
  • the power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle times, battery health status (leakage, impedance).
  • the power management module 141 may also be provided in the processor 110 .
  • the power management module 141 and the charging management module 140 may also be provided in the same device.
  • 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 a wireless communication solution including 2G/3G/4G/5G/6G 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 Satellite system (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), near field communication technology (near field communication, NFC), infrared technology (infrared, IR), UWB modules and other wireless communication solutions.
  • WLAN wireless local area networks
  • BT wireless fidelity
  • GNSS global navigation Satellite system
  • frequency modulation frequency modulation, FM
  • NFC near field communication technology
  • infrared technology infrared, IR
  • UWB modules wireless communication solutions.
  • 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
  • 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 display screen 194 is used to display images, videos, and the like.
  • Display screen 194 includes a display panel.
  • the display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active matrix organic light emitting diode, or an active matrix organic light emitting diode (active-matrix organic light).
  • emitting diode, AMOLED flexible light-emitting diode (flex light-emitting diode, FLED), mini light-emitting diode (mini light-emitting diode, miniled), MicroLed, Micro-oLed, quantum dot light-emitting diode (quantum dot light emitting diodes, QLED), etc.
  • electronic device 100 may include one or more display screens 194 .
  • 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 ISP is used to process the data fed back by the camera 193 .
  • the shutter is opened, the light is transmitted to the camera photosensitive element through the lens, the light signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to the ISP for processing, converting it into an image visible to the naked eye.
  • ISP can also perform algorithm optimization on image noise, brightness, and skin tone.
  • ISP can also optimize parameters such as exposure and color temperature of the shooting scene.
  • the ISP may be provided in the camera 193 .
  • Camera 193 is used to capture still images or video.
  • the object is projected through the lens to generate an optical image onto the photosensitive element.
  • the photosensitive element may be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor.
  • CMOS complementary metal-oxide-semiconductor
  • the photosensitive element converts the optical signal into an electrical signal, and then transmits the electrical signal to the ISP to convert it into a digital image signal.
  • the ISP outputs the digital image signal to the DSP for processing.
  • DSP converts digital image signals into standard RGB, YUV and other formats of image signals.
  • the electronic device 100 may include one or more cameras 193 .
  • a digital signal processor is used to process digital signals, in addition to processing digital image signals, it can also process other digital signals. For example, when the electronic device 100 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy and so on.
  • Video codecs are used to compress or decompress digital video.
  • the electronic device 100 may support one or more video codecs.
  • the electronic device 100 can play or record videos in various encoding formats, such as: Moving Picture Experts Group (moving picture experts group, MPEG) 1, MPEG2, MPEG3, MPEG4, and so on.
  • MPEG Moving Picture Experts Group
  • the NPU is a neural-network (NN) computing processor.
  • NN neural-network
  • Applications such as intelligent cognition of the electronic device 100 can be implemented through the NPU, such as image recognition, face recognition, speech recognition, text understanding, and the like.
  • the external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100 .
  • the external memory card communicates with the processor 110 through the external memory interface 120 to realize the data storage function. For example to save files like music, video etc in external memory card.
  • Internal memory 121 may be used to store one or more computer programs including instructions.
  • the processor 110 may execute the above-mentioned instructions stored in the internal memory 121, thereby causing the electronic device 101 to execute the method for displaying page elements, various applications and data processing provided in some embodiments of the present application.
  • the internal memory 121 may include a storage program area and a storage data area.
  • the stored program area may store the operating system; the stored program area may also store one or more applications (such as gallery, contacts, etc.) and the like.
  • the storage data area may store data (such as photos, contacts, etc.) created during the use of the electronic device 101 and the like.
  • the internal memory 121 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic disk storage components, flash memory components, universal flash storage (UFS), and the like.
  • the processor 110 may cause the electronic device 101 to execute the instructions provided in the embodiments of the present application by executing the instructions stored in the internal memory 121 and/or the instructions stored in the memory provided in the processor 110 .
  • the electronic device 100 may implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, an application processor, and the like. Such as music playback, recording, etc.
  • the sensor module 180 may include a pressure sensor 180A, a gyro 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 an ambient light sensor 180L, bone conduction sensor 180M, etc.
  • the pressure sensor 180A is used to sense pressure signals, and can convert the pressure signals into electrical signals.
  • the pressure sensor 180A may be provided on the display screen 194 .
  • the capacitive pressure sensor may be comprised of at least two parallel plates of conductive material. When a force is applied to the pressure sensor 180A, the capacitance between the electrodes changes.
  • the electronic device 100 determines the intensity of the pressure according to the change in capacitance. When a touch operation acts on the display screen 194, the electronic device 100 detects the intensity of the touch operation according to the pressure sensor 180A.
  • the electronic device 100 may also calculate the touched position according to the detection signal of the pressure sensor 180A.
  • touch operations acting on the same touch position but with different touch operation intensities may correspond to different operation instructions. For example, when a touch operation whose intensity is less than the first pressure threshold acts on the short message application icon, the instruction for viewing the short message is executed. When a touch operation with a touch operation intensity greater than or equal to the first pressure threshold acts on the short message application icon, the instruction to create a new short message is executed.
  • the gyro sensor 180B may be used to determine the motion attitude of the electronic device 100 .
  • the angular velocity of electronic device 100 about three axes i.e., X, Y, and Z axes
  • the gyro sensor 180B can be used for image stabilization.
  • the gyro sensor 180B detects the shaking angle of the electronic device 100, calculates the distance that the lens module needs to compensate according to the angle, and allows the lens to offset the shaking of the electronic device 100 through reverse motion to achieve anti-shake.
  • the gyro sensor 180B can also be used for navigation and somatosensory game scenarios.
  • the acceleration sensor 180E can detect the magnitude of the acceleration of the electronic device 100 in various directions (generally three axes).
  • the magnitude and direction of gravity can be detected when the electronic device 100 is stationary. It can also be used to identify the posture of electronic devices, and can be used in applications such as horizontal and vertical screen switching, pedometers, etc.
  • the ambient light sensor 180L is used to sense ambient light brightness.
  • the electronic device 100 can adaptively adjust the brightness of the display screen 194 according to the perceived ambient light brightness.
  • the ambient light sensor 180L can also be used to automatically adjust the white balance when taking pictures.
  • the ambient light sensor 180L can also cooperate with the proximity light sensor 180G to detect whether the electronic device 100 is in a pocket, so as to prevent accidental touch.
  • the fingerprint sensor 180H is used to collect fingerprints.
  • the electronic device 100 can use the collected fingerprint characteristics to realize fingerprint unlocking, accessing application locks, taking pictures with fingerprints, answering incoming calls with fingerprints, and the like.
  • the temperature sensor 180J is used to detect the temperature.
  • the electronic device 100 uses the temperature detected by the temperature sensor 180J to execute a temperature processing strategy. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold value, the electronic device 100 reduces the performance of the processor located near the temperature sensor 180J in order to reduce power consumption and implement thermal protection.
  • the electronic device 100 when the temperature is lower than another threshold, the electronic device 100 heats the battery 142 to avoid abnormal shutdown of the electronic device 100 caused by the low temperature.
  • the electronic device 100 boosts the output voltage of the battery 142 to avoid abnormal shutdown caused by low temperature.
  • Touch sensor 180K also called “touch panel”.
  • the touch sensor 180K may be disposed on the display screen 194 , and the touch sensor 180K and the display screen 194 form a touch screen, also called a “touch screen”.
  • the touch sensor 180K is used to detect a touch operation on or near it.
  • the touch sensor can pass the detected touch operation to the application processor to determine the type of touch event.
  • Visual output related to touch operations may be provided through display screen 194 .
  • the touch sensor 180K may also be disposed on the surface of the electronic device 100 , which is different from the location where the display screen 194 is located.
  • FIG. 2 shows a software structural block diagram of the electronic device 100 .
  • 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, from top to bottom, an application layer, an application framework layer, an Android runtime (Android runtime) and a system library, and a kernel layer.
  • the application layer can include a series of application packages.
  • the application layer can include applications such as camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, and short messages.
  • the application framework layer provides an application programming interface (application programming interface, API) and a programming framework for applications in the application layer.
  • the application framework layer includes some predefined functions.
  • the application framework layer may include window managers, content providers, view systems, telephony managers, resource managers, notification managers, and the like.
  • a window manager is used to manage window programs.
  • the window manager can get the size of the display screen, determine whether there is a status bar, lock the screen, take screenshots, etc.
  • Content providers are used to store and retrieve data and make these data accessible to applications.
  • Data can include videos, images, audio, calls made and received, browsing history and bookmarks, phone book, etc.
  • the view system includes visual controls, such as controls for displaying text, controls for displaying pictures, and so on. View systems can be used to build applications.
  • a display interface can consist of one or more views.
  • the display interface including the short message notification icon may include a view for displaying text and a view for displaying pictures.
  • the phone manager is used to provide the communication function of the electronic device 100 .
  • the management of call status including connecting, hanging up, etc.).
  • the resource manager provides various resources for the application, such as localization strings, icons, pictures, layout files, video files and so on.
  • the notification manager enables applications to display notification information in the status bar, which can be used to convey notification-type messages, and can disappear automatically after a brief pause without user interaction. For example, the notification manager is used to notify download completion, message reminders, etc.
  • the notification manager can also display notifications in the status bar at the top of the system in the form of graphs or scroll bar text, such as notifications from applications running in the background, and notifications that appear on the screen in the form of dialog windows. For example, text information is prompted in the status bar, a prompt sound is issued, the electronic device vibrates, and the indicator light flashes.
  • Android Runtime includes core libraries and a virtual machine. Android runtime is responsible for scheduling and management of the Android system.
  • the core library consists of two parts: one is the function functions that the java language needs to call, and the other is the core library of Android.
  • the application layer and the application framework layer run in virtual machines.
  • the virtual machine executes the java files of the application layer and the application framework layer as binary files.
  • the virtual machine is used to perform functions such as object lifecycle management, stack management, thread management, safety and exception management, and garbage collection.
  • a system library can include multiple functional modules. For example: surface manager (surface manager), media library (media library), 3D graphics processing library (eg: OpenGL ES), 2D graphics engine (eg: SGL), etc.
  • surface manager surface manager
  • media library media library
  • 3D graphics processing library eg: OpenGL ES
  • 2D graphics engine eg: SGL
  • the Surface Manager is used to manage the display subsystem and provides a fusion of 2D and 3D layers for multiple applications.
  • the media library supports playback and recording of a variety of commonly used audio and video formats, as well as still image files.
  • the media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.
  • the 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.
  • 2D graphics engine is a drawing engine for 2D drawing.
  • 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.
  • FIG. 3A is a schematic flowchart of a retrieval processing method provided by an embodiment of the application, applied to an electronic device.
  • the retrieval processing method includes:
  • the search term can be input by the user or pushed by the system.
  • the search term can be at least one of the following: Chinese characters, English sentences, character strings, German sentences, French sentences, dialect sentences, Japanese sentences, Korean sentences, images, videos, documents, etc., which are not limited here.
  • the electronic device can input search words through the touch screen.
  • the search term can be converted into text content, and then a subsequent search is performed.
  • step 301 acquiring the input search term, may include the following steps:
  • A32 Analyze the target speech segment to obtain the search term.
  • the electronic device can collect the target speech segment input by the user, convert the target speech segment into text, and perform semantic recognition on the text to obtain search words.
  • step 301 acquiring the input search term, may include the following steps:
  • the electronic device can obtain input content through an input circuit
  • the input circuit can be at least one of the following: a microphone, a touch display screen, a stylus, a mouse, a keyboard, etc., which are not limited here.
  • the electronic device can obtain the input content, and when the input content is not text content, it can convert the input content into target text content by means of character recognition, speech recognition, image recognition, etc., and perform keyword extraction on the target text content, The search terms are obtained, so that subsequent searches can be facilitated.
  • the electronic device may perform lexical analysis and syntax analysis on the search term, and convert it into a corresponding query expression, and the query expression may be a suffix expression (such as a reverse Polish expression).
  • processing the search term to obtain a query expression may include the following steps:
  • the electronic device may perform lexical analysis on the user's query, that is, perform at least one processing on the query through a lexical analyzer: normalization, synonym conversion, word segmentation, and removal of stop words, which are not limited here. Further, a plurality of first term lists (term lists) after word segmentation can be obtained, and further, grammatical analysis can be performed. The first is to analyze the relationship between the first term list, and finally generate a query expression. Because it is developed on electronic equipment, it adopts a simple configuration method. The relationship between different term lists (terms) can be hit all or hit one term. Replacing it with a data formula supports the OR operation (or,
  • query global box office rankings
  • term global
  • term box office
  • term rankings
  • relationship between terms is configured, then it is parsed as query expression 1&2&3, where the number is term Identification, for example, where 1 represents the term for the global term; 2 represents the term for the box office.
  • the infix expression is an infix expression, which is more in line with human thinking logic, but is difficult for computers to process. Therefore, the infix expression can also be converted into a postfix expression that is easier for computers to process ( Reverse Polish expressions, combined with stacks, can easily complete arithmetic sums). For example, the query expression 1&2&3 is converted to 12&3&.
  • the electronic device may collect local data or push data of a third-party application according to a search term to obtain target data, where the local data may be at least one of the following: local media data, address book data, Usage log data of third-party apps.
  • the third-party application may agree with the electronic device in advance on applications that are allowed to be retrieved.
  • the third-party application may be at least one of the following: game application, video application, audio application, instant messaging application, shopping application, weather application, payment application, etc., which are not limited herein.
  • the search engine when the search engine is started for the first time, all the data in the corresponding module will be obtained once, and the data will be stored in the In the search engine device, on the other hand, the user's data is updated and changed. Therefore, a listener can be registered on the above module. When the user's data changes, the data collection module can be notified in time and respond accordingly.
  • steps 302 and 303 may be executed synchronously or asynchronously. When executed synchronously, steps 302 and 303 may be executed by a process or thread respectively.
  • step 303 data collection is performed according to the search term to obtain target data, which can be implemented as follows:
  • the target data is obtained by acquiring the push or usage record data of the third-party application according to the search term.
  • the electronic device obtains local media data of a preset time period according to the search term, that is, the target data related to the search term can be obtained.
  • the local media data can be at least one of the following: image, audio, video, file (word text, PDF text, PPT, etc.), which is not limited here, and the preset time period can be set by the user or the system defaults; and/or , the electronic device can also obtain the local address book data according to the search term, and obtain the target data; and/or, the electronic device can obtain the push or usage record data of the third-party application according to the search term, and obtain the target data, that is, in the embodiment of the present application,
  • the electronic device can provide an open API. After the third-party application completes the authentication, it can push data one by one to the electronic device for data processing through the corresponding API interface, and the data update action can be marked as adding , delete, update.
  • step 303 data collection is performed according to the search term to obtain target data, which may include the following steps:
  • the preset time period may be set by the user or the system defaults.
  • the electronic device can obtain historical data of a preset time period, filter the historical data according to the search terms, and obtain the filtered historical data. Determine the priority order of the filtered historical data, and perform queue processing on the filtered historical data according to the priority order to obtain target data. Time determines the priority order. In this way, the response to different data will be different in the way of passing the priority queue.
  • a high-priority queue can be used to process the data to complete the timely update of the data, which helps to improve the efficiency of subsequent data retrieval.
  • the preset index table may be pre-stored in a database (database, DB), and the preset index table may be an inverted table, and at least one of the following information may be pre-stored in the inverted table: term list name, term list corresponding The number of documents, document identification, document size, document usage frequency, etc., are not limited here.
  • step 304 updating the preset index table according to the target data to obtain the first index table, may include the following steps:
  • the nodes in the preset index table store the identifiers corresponding to the data, and according to these identifiers, the reference data corresponding to the preset index table can be obtained, and further, the target data can be compared with the reference data, and it is obtained that the target data does not exist in the reference data.
  • the data to be updated in the data can then be subjected to lexical analysis.
  • the lexical analyzer performs at least one process on the data to be updated: normalization, synonym conversion, word segmentation, and removal of stop words, which are not described here. Restriction, at least one second term list is obtained, and the preset index table is updated according to the at least one second term list, that is, the index of the updated data is spliced into the preset index table, and then the first index table can be obtained.
  • the first index table may be an inverted table, and the query expression may be processed as a tree structure, such as a binary tree, and the electronic device may query the first index table according to the binary tree to obtain at least one search result.
  • fuzzy search or precise search can be realized, specifically, according to the accuracy of the search term or the update degree of the index table, for example, when the search term is a fuzzy term, a fuzzy search can be realized, and for example, if the search term is a precise term If the index table is not updated in time or the updated data is small, then the fuzzy search can be realized. For another example, if the index table is updated in time or the updated data is sufficient, the accurate search can be realized.
  • the first index table is queried according to the query expression to obtain at least one search result, which may include the following steps:
  • the first index table since the first index table is pre-stored in the database, it is an inverted table.
  • the electronic device may generate a merged tree structure based on the query expression, and at least one of the following information may be pre-stored in the inverted table: term list name, number of documents corresponding to the term list, document ID, document size, document usage frequency, etc. Not limited.
  • the electronic device can obtain the inverted zipper data corresponding to each node in the first index table according to the merged tree structure, and perform a query based on the inverted zipper data to obtain at least one search result.
  • steps 306-307 may also be included, as follows:
  • the preset algorithm can be set by the user or the system defaults, the preset algorithm can be at least one algorithm, and the preset algorithm can be at least one of the following: term frequency-inverse document frequency (term frequency-inverse document frequency, TF/ IDF), pomegranate algorithm, lulu algorithm, lulu algorithm, hurricane algorithm, original spark plan, poplar algorithm, light boat algorithm, thunder algorithm, skynet algorithm, beacon algorithm, drizzle algorithm, pomegranate algorithm, aurora algorithm, lightning algorithm, blue sky algorithm , Ice Bucket Algorithm, Panda Algorithm, Penguin Algorithm, etc., which are not limited here.
  • the electronic device may use a preset algorithm to determine the degree of relevancy between each search result in the at least one search result and the search term, and obtain at least one degree of relevancy.
  • a preset algorithm is used to determine the correlation between each search result in the at least one search result and the search term degree to obtain at least one correlation degree, which may include the following steps:
  • the target algorithm determine the degree of relevancy between each of the at least one search result and the search term to obtain at least one degree of relevancy.
  • the search term type can be determined according to the format of the search term, and the search term type can be at least one of the following: audio type, video type, image type, text type, etc., which are not limited here.
  • the type of search terms can also be determined according to the number of search terms, another example, the type of search terms can be determined according to the complexity of the search terms, and the type of search terms can also be determined according to the popularity of the search terms. It can be at least one of the following: hot words, low-frequency words, general hot words, etc., which are not limited here.
  • the electronic device can pre-store the relationship between the preset algorithm and the search term type. Then, after the electronic device determines the target search term type corresponding to the search term, according to the mapping relationship between the preset algorithm and the search term type, the target algorithm corresponding to the target search term type is determined, and then, according to the mapping relationship between the preset algorithm and the search term type The target algorithm determines the degree of relevancy between each search result in the at least one search result and the search term, obtains at least one degree of relevancy, and further helps to determine the degree of relevancy of the search result.
  • the electronic device can display at least one search result according to the high-relevance priority display principle, and then the high-relevance search results can be displayed preferentially, and the low-relevance search results can be hidden or displayed after the high-relevance search results are displayed. exhibit.
  • the search engine is divided into two data streams, one of which is the processing stream of the data on the user's mobile phone.
  • application data or cooperative third-party application data is parsed according to the customized configuration, the data is processed and stored in the search system.
  • what is finally returned to the user is the document, application, audio, video and other data that match the search term.
  • the data processing process is the process of collecting and storing user data.
  • the development on the software has very high requirements on the reliability and stability of the software, and the timely repair of the server cannot be achieved.
  • the stability requirements make it unsuitable to put some complex logic on the mobile phone as an example, but the search engine is a very complex project, which needs to be implemented in a better way.
  • light weight can be used.
  • magnitude DB to store the inverted table.
  • the inverted table stores key information such as the name of the term queue (term), the number of corresponding documents, and the list of document IDs.
  • the first step in the data processing process is to collect data.
  • data There are mainly two types of data that can be accessed into the search system. One is the data that the user has authorized to access on the mobile phone as an example, and the other is the third party that cooperates with.
  • the data in the corresponding module can be obtained in full when the search engine is started for the first time, and the data is stored in the search engine device. There are updates and changes in data, so register a listener on these modules, and the data collection module can be notified in time and respond to changes when the user's data changes.
  • an open API is provided. After the third-party application completes the authentication, it can push the data one by one to the data collection module for data processing through this API, and the data update actions need to be marked as add, delete, and update.
  • the index After completing the action of data collection, for each piece of data, the index needs to be updated through the processing of the indexing engine.
  • the lexical analyzer will be called to normalize the data, convert synonyms, segment words, and remove stop words. , and finally form a term list, and retain the term frequency, position information in the document, etc., and then update it to the inverted list storage to complete the data update, as shown in Figure 3C, which is the lexical analyzer processing flow
  • the sample data processing process in , specifically, for example, the search term is "Global Movie Ranking List", and the traditional Chinese characters and capitalization are normalized to obtain "Global Movie Ranking List”. Word processing, get “Global Movie Ranking List”, and finally remove stop words to get "Global Movie Ranking List”.
  • FIG. 3D it is another data flow that is the user’s search term processing process, the input of the processing is the user’s search term, and the output is all matched data result sets recorded in the search system, which can be Including the following steps 1-6:
  • the query expression 1&2&3 is converted to 12&3&.
  • the merge engine is processed, and the structure suffix expression after the syntax analysis is generated into a merge tree structure. Convert the query expression into a binary tree structure for storage, which is convenient for subsequent merge operations.
  • the nodes of the binary tree include operator nodes and term nodes.
  • the term node is a leaf node and records the id corresponding to the term and some key information of the term.
  • the operator node has left and right child nodes, which are arithmetic nodes that operate on the left and right child nodes. It is necessary to query the indexing engine to obtain the inverted zipper data corresponding to each term node.
  • the index engine stores all the index information that has been stored in the current system, stores the inverted zipper information one by one, and queries the inverted table of the db according to the name of the term to obtain the corresponding inverted data.
  • the term field is indexed in db in advance, and the corresponding inverted zipper can be queried in a very short time by using the index mechanism of db's B+ tree.
  • the time complexity is only O(log2N), even in the face of millions of The number of terms can also be loaded into memory in a very short period of time.
  • ) calculation is to find the union between two zippers
  • the AND (&) calculation is to find the intersection of the two zippers, as shown in Figure 3E.
  • the term set hit by each document needs to be recorded as part of the input of the correlation calculation in the next step.
  • TF/IDF is an algorithm commonly used in the industry to evaluate the correlation.
  • the core idea is that the more a document contains a term, the higher the correlation between the document and the term is considered. This is the document term frequency (term frequency), If the frequency of a certain term in all documents is about high, it is considered that the term is less important. This is the inverse document term frequency (inverse term frequency).
  • the correlation between the search term and the hit document is scored. , to get the relevance score.
  • step 301 before acquiring the input search term, may further include the following steps:
  • the target identity information may be at least one of the following: character strings, touch parameters, face images, fingerprint images, palmprint images, vein images, brain waves, voiceprints, etc. Do limit.
  • the electronic device can obtain the user's target identity information, and can verify the target identity information.
  • step 301 is performed, otherwise, subsequent steps are not performed.
  • step C2-step C3 when the target identity information is a target face image, between step C2-step C3, the following steps may also be included:
  • the preset face template may be stored in the electronic device in advance, and the preset image quality evaluation value and the preset matching threshold may be set by the user or the system defaults.
  • the electronic device can use at least one image quality evaluation index to evaluate the image quality of the target face image, and obtain the target image quality evaluation value, and the image quality evaluation index can be at least one of the following: information entropy, average gradient, average gray degree, contrast, etc., which are not limited here.
  • the target image quality evaluation value is greater than the preset image quality evaluation value, matching the target face image with the preset face template may be performed to obtain the target matching value; otherwise, re-authentication may be required.
  • step C4 determining the target image quality evaluation value of the target face image, may include the following steps:
  • the memory in the electronic device may pre-store the preset mapping relationship between the distribution density of feature points and the image quality evaluation value, the preset mapping relationship between the signal-to-noise ratio and the image quality deviation value, and the preset mapping relationship between the signal-to-noise ratio and the image quality deviation value.
  • the mapping relationship between the shooting parameters and the optimization coefficient wherein the value range of the image quality evaluation value may be 0-1, or may also be 0-100.
  • the image quality deviation value may be a positive real number, for example, 0 to 1, or may be greater than 1.
  • the value range of the optimization coefficient may be between -1 and 1, for example, the optimization coefficient may be -0.1 to 0.1.
  • the shooting parameters may be at least one of the following: exposure duration, shooting mode, ISO sensitivity, white balance parameters, focal length, focus, area of interest, etc., which are not limited herein.
  • the electronic device can determine the target feature point distribution density and the target signal-to-noise ratio of the target face image, and determine the target feature point distribution density according to the preset mapping relationship between the feature point distribution density and the image quality evaluation value.
  • the corresponding first image quality evaluation value, the feature point distribution density reflects the image quality to a certain extent, and the feature point distribution density can be understood as the ratio between the total number of feature points of the target face image and the image area of the target face image .
  • the electronic device can determine the target image quality deviation value corresponding to the target signal-to-noise ratio according to the preset mapping relationship between the signal-to-noise ratio and the image quality deviation value. angle, jitter, etc.) or internal (system, GPU) reasons, some noise will be generated, and these noises will have some impact on the image quality. Therefore, the image quality can be adjusted to a certain extent to ensure an objective evaluation of the image quality.
  • the electronic device can also acquire the first shooting parameter of the target face image, and the first shooting parameter can also be carried in the communication connection request, and further, according to the preset mapping relationship between the shooting parameters and the optimization coefficient, Determine the target optimization coefficient corresponding to the first shooting parameter.
  • the shooting parameter setting may also have a certain impact on the image quality evaluation. Therefore, it is necessary to determine the impact components of the shooting parameters on the image quality.
  • the target image quality The deviation value adjusts the first image quality evaluation value to obtain the target image quality evaluation value, wherein the target image quality evaluation value can be obtained according to the following formula:
  • Target image quality evaluation value (first image quality evaluation value+target image quality deviation value)*(1+target optimization coefficient)
  • Target image quality evaluation value first image quality evaluation value*(1+target image quality deviation value)*(1+target optimization coefficient)
  • the image quality can be objectively evaluated based on the influence of internal and external environmental factors and shooting setting factors, which helps to improve the accuracy of image quality evaluation.
  • the retrieval processing method described in the embodiment of the present application is applied to an electronic device, obtains the input retrieval term, processes the retrieval term, obtains the query expression, collects data according to the retrieval term, and obtains the target data, Update the preset index table according to the target data to obtain the first index table, query the first index table according to the query expression, obtain at least one search result, and use a preset algorithm to determine the relationship between each search result in the at least one search result and the Relevance between search terms, at least one correlation is obtained, and at least one search result is displayed according to the principle of high correlation priority.
  • the data to be searched can be updated, and on the other hand, the search terms can be converted into query expressions
  • FIG. 4 is a schematic flowchart of a retrieval processing method provided by an embodiment of the application, which is applied to an electronic device; as shown in the figure, the retrieval processing method includes:
  • steps 401 to 409 may refer to the corresponding steps of the retrieval processing method described in FIG. 3A , and details are not repeated here.
  • the retrieval processing method described in the embodiments of the present application is applied to electronic devices.
  • the data to be searched can be updated; It is a query expression, and further, it can realize accurate search for search terms, and can display search results according to the relevance, realize intelligent display of search results, and improve user experience.
  • FIG. 5 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • the electronic device includes a processor, a memory, a communication interface, and one or more A program, wherein the above-mentioned one or more programs are stored in the above-mentioned memory and are configured to be executed by the above-mentioned processor.
  • the above-mentioned program includes instructions for executing the following steps:
  • Data collection is performed according to the search terms to obtain target data
  • the first index table is queried according to the query expression to obtain at least one search result.
  • the electronic device described in the embodiments of the present application obtains the input search terms, processes the search terms to obtain a query expression, collects data according to the search terms, obtains target data, and updates presets according to the target data.
  • index table obtain the first index table, query the first index table according to the query expression, and obtain at least one search result, on the one hand, the data to be searched can be updated, on the other hand, the search term can be converted into a query expression, Furthermore, fuzzy search or precise search can be performed according to the search term, which improves user experience.
  • the above program includes instructions for executing the following steps:
  • the target data is obtained by acquiring the push or usage record data of the third-party application according to the search term.
  • the above program includes instructions for executing the following steps:
  • the priority order of the screened historical data is determined, and the screened historical data is queued according to the priority order to obtain the target data.
  • the above program includes instructions for executing the following steps:
  • Syntax analysis is performed on the at least one first term list to obtain the query expression.
  • the above program includes instructions for executing the following steps:
  • the preset index table is updated according to the at least one second term list to obtain the first index table.
  • the above program includes instructions for executing the following steps:
  • the above program includes instructions for executing the following steps:
  • the at least one search result is displayed according to the high-relevance priority display principle.
  • the above program includes instructions for performing the following steps:
  • mapping relationship between the preset algorithm and the search term type determine the target algorithm corresponding to the target search term type
  • the degree of relevancy between each of the at least one search result and the search term is determined to obtain at least one degree of relevancy.
  • the above program includes instructions for executing the following steps:
  • the electronic device includes corresponding hardware structures and/or software modules for executing each function.
  • the present application can be implemented in hardware or a combination of hardware and computer software with the units and algorithm steps of each example described in conjunction with the embodiments provided herein. Whether a function is performed by hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.
  • the electronic device may be divided into functional units according to the foregoing method examples.
  • each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing 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. It should be noted that the division of units in the embodiments of the present application is illustrative, and is only a logical function division, and other division methods may be used in actual implementation.
  • FIG. 6A is a block diagram of functional units of the retrieval processing apparatus 600 involved in the embodiment of the present application.
  • the retrieval processing apparatus 600 is applied to electronic equipment, and the apparatus 600 includes: an acquisition unit 601, a processing unit 602, a collection unit 603, an update unit 604, and a search unit 605, wherein,
  • the obtaining unit 601 is used to obtain the input search term
  • the processing unit 602 is configured to process the search term to obtain a query expression
  • the collecting unit 603 is configured to collect data according to the search term to obtain target data
  • the updating unit 604 is configured to update a preset index table according to the target data to obtain a first index table
  • the searching unit 605 is configured to query the first index table according to the query expression to obtain at least one search result.
  • the retrieval processing device described in the embodiment of the present application is applied to electronic equipment, obtains the input retrieval term, processes the retrieval term, obtains the query expression, collects data according to the retrieval term, and obtains the target data, Update the preset index table according to the target data to obtain the first index table, and query the first index table according to the query expression to obtain at least one search result.
  • the data to be searched can be updated, and on the other hand, the The search terms are converted into query expressions, and further, fuzzy search or precise search of the search terms can be realized, which improves the user experience.
  • the searching unit 603 is specifically configured to:
  • the target data is obtained by acquiring the push or usage record data of the third-party application according to the search term.
  • the searching unit 603 is specifically configured to:
  • the priority order of the screened historical data is determined, and the screened historical data is queued according to the priority order to obtain the target data.
  • the processing unit 602 is specifically configured to:
  • Syntax analysis is performed on the at least one first term list to obtain the query expression.
  • the updating unit 605 is specifically configured to:
  • the preset index table is updated according to the at least one second term list to obtain the first index table.
  • the searching unit 605 is specifically configured to:
  • FIG. 6B is another modified structure of the apparatus shown in FIG. 6A, which may further include: a determination unit 606 and a display unit 607, as follows:
  • the determining unit 606 is configured to adopt a preset algorithm to determine the degree of relevance between each search result in the at least one search result and the search term, and obtain at least one degree of relevance;
  • the display unit 607 is configured to display the at least one search result according to the principle of displaying the at least one search result with high relevancy.
  • the determining unit 606 is specifically configured to:
  • mapping relationship between the preset algorithm and the search term type determine the target algorithm corresponding to the target search term type
  • the degree of relevancy between each of the at least one search result and the search term is determined to obtain at least one degree of relevancy.
  • the acquiring unit 601 is specifically configured to:
  • each “unit” may be, for example, an integrated circuit ASIC, a single circuit for executing one or more software or firmware Program processors (shared, dedicated, or chipset) and memory, combinational logic circuits, and/or other suitable components that provide the functions described above.
  • the acquisition unit 601, the processing unit 602, the collection unit 603, the update unit 604, the search unit 605, the determination unit 606 and the display unit 607 may all be one or more of a control circuit or a processor, based on the above-mentioned unit modules The functions or steps of any of the above methods can be implemented.
  • This embodiment also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the above-mentioned computer program causes a computer to execute the embodiments of the present application, so as to realize any of the methods described above.
  • This embodiment also provides 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 any of the methods 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 any one of the foregoing method embodiments.
  • the electronic device, computer storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding method provided above. Therefore, for the beneficial effects that can be achieved, reference can be made to the corresponding provided above. The beneficial effects in the method will not be 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 May be integrated into another device, or some features may be omitted, 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.

Abstract

本申请公开了一种检索处理方法、装置及存储介质，应用于电子设备，该方法包括：获取输入的检索词；对所述检索词进行处理，得到查询表达式；依据所述检索词进行数据收集，得到目标数据；依据所述目标数据更新预设索引表，得到第一索引表；依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。采用本申请实施例能够实现检索功能，提升了用户体验。

Description

检索处理方法、装置及存储介质 技术领域
本申请涉及信息处理技术领域，尤其涉及一种检索处理方法、装置及存储介质。
背景技术
随着电子产品(如手机、平板电脑等等)的大量普及应用，电子产品能够支持的应用越来越多，功能越来越强大，电子产品向着多样化、个性化的方向发展，电子产品对用户的重要性可想而知，显然电子产品已成为用户生活中不可缺少的电子用品。以手机为例，现有的搜索功能较为单一，且针对多个搜索结果时，无法智能展示。
发明内容
本申请实施例提供一种检索处理方法、装置及存储介质，能够实现检索功能，能够实现检索功能，提升用户体验。
第一方面，本申请实施例提供一种检索处理方法，应用于电子设备，所述方法包括：
获取输入的检索词；
对所述检索词进行处理，得到查询表达式；
依据所述检索词进行数据收集，得到目标数据；
依据所述目标数据更新预设索引表，得到第一索引表；
依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。
第二方面，本申请实施例提供一种检索处理装置，应用于电子设备，所述装置包括：获取单元、处理单元、收集单元、更新单元和搜索单元，其中，
所述获取单元，用于获取输入的检索词；
所述处理单元，用于对所述检索词进行处理，得到查询表达式；
所述收集单元，用于依据所述检索词进行数据收集，得到目标数据；
所述更新单元，用于依据所述目标数据更新预设索引表，得到第一索引表；
所述搜索单元，用于依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。
第三方面，本申请实施例提供一种电子设备，所述电子设备包括处理器、存储器，所述存储器用于存储一个或多个程序，并且被配置由所述处理器执行，所述程序包括用于执行如权利要求第一方面任一项所述的方法中的步骤的指令。
第四方面，本申请实施例提供了一种计算机可读存储介质，其中，上述计算机可读存储介质存储用于电子数据交换的计算机程序，其中，上述计算机程序使得计算机执行如本申请实施例第一方面中所描述的部分或全部步骤。
第五方面，本申请实施例提供了一种计算机程序产品，其中，上述计算机程序产品包括存储了计算机程序的非瞬时性计算机可读存储介质，上述计算机程序可操作来使计算机执行如本申请实施例第一方面中所描述的部分或全部步骤。该计算机程序产品可以为一个软件安装包。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的一种电子设备的结构示意图；
图2是本申请实施例提供的一种电子设备的软件结构示意图；
图3A是本申请实施例提供的一种检索处理方法的流程示意图；
图3B是本申请实施例提供的另一种检索处理方法的流程示意图；
图3C是本申请实施例提供的分词处理过程的演示示意图；
图3D是本申请实施例提供的另一种检索处理方法的流程示意图；
图3E是本申请实施例提供的归并树结构的演示示意图；
图4是本申请实施例提供的另一种检索处理方法的流程示意图；
图5是本申请实施例提供的一种电子设备的结构示意图；
图6A是本申请实施例提供的一种检索处理装置的功能单元组成框图；
图6B是本申请实施例提供的一种检索处理装置的功能单元组成框图。
具体实施方式
下面将结合附图，对本申请实施例中的技术方案进行描述。
为了更好地理解本申请实施例的方案，下面先对本申请实施例可能涉及的相关术语和概念进行介绍。
电子设备可以包括各种超宽带(ultra wide band，UWB)模块的设备，例如，智能手机、车载设备(导航仪、行车记录仪、雷达测距仪、ETC支付装载等等)、可穿戴设备、智能手表、基站设备、标签设备、对讲机、智能眼镜、无线蓝牙耳机、计算设备或连接到无线调制解调器的其他处理设备，以及各种形式的用户设备(User Equipment，UE)，移动台(Mobile Station，MS)，虚拟现实/增强现实设备，终端设备(terminal device)等等。
第一部分，本申请所公开的技术方案的软硬件运行环境介绍如下。
如图所示，图1示出了电子设备100的结构示意图。电子设备100可以包括处理器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、指南针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。
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AP，调制解调处理器，图形处理器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NPU等。其中，不同的处理单元可以是独立的部件，也可以集成在一个或多个处理器中。在一些实施例中，电子设备101也可以包括一个或多个处理器110。其中，控制器可以根据指令操作码和时序信号，产生操作控制信号，完成取指令和执行指令的控制。在其他一些实施例中，处理器110中还可以设置存储器，用于存储指令和数据。示例性地，处理器110中的存储器可以为高速缓冲存储器。该存储器可以保存处理器110刚用过或循环使用的指令或数据。如果处理器110需要再次使用该指令或数据，可从存储器中直接调用。这样就避免了重复存取，减少了处理器110的等待时间，因而提高了电子设备101处理数据或执行指令的效率。
在一些实施例中，处理器110可以包括一个或多个接口。接口可以包括集成电路间(inter-integrated circuit，I2C)接口、集成电路间音频(inter-integrated circuit sound，I2S)接口、脉冲编码调制(pulse code modulation，PCM)接口、通用异步收发传输器(universal asynchronous receiver/transmitter，UART)接口、移动产业处理器接口(mobile industry processor interface，MIPI)、用输入输出(general-purpose input/output，GPIO)接口、SIM卡接口和/或USB接口等。其中，USB接口130是符合USB标准规范的接口，具体可以是Mini USB接口、Micro USB接口、USB Type C接口等。USB接口130可以用于连 接充电器为电子设备101充电，也可以用于电子设备101与外围设备之间传输数据。该USB接口130也可以用于连接耳机，通过耳机播放音频。
可以理解的是，本申请实施例示意的各模块间的接口连接关系，只是示意性说明，并不构成对电子设备100的结构限定。在本申请另一些实施例中，电子设备100也可以采用上述实施例中不同的接口连接方式，或多种接口连接方式的组合。
充电管理模块140用于从充电器接收充电输入。其中，充电器可以是无线充电器，也可以是有线充电器。在一些有线充电的实施例中，充电管理模块140可以通过USB接口130接收有线充电器的充电输入。在一些无线充电的实施例中，充电管理模块140可以通过电子设备100的无线充电线圈接收无线充电输入。充电管理模块140为电池142充电的同时，还可以通过电源管理模块141为电子设备供电。
电源管理模块141用于连接电池142，充电管理模块140与处理器110。电源管理模块141接收电池142和/或充电管理模块140的输入，为处理器110、内部存储器121、外部存储器、显示屏194、摄像头193和无线通信模块160等供电。电源管理模块141还可以用于监测电池容量、电池循环次数、电池健康状态(漏电，阻抗)等参数。在其他一些实施例中，电源管理模块141也可以设置于处理器110中。在另一些实施例中，电源管理模块141和充电管理模块140也可以设置于同一个器件中。
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/6G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(blue tooth，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)、红外技术(infrared，IR)、UWB模块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。
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。
显示屏194用于显示图像、视频等。显示屏194包括显示面板。显示面板可以采用液晶显示屏(liquid crystal display，LCD)、有机发光二极管(organic light-emitting diode，OLED)、有源矩阵有机发光二极体或主动矩阵有机发光二极体(active-matrix organic light emitting diode的，AMOLED)、柔性发光二极管(flex light-emitting diode，FLED)、迷你发光二极管(mini light-emitting diode，miniled)、MicroLed、Micro-oLed、量子点发光二极管(quantum dot light emitting diodes，QLED)等。在一些实施例中，电子设备100可以包括1个或多个显示屏194。
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。
ISP用于处理摄像头193反馈的数据。例如，拍照时，打开快门，光线通过镜头被传递到摄像头感光元件上，光信号转换为电信号，摄像头感光元件将电信号传递给ISP处理，转化为肉眼可见的图像。ISP还可以对图像的噪点、亮度、肤色进行算法优化。ISP还可以对拍摄场景的曝光、色温等参数优化。在一些实施例中，ISP可以设置在摄像头193中。
摄像头193用于捕获静态图像或视频。物体通过镜头生成光学图像投射到感光元件。感光元件可以是电荷耦合器件(charge coupled device，CCD)或互补金属氧化物半导体(complementary metal-oxide-semiconductor，CMOS)光电晶体管。感光元件把光信号转换成电信号，之后将电信号传递给ISP转换成数字图像信号。ISP将数字图像信号输出到DSP加工处理。DSP将数字图像信号转换成标准的RGB，YUV等格式的图像信号。在一些实施例中，电子设备100可以包括1个或多个摄像头193。
数字信号处理器用于处理数字信号，除了可以处理数字图像信号，还可以处理其他数字信号。例如，当电子设备100在频点选择时，数字信号处理器用于对频点能量进行傅里叶变换等。
视频编解码器用于对数字视频压缩或解压缩。电子设备100可以支持一种或多种视频编解码器。这样，电子设备100可以播放或录制多种编码格式的视频，例如：动态图像专家组(moving picture experts group，MPEG)1、MPEG2、MPEG3、MPEG4等。
NPU为神经网络(neural-network，NN)计算处理器，通过借鉴生物神经网络结构，例如借鉴人脑神经元之间传递模式，对输入信息快速处理，还可以不断的自学习。通过NPU可以实现电子设备100的智能认知等应用，例如：图像识别、人脸识别、语音识别、文本理解等。
外部存储器接口120可以用于连接外部存储卡，例如Micro SD卡，实现扩展电子设备100的存储能力。外部存储卡通过外部存储器接口120与处理器110通信，实现数据存储功能。例如将音乐，视频等文件保存在外部存储卡中。
内部存储器121可以用于存储一个或多个计算机程序，该一个或多个计算机程序包括指令。处理器110可以通过运行存储在内部存储器121的上述指令，从而使得电子设备101执行本申请一些实施例中所提供的显示页面元素的方法，以及各种应用以及数据处理等。内部存储器121可以包括存储程序区和存储数据区。其中，存储程序区可存储操作系统；该存储程序区还可以存储一个或多个应用(比如图库、联系人等)等。存储数据区可存储电子设备101使用过程中所创建的数据(比如照片，联系人等)等。此外，内部存储器121可以包括高速随机存取存储器，还可以包括非易失性存储器，例如一个或多个磁盘存储部件，闪存部件，通用闪存存储器(universal flash storage，UFS)等。在一些实施例中，处理器110可以通过运行存储在内部存储器121的指令，和/或存储在设置于处理器110中的存储器的指令，来使得电子设备101执行本申请实施例中所提供的显示页面元素的方法，以及其他应用及数据处理。电子设备100可以通过音频模块170、扬声器170A、受话器170B、麦克风170C、耳机接口170D、以及应用处理器等实现音频功能。例如音乐播放、录音等。
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。
其中，压力传感器180A用于感受压力信号，可以将压力信号转换成电信号。在一些实施例中，压力传感器180A可以设置于显示屏194。压力传感器180A的种类很多，如电阻式压力传感器，电感式压力传感器，电容式压力传感器等。电容式压力传感器可以是包括至少两个具有导电材料的平行板。当有力作用于压力传感器180A，电极之间的电容改变。电子设备100根据电容的变化确定压力的强度。当有触摸操作作用于显示屏194，电子设备100根据压力传感器180A检测触摸操作强度。电子设备100也可以根据压力传感器180A的检测信号计算触摸的位置。在一些实施例中，作用于相同触摸位置，但不同触摸操作强度的触摸操作，可以对应不同的操作指令。例如：当有触摸操作强度小于第一压力阈值的触摸操作作用于短消息应用图标时，执行查看短消息的指令。当有触摸操作强度大于或等于第一压力阈值的触摸操作作用于短消息应用图标时，执行新建短消息的指令。
陀螺仪传感器180B可以用于确定电子设备100的运动姿态。在一些实施例中，可以通过陀螺仪传 感器180B确定电子设备100围绕三个轴(即X、Y和Z轴)的角速度。陀螺仪传感器180B可以用于拍摄防抖。示例性的，当按下快门，陀螺仪传感器180B检测电子设备100抖动的角度，根据角度计算出镜头模组需要补偿的距离，让镜头通过反向运动抵消电子设备100的抖动，实现防抖。陀螺仪传感器180B还可以用于导航，体感游戏场景。
加速度传感器180E可检测电子设备100在各个方向上(一般为三轴)加速度的大小。当电子设备100静止时可检测出重力的大小及方向。还可以用于识别电子设备姿态，应用于横竖屏切换，计步器等应用。
环境光传感器180L用于感知环境光亮度。电子设备100可以根据感知的环境光亮度自适应调节显示屏194亮度。环境光传感器180L也可用于拍照时自动调节白平衡。环境光传感器180L还可以与接近光传感器180G配合，检测电子设备100是否在口袋里，以防误触。
指纹传感器180H用于采集指纹。电子设备100可以利用采集的指纹特性实现指纹解锁，访问应用锁，指纹拍照，指纹接听来电等。
温度传感器180J用于检测温度。在一些实施例中，电子设备100利用温度传感器180J检测的温度，执行温度处理策略。例如，当温度传感器180J上报的温度超过阈值，电子设备100执行降低位于温度传感器180J附近的处理器的性能，以便降低功耗实施热保护。在另一些实施例中，当温度低于另一阈值时，电子设备100对电池142加热，以避免低温导致电子设备100异常关机。在其他一些实施例中，当温度低于又一阈值时，电子设备100对电池142的输出电压执行升压，以避免低温导致的异常关机。
触摸传感器180K，也称“触控面板”。触摸传感器180K可以设置于显示屏194，由触摸传感器180K与显示屏194组成触摸屏，也称“触控屏”。触摸传感器180K用于检测作用于其上或附近的触摸操作。触摸传感器可以将检测到的触摸操作传递给应用处理器，以确定触摸事件类型。可以通过显示屏194提供与触摸操作相关的视觉输出。在另一些实施例中，触摸传感器180K也可以设置于电子设备100的表面，与显示屏194所处的位置不同。
示例性的，图2示出了电子设备100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程序层，应用程序框架层，安卓运行时(Android runtime)和系统库，以及内核层。应用程序层可以包括一系列应用程序包。
如图2所示，应用程序层可以包括相机，图库，日历，通话，地图，导航，WLAN，蓝牙，音乐，视频，短信息等应用程序。
应用程序框架层为应用程序层的应用程序提供应用编程接口(application programming interface，API)和编程框架。应用程序框架层包括一些预先定义的函数。
如图2所示，应用程序框架层可以包括窗口管理器，内容提供器，视图系统，电话管理器，资源管理器，通知管理器等。
窗口管理器用于管理窗口程序。窗口管理器可以获取显示屏大小，判断是否有状态栏，锁定屏幕，截取屏幕等。
内容提供器用来存放和获取数据，并使这些数据可以被应用程序访问。数据可以包括视频，图像，音频，拨打和接听的电话，浏览历史和书签，电话簿等。
视图系统包括可视控件，例如显示文字的控件，显示图片的控件等。视图系统可用于构建应用程序。显示界面可以由一个或多个视图组成的。例如，包括短信通知图标的显示界面，可以包括显示文字的视图以及显示图片的视图。
电话管理器用于提供电子设备100的通信功能。例如通话状态的管理(包括接通，挂断等)。
资源管理器为应用程序提供各种资源，比如本地化字符串，图标，图片，布局文件，视频文件等等。
通知管理器使应用程序可以在状态栏中显示通知信息，可以用于传达告知类型的消息，可以短暂停留后自动消失，无需用户交互。比如通知管理器被用于告知下载完成，消息提醒等。通知管理器还可以是以图表或者滚动条文本形式出现在系统顶部状态栏的通知，例如后台运行的应用程序的通知，还可以 是以对话窗口形式出现在屏幕上的通知。例如在状态栏提示文本信息，发出提示音，电子设备振动，指示灯闪烁等。
Android Runtime包括核心库和虚拟机。Android runtime负责安卓系统的调度和管理。
核心库包含两部分：一部分是java语言需要调用的功能函数，另一部分是安卓的核心库。
应用程序层和应用程序框架层运行在虚拟机中。虚拟机将应用程序层和应用程序框架层的java文件执行为二进制文件。虚拟机用于执行对象生命周期的管理，堆栈管理，线程管理，安全和异常的管理，以及垃圾回收等功能。
系统库可以包括多个功能模块。例如：表面管理器(surface manager)，媒体库(media libraries)，三维图形处理库(例如：OpenGL ES)，2D图形引擎(例如：SGL)等。
表面管理器用于对显示子系统进行管理，并且为多个应用程序提供了2D和3D图层的融合。
媒体库支持多种常用的音频，视频格式回放和录制，以及静态图像文件等。媒体库可以支持多种音视频编码格式，例如：MPEG4，H.264，MP3，AAC，AMR，JPG，PNG等。
三维图形处理库用于实现三维图形绘图，图像渲染，合成，和图层处理等。
2D图形引擎是2D绘图的绘图引擎。
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。
第二部分，本申请实施例所公开的检索处理方法及装置介绍如下。
本申请提供了请参阅图3A，图3A是本申请实施例提供的一种检索处理方法的流程示意图，应用于电子设备，如图所示，本检索处理方法包括：
301、获取输入的检索词。
其中检索词可以由用户自行输入，或者，系统推送。检索词可以为以下至少一种：汉字、英文句子、字符串、德语句子、法语句子、方言句子、日文句子、韩文句子、图像、视频、文档等等，在此不作限定。具体实现中，电子设备可以通过触控显示屏输入检索词。在输入的检索词不为文本内容时，则可以将检索词转化为文本内容，再进行后续检索。
在一个可能地示例中，上述步骤301，获取输入的检索词，可以包括如下步骤：
A31、获取目标语音片段；
A32、对所述目标语音片段进行解析，得到所述检索词。
其中，电子设备可以采集用户输入的目标语音片段，并对目标语音片段转化为文本，对文本进行语义识别，得到检索词。
在一个可能地示例中，上述步骤301，获取输入的检索词，可以包括如下步骤：
B31、获取输入内容；
B32、在输入内容不为文本内容时，将所述输入内容转化为目标文本内容；
B33、对所述目标文本内容进行关键字提取，得到所述检索词。
其中，具体实现中，电子设备可以通过输入电路获取输入内容，输入电路可以为以下至少一种：麦克风、触控显示屏、触控笔、鼠标、键盘等等，在此不作限定。
具体实现中，电子设备可以获取输入内容，在输入内容不为文本内容时，可以通过字符识别、语音识别、图像识别等方式将输入内容转化为目标文本内容，对目标文本内容进行关键字提取，得到检索词，如此，可以便于后续检索。
302、对所述检索词进行处理，得到查询表达式。
其中，电子设备可以对检索词进行词法分析以及语法分析，将其转化为相应的查询表达式，查询表达式可以为后缀表达式(如逆波兰表达式)。
在一个可能地示例中，上述步骤302，对所述检索词进行处理，得到查询表达式，可以包括如下步骤：
21、对所述检索词进行词法分析，得到多个第一术语列表；
22、对所述多个第一术语列表进行语法分析，得到所述查询表达式。
其中，电子设备可以对用户的检索词(query)进行词法分析，即通过词法分析器对检索词进行至少一项处理：归一化、同义词转换、分词、去除停用词，在此不作限定，进而，可以得到分词后的多个第一术语列表(term list)，进而，进行语法分析。首先是分析第一术语列表之间的关系，最终生成一个查询表达式。由于是在电子设备上开发，采用简单的配置方式。不同术语列表(term)之间的关系可以为命中所有、命中一个term即可。换成数据公式即为支持或运算(or、|运算符)和与运算(and、&运算符)，两种运算符优先级相同。
举例说明下：query＝全球票房排行榜，词法分析后为term＝全球、term＝票房、term＝排行榜，配置term之间为与的关系，则解析为查询表达式1&2&3，其中，数字为term标识，例如其中1代表词为全球的term；2代表词为票房的term。
对于此查询表达式而言，其为一个中缀表达式，其更为符合人的思维逻辑，而计算机难于处理，因此，还可以将中缀表达式转换为计算机更容易处理的后缀表达式(逆波兰表达式，结合栈很容易完成算数求和)。例如，查询表达式1&2&3转换为12&3&。
303、依据所述检索词进行数据收集，得到目标数据。
其中，本申请实施例中，电子设备可以依据检索词对本地数据或者第三方应用的推送数据进行收集，得到目标数据，其中，本地数据可以为以下至少一种：本地媒体数据、通讯录数据、第三方应用的使用记录数据。第三方应用可以与电子设备事先约定允许被检索的应用。第三方应用可以为以下至少一种：游戏应用、视频应用、音频应用、即时通讯应用、购物应用、天气应用、支付应用等等，在此不作限定。
举例说明下，以手机为例，具体实现中，可以对于手机上媒体数据、通信录、应用数据，在第一次启动搜索引擎时会全量获取一遍对应模块中的数据，并将数据存储在的搜索引擎装置中，另一方面用户的数据是存在更新变化的，因此，可以注册一个监听器在上述模块上，当用户的数据发生变化时数据收集模块能够得到及时的通知并进行响应处理。
其中，上述步骤302、步骤303可以同步执行，也可以异步执行，在同步执行时，步骤302、步骤303可以分别采用一个进程或者线程执行。
在一个可能地示例中，上述步骤303，依据所述检索词进行数据收集，得到目标数据，可以按照如下方式实施：
依据所述检索词获取本地媒体数据，得到所述目标数据；
和/或，
依据所述检索词获取本地通讯录数据，得到所述目标数据；
和/或，
依据所述检索词获取第三方应用的推送或者使用记录数据，得到所述目标数据。
其中，电子设备依据检索词获取预设时间段的本地媒体数据，即可以得到与检索词相关的目标数据。本地媒体数据可以为以下至少一种：图像、音频、视频、文件(word文本、PDF文本、PPT等等)，在此不作限定，预设时间段可以由用户自行设置或者系统默认；和/或，电子设备也可以依据检索词获取本地通讯录数据，得到目标数据；和/或，电子设备可以依据检索词获取第三方应用的推送或者使用记录数据，得到目标数据，即本申请实施例中，对于第三方应用来说，电子设备可以提供开放的API，第三方应用在完成鉴权后，可以通过相应的API接口推送一条一条数据给电子设备进行数据处理，其数据的更新动作可以标记为增加、删除、更新。
在一个可能地示例中，上述步骤303，依据所述检索词进行数据收集，得到目标数据，可以包括如下步骤：
31、获取预设时间段的历史数据；
32、依据所述检索词对所述历史数据进行筛选，得到筛选后的所述历史数据；
33、确定筛选后的所述历史数据的优先级顺序，依据该优先级顺序对筛选后的所述历史数据进行队列处理，得到所述目标数据。
其中，预设时间段可以由用户自行设置或者系统默认。
具体实现中，电子设备可以获取预设时间段的历史数据，依据检索词对历史数据进行筛选，得到筛选后的历史数据，其目的在于，尽量筛选出与检索词关联程度高的数据，进而，确定筛选后的历史数据的优先级顺序，依据该优先级顺序对所述筛选后的历史数据进行队列处理，得到目标数据，优先级顺序可以为关联度高低顺序，或者，也可以由数据的生成时间确定优先级顺序。如此，过优先级队列的方式，对不同数据的响应也会不同，在面对需要及时更新的数据可以采用高优先级队列进行处理，完成数据的及时更新，有助于提升后续数据检索效率。
304、依据所述目标数据更新预设索引表，得到第一索引表。
其中，预设索引表可以预先保存在数据库(database，DB)中，预设索引表可以为倒排表，该倒排表中可以预先存储以下至少一项信息：术语列表名称、术语列表对应的文档数量、文档标识、文档大小、文档使用频率等等，在此不做限定。
在一个可能地示例中，上述步骤304，依据所述目标数据更新预设索引表，得到第一索引表，可以包括如下步骤：
41、获取所述预设索引表对应的参考数据；
42、依据所述目标数据与所述参考数据进行对比，得到待更新数据；
43、依据所述待更新数据进行词法分析，得到至少一个第二术语列表；
44、依据所述至少一个第二术语列表更新所述预设索引表，得到所述第一索引表。
其中，预设索引表中的节点存储数据对应的标识，依据这些标识可以获取预设索引表对应的参考数据，进而，可以将目标数据与参考数据进行比对，得到目标数据中不存在于参考数据中的待更新数据，进而，可以对待更新数据进行词法分析，具体地，通过词法分析器对待更新数据进行至少一项处理：归一化、同义词转换、分词、去除停用词，在此不作限定，得到至少一个第二术语列表，依据至少一个第二术语列表更新预设索引表，即将更新数据的索引拼接在预设索引表中，进而，可以得到第一索引表。
305、依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。
其中，第一索引表可以为一个倒排表，查询表达式可以处理为树结构，如二叉树，进而，电子设备可以依据二叉树对第一索引表进行查询，得到至少一个搜索结果。进而，能够实现模糊搜索或者精准搜索，具体地，依据检索词的精准度或者索引表的更新程度实现，例如，检索词为模糊词语时，则可以实现模糊搜索，又例如，检索词为精准词语时，则可以实现精准搜索，又例如，索引表更新不及时或者更新数据少，则可以实现模糊搜索，又例如，索引表更新及时或者更新数据充足，则可以实现精准搜索。
在一个可能地示例中，上述步骤305，依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果，可以包括如下步骤：
51、将所述查询表达式生成归并树结构；
52、依据所述归并树结构获取所述第一索引表中每一节点对应的倒排拉链数据，并基于所述倒排拉链数据进行查询，得到所述至少一个搜索结果。
其中，由于第一索引表预先保存在数据库中，其为一个倒排表。电子设备可以基于查询表达式生成归并树结构，倒排表中可以预先存储以下至少一项信息：术语列表名称、术语列表对应的文档数量、文档标识、文档大小、文档使用频率等等，在此不做限定。进而，电子设备可以依据归并树结构获取第一索引表中每一节点对应的倒排拉链数据，并基于倒排拉链数据进行查询，得到至少一个搜索结果。
在一个可能的示例中，在上述步骤305之后，还可以包括如下步骤306-步骤307，具体如下：
306、采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度。
其中，预设算法可以由用户自行设置或者系统默认，预设算法可以为至少一个算法，预设算法可以为以下至少一种：术语频率-反向文档频率(term frequency–inverse document frequency，TF/IDF)、石榴算法，绿萝算法，绿萝算法，飓风算法、原创星火计划、白杨算法、轻舟算法，惊雷算法、天网算法、烽火算法、细雨算法、石榴算法、极光算法、闪电算法、蓝天算法、冰桶算法、熊猫算法、企鹅算法等 等，在此不作限定。具体实现中，电子设备可以采用预设算法，确定至少一个搜索结果中的每一搜索结果与检索词之间的相关度，得到至少一个相关度。
在一个可能地示例中，在所述预设算法为多个算法时，上述步骤306，采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度，可以包括如下步骤：
61、确定所述检索词对应的目标检索词类型；
62、按照预设的算法与检索词类型之间的映射关系，确定所述目标检索词类型对应的目标算法；
63、依据所述目标算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度。
其中，本申请实施例中，例如，可以依据检索词的格式确定检索词类型、检索词类型可以为以下至少一种：音频类型、视频类型、图像类型、文本类型等等，在此不作限定，又例如，还可以依据检索词的数量确定检索词类型，又例如，还可以依据检索词的复杂度确定检索词类型，又例如，还可以依据检索词的热门程度确定检索词类型，检索词类型可以为以下至少一种：热词、低频词、一般热度词等等，在此不作限定。
具体实现中，在预设算法为多个算法时，则不同的算法针对不同的检索词，其检索效率以及检索精度不一样，进而，电子设备中可以预先存储预设的算法与检索词类型之间的映射关系，进而，在电子设备确定检索词对应的目标检索词类型之后，依据该预设的算法与检索词类型之间的映射关系，确定目标检索词类型对应的目标算法，进而，依据目标算法，确定至少一个搜索结果中的每一搜索结果与检索词之间的相关度，得到至少一个相关度，进而，有助于确定搜索结果的相关度。
307、按照相关度高优先展示原则展示所述至少一个搜索结果。
其中，电子设备可以按照相关度高优先展示原则展示至少一个搜索结果，则可以优先展示相关度高的搜索结果，相关度低的搜索结果则可以隐藏或者在相关度高的搜索结果展示完成之后再展示。
基于上述检索处理方法，以手机为例，其是在手机上进行全文检索的一种全新探索，可以用来满足日益增长的用户数据文档与用户快速精准定位之间的矛盾需求，而在这样的终端搜索引擎下，可以满足用户在目前竞品中无法做到内容检索、模糊检索、根据检索词与文档相关度进行展现的痛点，在设计中，考虑了手机上的开发稳定性要求，因此，开创性的使用了DB作为倒排存储，同时，利用DB的索引来达到快速定位到某个特定倒排拉链，因此，在用户大规模数据下检索也能够快速得到响应，在数据收集方面，通过优先级队列的方式，对不同数据的响应也会不同，在面对需要及时更新的数据可以采用高优先级队列进行处理，完成数据的及时更新。
举例说明下，如图3B所示，以手机为例搜索引擎分为两个数据流向，其中一条数据流向为对用户手机上数据的处理流，如图上椭圆标识部分，可以将媒体数据、通信录数据、应用数据或者合作的第三方应用数据根据定制化的配置解析后，对数据进行处理后存储到搜索系统中去，另一条数据流向为方形标识部分，是用户输入的检索词进入搜索系统后的处理过程，最终返回给用户的是与检索词匹配的文档、应用、音频、视频等数据。
其中，数据处理流程是对用户数据的收集、入库过程。以手机为例上的开发对软件的可靠性、稳定性有非常高的要求，无法做到服务端的及时修复。稳定性的要求导致不适合将一些复杂逻辑放到以手机为例上，但是搜索引擎又是一个非常复杂的工程，这就需要以更优的方式进行实现，为了满足稳定性需求，可以采用轻量级DB来存储倒排表。倒排表中存储术语队列(term)名称、对应的文档数量、文档id的列表等关键信息。
数据处理流程的第一步是需要对数据进行收集，主要有两类数据可以接入到搜索系统中，一类是用户在以手机为例上已授权访问的数据，一类是合作的第三方应用推送的数据，从外部推送过来的用户数据。
具体实现中，对于手机上媒体数据、通信录、应用数据，可以在第一次启动搜索引擎时全量获取一遍对应模块中的数据，并将数据存储在的搜索引擎装置中，另一方面用户的数据是存在更新变化的，因 此注册一个监听器在这些模块上，当用户的数据发生变化时数据收集模块能够得到及时的通知并进行响应处理。
对于合作的第三方应用来说，提供了开放API。第三方应用在完成鉴权后，可以通过这个API推送一条一条数据给数据收集模块进行数据处理，其数据的更新动作需要标记为增加、删除、更新。
在处理这些数据过程中存在队列排队的问题，由于用户的数据量可能会非常大，因此提出对了一条时效性通道，针对不同类型的数据分配不同的优先级，优先级高的数据会得到优先处理。
在完成数据收集的动作之后，针对每条数据都需要通过索引引擎的处理完成对索引的更新，在此过程中会调用词法分析器对数据进行归一化、同义词转换、分词、去除停用词，最终形成一个term列表，并保留term的词频、在文档中出现的位置信息等，然后更新到倒排表存储中，完成对数据的更新，如图3C所示，其为词法分析器处理流程中的样例数据处理过程，具体地，例如，检索词为“全球電影的排行榜”，对其进行繁体字、大小写进行归一化，得到“全球电影的排行榜”，接着，进行切词处理，得到“全球电影的排行榜”，最后进行去除停用词，得到“全球电影排行榜”。
进一步地，如图3D所示，其为另一条数据流向即为用户的检索词处理过程，处理的输入为用户的检索词，输出为搜索系统中记录的所有匹配到的数据结果集合，其可以包括如下步骤1-6：
1、首先对用户的query进行词法分析，此过程可以与数据处理流程中词法分析器基本一致，需要获取的是分词后的一个term列表。
2、进行语法分析。首先是分析term列表之间的关系，最终生成一个查询表达式。由于是在以手机为例上开发，采用简单的配置方式。不同term之间的关系可以为命中所有、命中一个term即可。换成数据公式即为支持或运算(or、|运算符)和与运算(and、&运算符)，两种运算符优先级相同。例如：query＝全球票房排行榜，词法分析后为term＝全球、term＝票房term＝排行榜，配置term之间为与的关系，则解析为查询表达式1&2&3，其中数字为term标识，例如其中1代表词为全球的term；2代表词为票房的term。其中，对于此查询表达式而言，这是一个中缀表达式，其更为符合人的思维逻辑，而计算机难于处理，因此需要将中缀表达式转换为计算机更容易处理的后缀表达式(逆波兰表达式，结合栈很容易完成算数求和)。例如查询表达式1&2&3转换为12&3&。
3、归并引擎处理，将语法分析后的结构后缀表达式生成归并树结构。将查询表达式转换为二叉树结构进行存储，方便后续的归并操作。二叉树的节点包括操作符节点、term节点，其中term节点为叶子节点，记录term对应的id以及term的一些关键信息；操作符节点有左右子节点，是对左右子节点进行操作的算术节点。需要进行查询索引引擎，获取每个term节点对应的倒排拉链数据。索引引擎中存储着当前系统中已入库的所有索引信息，存储一条条的倒排拉链信息，根据term的名称对db的倒排表进行查询获取对应的倒排数据。在db中提前对term字段建立索引，利用db的B+树的索引机制可以在很短的时间内查询到对应的倒排拉链，其时间复杂度只有O(log2N)，即使面对百万级的term数量也可以在极短的时间内可以做到加载对应倒排到内存中。
4、通过对归并树的操作，完成算术运算，获取归并的最终结果拉链。此过程中自底向上的逐个完成操作符节点的运算，最终完成根节点的归并计算。
其中求或(|)计算，即为求两条拉链之间的并集，而与(&)计算是求两条拉链的交集，如图3E所示。在求并、交集过程中，需要记录每篇文档命中的term集合，作为下一步骤中相关性计算的输入的一部分。
5、是按照TF/IDF算法，对最终的拉链结果中每篇文档与检索词之间的相关度进行打分。其中TF/IDF为业界常用的评价相关性的算法，其核心思想是文档中包含某个term越多，则认为此文档与该term之间相关度越高，此为文档词频(term frequency)，如果所有文档中出现某个term的频次约高，则认为该term越不重要，此为逆文档词频(inverse term frequency)，根据这一核心思想对检索词与命中文档之间的相关度进行打分，获取相关性分数。
6、按照相关度打分的结果进行排序，将分数约高的文档排在前面的方式展现给用户。
在一个可能的示例中，步骤301，获取输入的检索词之前，还可以包括如下步骤：
C1、获取用户的目标身份信息；
C2、对所述目标身份信息进行验证；
C3、在所述目标身份信息被验证通过时，执行所述获取输入的检索词的步骤。
其中，本申请实施例中，目标身份信息可以为以下至少一种：字符串、触控参数、人脸图像、指纹图像、掌纹图像、静脉图像、脑电波、声纹等等，在此不做限定。
具体实现中，电子设备可以获取用户的目标身份信息，可以对该目标身份信息进行验证，在目标身份信息被验证通过时，执行步骤301，否则，不执行后续步骤。
进一步地，在所述目标身份信息为目标人脸图像时，在步骤C2-步骤C3之间，还可以包括如下步骤：
C4、确定所述目标人脸图像的目标图像质量评价值；
C5、在所述目标图像质量评价值大于预设图像质量评价值时，将所述目标人脸图像与预设人脸模板进行匹配，得到目标匹配值；
C6、在所述目标匹配值大于预设匹配阈值时，确认所述目标身份信息被验证通过。
其中，预设人脸模板可以预先保存在电子设备中，预设图像质量评价值、预设匹配阈值可以由用户自行设置或者系统默认。具体实现中，电子设备可以采用至少一个图像质量评价指标对目标人脸图像进行图像质量评价，得到目标图像质量评价值，图像质量评价指标可以为以下至少一种：信息熵、平均梯度、平均灰度、对比度等等，在此不做限定。在目标图像质量评价值大于预设图像质量评价值时，可以执行将目标人脸图像与预设人脸模板进行匹配，得到目标匹配值，否则，则可以要求重新进行身份认证。
进一步地，上述步骤C4，确定所述目标人脸图像的目标图像质量评价值，可以包括如下步骤：
C41、确定所述目标人脸图像的目标特征点分布密度和目标信噪比；
C42、按照预设的特征点分布密度与图像质量评价值之间的映射关系，确定所述目标特征点分布密度对应的第一图像质量评价值；
C43、按照预设的信噪比与图像质量偏差值之间的映射关系，确定所述目标信噪比对应的目标图像质量偏差值；
C44、获取所述目标人脸图像的第一拍摄参数；
C45、按照预设的拍摄参数与优化系数之间的映射关系，确定所述第一拍摄参数对应的目标优化系数；
C46、依据所述目标优化系数、所述目标图像质量偏差值对所述第一图像质量评价值进行调整，得到所述目标图像质量评价值。
具体实现中，电子设备中的存储器可以预先存储预设的特征点分布密度与图像质量评价值之间的映射关系、预设的信噪比与图像质量偏差值之间的映射关系、以及预设的拍摄参数与优化系数之间的映射关系，其中，图像质量评价值的取值范围可以为0～1，或者，也可以为0～100。图像质量偏差值可以为正实数，例如，0～1，或者，也可以大于1。优化系数的取值范围可以为-1～1之间，例如，优化系数可以为-0.1～0.1。本申请实施例中，拍摄参数可以为以下至少一种：曝光时长、拍摄模式、感光度ISO、白平衡参数、焦距、焦点、感兴趣区域等等，在此不做限定。
具体实现中，电子设备可以确定目标人脸图像的目标特征点分布密度和目标信噪比，且按照预设的特征点分布密度与图像质量评价值之间的映射关系，确定目标特征点分布密度对应的第一图像质量评价值，特征点分布密度在一定程度上反映了图像质量，特征点分布密度可以理解为目标人脸图像的特征点总数与该目标人脸图像的图像面积之间的比值。进而，电子设备可以按照预设的信噪比与图像质量偏差值之间的映射关系，确定目标信噪比对应的目标图像质量偏差值，由于在生成图像的时候，由于外部(天气、光线、角度、抖动等)或者内部(系统、GPU)原因，产生一些噪声，这些噪声对图像质量会带来一些影响，因此，可以对图像质量进行一定程度调节，以保证对图像质量进行客观评价。
进一步地，电子设备还可以获取目标人脸图像的第一拍摄参数，该第一拍摄参数也可以被携带在通信连接请求中，进而，按照预设的拍摄参数与优化系数之间的映射关系，确定第一拍摄参数对应的目标优化系数，拍摄的参数设置也可能对图像质量评价带来一定的影响，因此，需要确定拍摄参数对图像质 量的影响成分，最后，依据目标优化系数、目标图像质量偏差值对第一图像质量评价值进行调整，得到目标图像质量评价值，其中，目标图像质量评价值可以按照如下公式得到：
在图像质量评价值为百分制的情况下，具体计算公式如下：
目标图像质量评价值＝(第一图像质量评价值+目标图像质量偏差值)*(1+目标优化系数)
在图像质量评价值为百分比的情况下，具体计算公式如下：
目标图像质量评价值＝第一图像质量评价值*(1+目标图像质量偏差值)*(1+目标优化系数)
如此，可以结合内部、外部环境因素以及拍摄设置因素等影响，对图像质量进行客观评价，有助于提升图像质量评价精准度。
可以看出，在本申请实施例中所描述的检索处理方法，应用于电子设备，获取输入的检索词，对检索词进行处理，得到查询表达式，依据检索词进行数据收集，得到目标数据，依据目标数据更新预设索引表，得到第一索引表，依据查询表达式对第一索引表进行查询，得到至少一个搜索结果，采用预设算法，确定至少一个搜索结果中的每一搜索结果与检索词之间的相关度，得到至少一个相关度，按照相关度高优先展示原则展示至少一个搜索结果，如此，一方面，能够更新待搜索数据，另一方面，能够将检索词转化为查询表达式，进而，能够实现对检索词精准搜索，且可以依据相关度展示搜索结果，实现智能化展示搜索结果，提升了用户体验。
本申请提供了请参阅图4，图4是本申请实施例提供的一种检索处理方法的流程示意图，应用于电子设备；如图所示，本检索处理方法包括：
401、获取输入内容。
402、在输入内容不为文本内容时，将所述输入内容转化为目标文本内容。
403、对所述目标文本内容进行关键字提取，得到检索词。
404、对所述检索词进行处理，得到查询表达式。
405、依据所述检索词进行数据收集，得到目标数据。
406、依据所述目标数据更新预设索引表，得到第一索引表。
407、依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。
408、采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度。
409、按照相关度高优先展示原则展示所述至少一个搜索结果。
其中，上述步骤401-步骤409的具体描述可以参照图3A所描述的检索处理方法的相应步骤，在此不再赘述。
可以看出，在本申请实施例中所描述的检索处理方法，应用于电子设备，一方面，能够更新待搜索数据，另一方面，能够通过输入内容，提取检索词，并将该检索词转化为查询表达式，进而，能够实现对检索词精准搜索，且可以依据相关度展示搜索结果，实现智能化展示搜索结果，提升了用户体验。
与上述实施例一致地，请参阅图5，图5是本申请实施例提供的一种电子设备的结构示意图，如图所示，该电子设备包括处理器、存储器、通信接口以及一个或多个程序，其中，上述一个或多个程序被存储在上述存储器中，并且被配置由上述处理器执行，本申请实施例中，上述程序包括用于执行以下步骤的指令：
获取输入的检索词；
对所述检索词进行处理，得到查询表达式；
依据所述检索词进行数据收集，得到目标数据；
依据所述目标数据更新预设索引表，得到第一索引表；
依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。可以看出，在本申请实施例中所描述的电子设备，获取输入的检索词，对检索词进行处理，得到查询表达式，依据检索词进行 数据收集，得到目标数据，依据目标数据更新预设索引表，得到第一索引表，依据查询表达式对第一索引表进行查询，得到至少一个搜索结果，一方面，能够更新待搜索数据，另一方面，能够将检索词转化为查询表达式，进而，能够实现依据检索词进行模糊搜索或者精准搜索，提升了用户体验。
在一个可能地示例中，在所述依据所述检索词进行数据收集，得到目标数据方面，上述程序包括用于执行以下步骤的指令：
依据所述检索词获取本地媒体数据，得到所述目标数据；
和/或，
依据所述检索词获取本地通讯录数据，得到所述目标数据；
和/或，
依据所述检索词获取第三方应用的推送或者使用记录数据，得到所述目标数据。
在一个可能地示例中，在所述依据所述检索词进行数据收集，得到目标数据方面，上述程序包括用于执行以下步骤的指令：
获取预设时间段的历史数据；
依据所述检索词对所述历史数据进行筛选，得到筛选后的所述历史数据；
确定筛选后的所述历史数据的优先级顺序，依据该优先级顺序对筛选后的所述历史数据进行队列处理，得到所述目标数据。
在一个可能地示例中，在所述对所述检索词进行处理，得到查询表达式方面，上述程序包括用于执行以下步骤的指令：
对所述检索词进行词法分析，得到至少一个第一术语列表；
对所述至少一个第一术语列表进行语法分析，得到所述查询表达式。
在一个可能地示例中，在所述依据所述目标数据更新预设索引表，得到第一索引表方面，上述程序包括用于执行以下步骤的指令：
获取所述预设索引表对应的参考数据；
依据所述目标数据与所述参考数据进行对比，得到待更新数据；
依据所述待更新数据进行词法分析，得到至少一个第二术语列表；
依据所述至少一个第二术语列表更新所述预设索引表，得到所述第一索引表。
在一个可能地示例中，在所述依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果方面，上述程序包括用于执行以下步骤的指令：
将所述查询表达式生成归并树结构；
依据所述归并树结构获取所述第一索引表中每一节点对应的倒排拉链数据，并基于所述倒排拉链数据进行查询，得到所述至少一个搜索结果。
在一个可能地示例中，在所述依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果之后，上述程序包括用于执行以下步骤的指令：
采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度；
按照相关度高优先展示原则展示所述至少一个搜索结果。
在一个可能地示例中，在所述预设算法为多个算法时，在所述采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度方面，上述程序包括用于执行以下步骤的指令：
确定所述检索词对应的目标检索词类型；
按照预设的算法与检索词类型之间的映射关系，确定所述目标检索词类型对应的目标算法；
依据所述目标算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度。
在一个可能地示例中，在所述获取输入的检索词方面，上述程序包括用于执行以下步骤的指令：
获取输入内容；
在输入内容不为文本内容时，将所述输入内容转化为目标文本内容；
对所述目标文本内容进行关键字提取，得到所述检索词。
上述主要从方法侧执行过程的角度对本申请实施例的方案进行了介绍。可以理解的是，电子设备为了实现上述功能，其包含了执行各个功能相应的硬件结构和/或软件模块。本领域技术人员应该很容易意识到，结合本文中所提供的实施例描述的各示例的单元及算法步骤，本申请能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
本申请实施例可以根据上述方法示例对电子设备进行功能单元的划分，例如，可以对应各个功能划分各个功能单元，也可以将两个或两个以上的功能集成在一个处理单元中。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。需要说明的是，本申请实施例中对单元的划分是示意性的，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。
图6A是本申请实施例中所涉及的检索处理装置600的功能单元组成框图。该检索处理装置600应用于电子设备，所述装置600包括：获取单元601、处理单元602、收集单元603、更新单元604和搜索单元605，其中，
所述获取单元601，用于获取输入的检索词；
所述处理单元602，用于对所述检索词进行处理，得到查询表达式；
所述收集单元603，用于依据所述检索词进行数据收集，得到目标数据；
所述更新单元604，用于依据所述目标数据更新预设索引表，得到第一索引表；
所述搜索单元605，用于依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。
可以看出，在本申请实施例中所描述的检索处理装置，应用于电子设备，获取输入的检索词，对检索词进行处理，得到查询表达式，依据检索词进行数据收集，得到目标数据，依据目标数据更新预设索引表，得到第一索引表，依据查询表达式对第一索引表进行查询，得到至少一个搜索结果，如此，一方面，能够更新待搜索数据，另一方面，能够将检索词转化为查询表达式，进而，能够实现对检索词模糊搜索或者精准搜索，提升了用户体验。
在一个可能地示例中，在所述依据所述检索词进行数据收集，得到目标数据方面，所述搜索单元603具体用于：
依据所述检索词获取本地媒体数据，得到所述目标数据；
和/或，
依据所述检索词获取本地通讯录数据，得到所述目标数据；
和/或，
依据所述检索词获取第三方应用的推送或者使用记录数据，得到所述目标数据。
在一个可能地示例中，在所述依据所述检索词进行数据收集，得到目标数据方面，所述搜索单元603具体用于：
获取预设时间段的历史数据；
依据所述检索词对所述历史数据进行筛选，得到筛选后的所述历史数据；
确定筛选后的所述历史数据的优先级顺序，依据该优先级顺序对筛选后的所述历史数据进行队列处理，得到所述目标数据。
在一个可能地示例中，在所述对所述检索词进行处理，得到查询表达式方面，所述处理单元602具体用于：
对所述检索词进行词法分析，得到至少一个第一术语列表；
对所述至少一个第一术语列表进行语法分析，得到所述查询表达式。
在一个可能地示例中，在所述依据所述目标数据更新预设索引表，得到第一索引表方面，所述更新单元605具体用于：
获取所述预设索引表对应的参考数据；
依据所述目标数据与所述参考数据进行对比，得到待更新数据；
依据所述待更新数据进行词法分析，得到至少一个第二术语列表；
依据所述至少一个第二术语列表更新所述预设索引表，得到所述第一索引表。
在一个可能地示例中，在所述依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果方面，所述搜索单元605具体用于：
将所述查询表达式生成归并树结构；
依据所述归并树结构获取所述第一索引表中每一节点对应的倒排拉链数据，并基于所述倒排拉链数据进行查询，得到所述至少一个搜索结果。
在一个可能地示例中，如图6B，图6B为图6A所示的装置又一变型结构，其还可以包括：确定单元606和展示单元607，具体如下：
所述确定单元606，用于采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度；
所述展示单元607，用于按照相关度高优先展示原则展示所述至少一个搜索结果。
进一步地，在一个可能地示例中，在所述预设算法为多个算法时，在所述采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度方面，所述确定单元606具体用于：
确定所述检索词对应的目标检索词类型；
按照预设的算法与检索词类型之间的映射关系，确定所述目标检索词类型对应的目标算法；
依据所述目标算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度。
在一个可能地示例中，在所述获取输入的检索词方面，所述获取单元601具体用于：
获取输入内容；
在输入内容不为文本内容时，将所述输入内容转化为目标文本内容；
对所述目标文本内容进行关键字提取，得到所述检索词。
需要注意的是，本申请实施例所描述的标签设备是以功能单元的形式呈现。这里所使用的术语“单元”应当理解为尽可能最宽的含义，用于实现各个“单元”所描述功能的对象例如可以是集成电路ASIC，单个电路，用于执行一个或多个软件或固件程序的处理器(共享的、专用的或芯片组)和存储器，组合逻辑电路，和/或提供实现上述功能的其他合适的组件。
其中，获取单元601、处理单元602、收集单元603、更新单元604、搜索单元605、确定单元606和展示单元607均可以为可以是控制电路或处理器中的一个或者多个，基于上述单元模块能够实现上述任一方法的功能或者步骤。
本实施例还提供了一种计算机可读存储介质，其中，该计算机可读存储介质存储用于电子数据交换的计算机程序，其中，上述计算机程序使得计算机执行如本申请实施例，以用于实现上述实施例中的任一方法。
本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任一方法。
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任一方法。
其中，本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，可以通过其它的方式实现。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，或一些特征可以忽略，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，机械或其它的形式。
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 (20)

  1. 一种检索处理方法，其特征在于，应用于电子设备，所述方法包括：
    获取输入的检索词；
    对所述检索词进行处理，得到查询表达式；
    依据所述检索词进行数据收集，得到目标数据；
    依据所述目标数据更新预设索引表，得到第一索引表；
    依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。
  2. 根据权利要求1所述的方法，其特征在于，所述依据所述检索词进行数据收集，得到目标数据，包括：
    依据所述检索词获取本地媒体数据，得到所述目标数据；
    和/或，
    依据所述检索词获取本地通讯录数据，得到所述目标数据；
    和/或，
    依据所述检索词获取第三方应用的推送或者使用记录数据，得到所述目标数据。
  3. 根据权利要求1所述的方法，其特征在于，所述依据所述检索词进行数据收集，得到目标数据，包括：
    获取预设时间段的历史数据；
    依据所述检索词对所述历史数据进行筛选，得到筛选后的所述历史数据；
    确定筛选后的所述历史数据的优先级顺序，依据该优先级顺序对筛选后的所述历史数据进行队列处理，得到所述目标数据。
  4. 根据权利要求1-3任一项所述的方法，其特征在于，所述对所述检索词进行处理，得到查询表达式，包括：
    对所述检索词进行词法分析，得到至少一个第一术语列表；
    对所述至少一个第一术语列表进行语法分析，得到所述查询表达式。
  5. 根据权利要求1-4任一项所述的方法，其特征在于，所述依据所述目标数据更新预设索引表，得到第一索引表，包括：
    获取所述预设索引表对应的参考数据；
    依据所述目标数据与所述参考数据进行对比，得到待更新数据；
    依据所述待更新数据进行词法分析，得到至少一个第二术语列表；
    依据所述至少一个第二术语列表更新所述预设索引表，得到所述第一索引表。
  6. 根据权利要求1-5任一项所述的方法，其特征在于，所述依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果，包括：
    将所述查询表达式生成归并树结构；
    依据所述归并树结构获取所述第一索引表中每一节点对应的倒排拉链数据，并基于所述倒排拉链数据进行查询，得到所述至少一个搜索结果。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，在所述依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果之后，所述方法还包括：
    采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度；
    按照相关度高优先展示原则展示所述至少一个搜索结果。
  8. 根据权利要求7所述的方法，其特征在于，在所述预设算法为多个算法时，所述采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度，包括：
    确定所述检索词对应的目标检索词类型；
    按照预设的算法与检索词类型之间的映射关系，确定所述目标检索词类型对应的目标算法；
    依据所述目标算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度。
  9. 根据权利要求1-8任一项所述的方法，其特征在于，所述获取输入的检索词，包括：
    获取输入内容；
    在输入内容不为文本内容时，将所述输入内容转化为目标文本内容；
    对所述目标文本内容进行关键字提取，得到所述检索词。
  10. 一种电子设备，其特征在于，所述电子设备包括处理器、存储器、通信接口，以及一个或多个程序，所述一个或多个程序被存储在所述存储器中，并且被配置由所述处理器执行，所述程序包括用于执行以下方法中的步骤的指令：
    获取输入的检索词；
    对所述检索词进行处理，得到查询表达式；
    依据所述检索词进行数据收集，得到目标数据；
    依据所述目标数据更新预设索引表，得到第一索引表；
    依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果。
  11. 根据权利要求10所述的电子设备，其特征在于，在所述依据所述检索词进行数据收集，得到目标数据方面，所述程序包括用于执行以下方法中的步骤的指令：
    依据所述检索词获取本地媒体数据，得到所述目标数据；
    和/或，
    依据所述检索词获取本地通讯录数据，得到所述目标数据；
    和/或，
    依据所述检索词获取第三方应用的推送或者使用记录数据，得到所述目标数据。
  12. 根据权利要求10所述的电子设备，其特征在于，在所述依据所述检索词进行数据收集，得到目标数据方面，所述程序包括用于执行以下方法中的步骤的指令：
    获取预设时间段的历史数据；
    依据所述检索词对所述历史数据进行筛选，得到筛选后的所述历史数据；
    确定筛选后的所述历史数据的优先级顺序，依据该优先级顺序对筛选后的所述历史数据进行队列处理，得到所述目标数据。
  13. 根据权利要求10-12任一项所述的电子设备，其特征在于，在所述对所述检索词进行处理，得到查询表达式方面，所述程序包括用于执行以下方法中的步骤的指令：
    对所述检索词进行词法分析，得到至少一个第一术语列表；
    对所述至少一个第一术语列表进行语法分析，得到所述查询表达式。
  14. 根据权利要求10-13任一项所述的电子设备，其特征在于，在所述依据所述目标数据更新预设索引表，得到第一索引表方面，所述程序包括用于执行以下方法中的步骤的指令：
    获取所述预设索引表对应的参考数据；
    依据所述目标数据与所述参考数据进行对比，得到待更新数据；
    依据所述待更新数据进行词法分析，得到至少一个第二术语列表；
    依据所述至少一个第二术语列表更新所述预设索引表，得到所述第一索引表。
  15. 根据权利要求10-14任一项所述的电子设备，其特征在于，在所述依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果方面，所述程序包括用于执行以下方法中的步骤的指令：
    将所述查询表达式生成归并树结构；
    依据所述归并树结构获取所述第一索引表中每一节点对应的倒排拉链数据，并基于所述倒排拉链数据进行查询，得到所述至少一个搜索结果。
  16. 根据权利要求10-15任一项所述的电子设备，其特征在于，在所述依据所述查询表达式对所述第一索引表进行查询，得到至少一个搜索结果之后，所述程序还包括用于执行以下方法中的步骤的指令：
    采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度；
    按照相关度高优先展示原则展示所述至少一个搜索结果。
  17. 根据权利要求16所述的电子设备，其特征在于，在所述预设算法为多个算法时，所述采用预设算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度，所述程序包括用于执行以下方法中的步骤的指令：
    确定所述检索词对应的目标检索词类型；
    按照预设的算法与检索词类型之间的映射关系，确定所述目标检索词类型对应的目标算法；
    依据所述目标算法，确定所述至少一个搜索结果中的每一搜索结果与所述检索词之间的相关度，得到至少一个相关度。
  18. 根据权利要求10-17任一项所述的电子设备，其特征在于，在所述获取输入的检索词方面，所述程序包括用于执行以下方法中的步骤的指令：
    获取输入内容；
    在输入内容不为文本内容时，将所述输入内容转化为目标文本内容；
    对所述目标文本内容进行关键字提取，得到所述检索词。
  19. 一种计算机可读存储介质，其特征在于，存储用于电子数据交换的计算机程序，其中，所述计算机程序使得计算机执行如权利要求1-9任一项所述的方法。
  20. 一种计算机程序产品，其特征在于，所述计算机程序产品包括存储了计算机程序的非瞬时性计算机可读存储介质，所述计算机程序可操作来使计算机执行如权利要求1-9任一项所述的方法。
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