WO2020044094A1 - Procédé et appareil de recommandation de ressource, dispositif électronique et support lisible par ordinateur - Google Patents

Procédé et appareil de recommandation de ressource, dispositif électronique et support lisible par ordinateur Download PDF

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Publication number
WO2020044094A1
WO2020044094A1 PCT/IB2018/057156 IB2018057156W WO2020044094A1 WO 2020044094 A1 WO2020044094 A1 WO 2020044094A1 IB 2018057156 W IB2018057156 W IB 2018057156W WO 2020044094 A1 WO2020044094 A1 WO 2020044094A1
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WO
WIPO (PCT)
Prior art keywords
images
user
demand target
feature
physical location
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Application number
PCT/IB2018/057156
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English (en)
Chinese (zh)
Inventor
蔡山清
Original Assignee
优视科技新加坡有限公司
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Publication of WO2020044094A1 publication Critical patent/WO2020044094A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0252—Targeted advertisements based on events or environment, e.g. weather or festivals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0261—Targeted advertisements based on user location
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/52—Network services specially adapted for the location of the user terminal
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/55—Push-based network services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/35—Services specially adapted for particular environments, situations or purposes for the management of goods or merchandise

Definitions

  • the present application relates to the field of computer technology, and particularly to the field of Internet technology, and in particular, to a resource recommendation method, apparatus, electronic device, and computer-readable storage medium. Background technique
  • the location-based service (LocationBasedService, LBS) system obtains the location information (geographical coordinates, Or geodetic coordinates), a value-added service that provides users with corresponding services under the support of a Geographic Information System (GIS) platform.
  • LBS LocationBasedService
  • GIS Geographic Information System
  • the characteristics of the LBS service are as follows: 1. High requirements on coverage. On the one hand, the coverage needs to be large enough. On the other hand, the coverage required includes indoors. Users use this function indoors most of the time, from high-rise buildings and underground facilities must ensure coverage to every corner. According to the range of coverage, it can be divided into three types of coverage positioning services: the entire local network, covering part of the local network, and providing roaming network service types. In addition to considering coverage, network structure and dynamically changing environmental factors may also prevent a telecommunications operator from guaranteeing service in the local network or roaming network. Second, positioning accuracy requirements based on user needs. Mobile phone positioning should provide different accuracy services according to different user service needs, and can provide users with the right to choose accuracy.
  • the probability of positioning accuracy within 50 meters introduced by the FCC in the United States is 67%, and the probability of positioning accuracy within 150 meters is 95%.
  • the positioning accuracy is related to the positioning technology used, and also depends on the external environment in which the service is provided, including the radio propagation environment, the density and geographical location of the base station, and the equipment used for positioning.
  • the LBS service is considered to be one of the killer services after the short message. It has a huge market size and good profit prospects, but the actual progress is relatively slow. However, with the improvement of the industrial chain, the mobile location and location service market is expected to grow. Since 2008, the global LBS operation market will begin to accelerate its growth, but at the same time, it must pay attention to the balance between business and network performance. It should ensure the performance of the business while ensuring network performance.
  • LBS location based service
  • Check-in applications such as public comment and word of mouth will break the business based on location information
  • Instagram, Flicker and other photo sharing websites can also add the current location information
  • Facebook, Twitter, MySpace, WeChat, Weibo, etc. as Representative social networks also have services such as location sharing and location check-in; map products have brought convenience to everyone's travel; there are also some market segments that use location information to provide services to users.
  • the purpose of this application is to propose a resource recommendation method, device, electronic device, and computer-readable medium to solve the above-mentioned problems in the prior art.
  • this application provides a resource recommendation method, which includes:
  • an embodiment of the present application provides a resource recommendation device, including:
  • a first program unit configured to determine a user's physical location and a user's demand target
  • a second program unit configured to determine a plurality of images configured with position annotations, and extract feature imaging elements from the plurality of images
  • a third program unit configured to filter, based on the characteristic imaging element, an image associated with the demand target from the plurality of images
  • a fourth program unit configured to perform resource recommendation according to a position label configured in an image associated with the demand target and the physical position.
  • an electronic device including:
  • an embodiment of the present application provides a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, implements any of the foregoing methods.
  • the physical location of the user and the user's needs are determined; a plurality of images configured with position annotations are determined, and feature imaging elements are extracted from the plurality of images; according to the Feature imaging elements, filtering images associated with the demand target from the plurality of images; and performing resource recommendation based on the position labels and the physical locations configured in the images associated with the demand target, thereby improving based on Location friendly.
  • FIG. 1 is a schematic flowchart of a resource recommendation method in Embodiment 1 of the present application.
  • FIG. 2 is a schematic structural diagram of a resource recommendation device in Embodiment 2 of the present application.
  • FIG. 3 is a schematic structural diagram of a resource recommendation device in Embodiment 3 of the present application.
  • FIG. 4 is a schematic structural diagram of a device / terminal / server in Embodiment 4 of the present application; [0030] FIG. 5 is a hardware structure of the device / terminal / server in Embodiment 5 of the present application. detailed description
  • FIG. 1 is a schematic flowchart of a resource recommendation method in Embodiment 1 of the present application; as shown in FIG. 1, it includes:
  • S101 Determine the physical location of the user and the user's demand target
  • the user's physical location and the user's demand target may be determined according to the analysis result of the user input.
  • the user input is at least one of text input or voice input.
  • the user input may be a text keyword entered in a dialog box, or a voice keyword entered in a dialog box.
  • the user input can also be: a picture entered in a dialog box, or an object specified or selected by the user in the application program interface, or an object selected or specified by the user in the candidate resources recommended by the application.
  • the parsing process for the user input may include: processing the text keywords, keyword extraction, or other processing, or converting the speech keywords into text keywords. Keyword extraction, etc .; or, capturing a specified or selected action from an application program interface, and matching with content configured on the application program interface.
  • an input interface may be configured in an application program, the input interface being used to capture the user input. [0039] If the application is allowed to read the location data of the user, the physical location of the user is determined by analyzing the GPS location data in the user input.
  • the physical location of the user can be determined by analyzing the data of the radio communication network (such as GSM network, CDMA network) in the user input.
  • the radio communication network such as GSM network, CDMA network
  • the user's demand is actually the ultimate purpose of characterizing the user's current actions, such as a tourist attraction, a restaurant, or the like.
  • S102 Determine a plurality of images configured with position labels, and extract feature imaging elements from the plurality of images;
  • an image library can be configured in the background, and all images in the image library carry position labels.
  • the image library can be established based on big data search technology, that is, the analysis is performed on the input of all users using the same application to generate an image, and position annotation is added to the image.
  • a feature library is established in advance based on a neural network.
  • crawl pictures from other data sources based on the search technology, to crawl those images with position markers, and store them in the background database.
  • the image can be specifically analyzed to determine whether the analysis result includes position data. That is, all images are parsed to determine the image that is configured with position annotation.
  • a mark may also be directly marked on the image with a position mark, and the mark corresponds to a data bit, which can be directly written into the header data of the image.
  • step S103 may specifically perform enhanced recognition processing on the multiple images to extract a characteristic imaging element from the multiple images.
  • the feature imaging element according to a pre-established feature library to filter out images associated with the demand target from the plurality of images.
  • a specific application scenario is: The collected images are not limited to pictures, and can be recommended for indoor positioning. For example, in large shopping malls, it is easy to get lost. It is more difficult to find where and on which floor a person is. If the other party sends a picture here, then based on the enhanced image analysis, you can know which position the other party is on. It can be used for indoor positioning. In the last example, because the user uploaded some images, according to These images can not only know that this building has a cafe, but also where and on which floor.
  • the enhancement processing may be performed on the image after step S102 and before step S103.
  • This application obtains a sample space of a picture of a user's location, and then obtains an index number of a sample point based on image matching, and hits feature imaging elements such as historical data of buildings or landscapes in the picture, local services, and adds these feature imaging elements to The description of the attribute information of the picture.
  • the image enhancement processing may further include adding attribute information of a photographer of the picture, that is, a user, to attribute information of the picture as a characteristic imaging element.
  • the attribute information may be classified and stored to form different types of feature imaging elements. There is a-correspondence relationship between the images in the feature library and the feature imaging elements.
  • S104 Perform resource recommendation according to a position label configured in an image associated with the demand target and the physical position.
  • step S104 according to the feature imaging element, an image associated with the demand target is filtered from the multiple images, and the feature image may be specifically imaged with the feature database established in advance Element, filtering the images related to the demand target from the multiple images, and it is critical for different users to construct users at the same geographical location at the same time.
  • the feature imaging element may be based on the same imaging object, for example, the same dining place, tourist attraction, etc., or may be based on a love with the same interest, such as having similar ages.
  • the geographic location and location labeling can be directly compared, and the image similarity can be compared to achieve resource recommendation.
  • an image with the same or similar feature imaging element may be determined first by comparing the similarity of the images, and then the comparison of the geographical position and the position label may be performed to determine the same geographical position or a certain geographical position.
  • the images in the location range finally form the recommended resources, which are shared among different users, and the users are aggregated, so that the shared recommendation of resources can be performed among different users, thereby improving the friendliness.
  • the similarity between the two images may be specifically determined through calculation of a color difference value.
  • the specific process is as follows: The two images to be compared are processed separately A white background monochrome image is formed, and the size of the convolution area is calculated according to the parameter s of the adjacent area of the central pixel; the convolution calculation is completed for each input pixel point on the white background monochrome image, and each input pixel is further calculated The image moment of a point is used to determine the similarity of the pixels according to the magnitude of the image moment of the pixel. If the image moments of all pixels of the two images are in the same threshold range, the similarity between the entire image is determined.
  • image filtering can be performed based on the range of labeled locations.
  • performing resource recommendation based on the position label configured in the image associated with the demand target and the physical location includes: according to the position label configured in the image associated with the demand target and the A recommendation queue is generated at a physical location, and the resources are recommended from high to low according to the recommendation priority of the resources in the recommendation queue.
  • FIG. 2 is a schematic structural diagram of a resource recommendation device in Embodiment 2 of the present application; as shown in FIG. 2, it includes:
  • a first program unit 201 configured to determine a physical location of a user and a demand target of the user
  • a second program unit 202 configured to determine a plurality of images configured with position annotations, and extract feature imaging elements from the plurality of images;
  • a third program unit 203 is configured to filter, based on the characteristic imaging element, an image associated with the demand target from the multiple images;
  • a fourth program unit 204 is configured to perform resource recommendation according to a position label configured in an image associated with the demand target and the physical position.
  • the first program unit 201 is further configured to determine the physical location of the user and the user's demand target according to the analysis result of the user input.
  • the user input is at least one of a text input or a voice input.
  • the first program unit 201 is further configured to capture the user input through a configured input interface.
  • the second program unit 202 is further configured to analyze all images to determine an image configured with a position label.
  • the second program unit 202 is further configured to perform enhanced recognition processing on the multiple images to extract feature imaging elements from the multiple images.
  • the third program unit 203 is further configured to: The collection database and the feature imaging element filter out images related to the demand target from the plurality of images.
  • FIG. 3 is a schematic structural diagram of a resource recommendation device in Embodiment 3 of the present application; as shown in FIG. 3, it includes the first program unit 201, the second program unit 202, the third program unit 203, The fourth program unit 204 further includes a fifth program unit 205, configured to pre-establish a feature library in the foregoing method embodiment based on a neural network.
  • the fourth program unit 204 is further configured to generate a recommendation queue according to the position label configured in the image associated with the demand target and the physical location, and prioritize the recommendation of resources in the recommendation queue. Levels are recommended from high to low order resources.
  • FIG. 4 is a schematic structural diagram of a device / terminal / server in Embodiment 4 of the present application; the device / terminal / server may include:
  • processors 401 one or more processors 401;
  • the computer-readable medium 402 may be configured to store one or more programs, [0076] when the one or more programs are executed by the one or more processors, so that the one or more processors Implement the resource recommendation method as described in any of the above embodiments.
  • the hardware structure of the device / terminal / server may include: a processor 501, a communication interface 502, and a computer readable Medium 503 and communication bus 504;
  • the processor 501, the communication interface 502, and the computer-readable medium 503 complete communication with each other through a communication bus 504;
  • the communication interface 502 may be an interface of a communication module, such as an interface of a GSM module;
  • the processor 501 may be specifically configured to: determine a user's physical location and a user's demand target; determine a plurality of images configured with position annotations, and extract feature imaging elements from the plurality of images; The feature imaging element selects an image associated with the demand target from the plurality of images; and performs resource recommendation based on a position label configured in the image associated with the demand target and the physical location.
  • the processor 501 may be a general-purpose processor, including a central processing unit (CPU), a network processor (Network Processor, NP), etc .; it may also be a digital signal processor (DSP), dedicated integration Circuit (ASIC), off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic Pieces, discrete hardware components.
  • DSP digital signal processor
  • ASIC dedicated integration Circuit
  • FPGA off-the-shelf programmable gate array
  • a general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • the computer-readable medium 503 may be, but is not limited to, a random access memory (Random Access Memory, RAM), a read-only memory (Read Only Memory, ROM), and a programmable read-only storage medium (Programmable Read- Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electric Erasable Programmable Read-Only Memory (EEPR0M), etc.
  • RAM Random Access Memory
  • ROM Read Only Memory
  • EEPR0M Electric Erasable Programmable Read-Only Memory
  • the process described above with reference to the flowchart may be implemented as a computer software program.
  • embodiments of the present application include a computer program product including a computer program borne on a computer-readable medium, the computer program containing program code configured to execute the method shown in the flowchart.
  • the computer program may be downloaded and installed from a network through a communication section, and / or installed from a removable medium.
  • CPU central processing unit
  • the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two.
  • the computer-readable medium may be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.
  • Computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access storage media (RAM), read-only storage media (ROM), erasable Type programmable read-only storage medium (EPR0M or flash memory), optical fiber, portable compact disk read-only storage medium (CD-ROM), optical storage medium piece, magnetic storage medium piece, or any suitable combination of the foregoing.
  • a computer-readable storage medium may be any tangible medium containing or storing a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal that is included in baseband or propagated as part of a carrier wave, and which carries computer-readable program code. Such a propagated data signal may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium.
  • the computer-readable medium may be A program configured to be sent, propagated, or transmitted for use by or in combination with an instruction execution system, device, or device.
  • Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
  • the computer program code configured to perform the operations of the present application may be written in one or more programming languages or combinations thereof, the programming languages including an object-oriented programming language such as Java, Smalltalk, C ++ It also includes conventional procedural programming languages such as "C" or similar programming languages.
  • the program code can be executed entirely on the user's computer, partly on the user's computer, as an independent software package, partly on the user's computer, partly on a remote computer, or entirely on a remote computer or server.
  • the remote computer can be connected to a user's computer through any kind of network: including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as through the Internet using an Internet service provider) Connection).
  • LAN local area network
  • WAN wide area network
  • Internet service provider Internet service provider
  • each block in the flowchart or block diagram may represent a module, a program segment, or a portion of a code, which module, program segment, or portion of the code contains one or more logic functions configured to implement a specified logic function.
  • Executable instructions In the above specific embodiments, there is a specific sequence relationship, but these sequence relationships are only exemplary. In specific implementation, these steps may be fewer, more or the execution order may be adjusted. That is, in some alternative implementations, the functions marked in the boxes may occur in a different order than those marked in the drawings.
  • each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts may be implemented in a dedicated hardware-based system that performs the specified function or operation. Or, it can be implemented by a combination of dedicated hardware and computer instructions.
  • a processor includes a demand target determination unit, a feature extraction unit, a screening unit, and a recommendation unit. among them: [0088] a demand target determination unit configured to determine a physical location of the user and a demand target of the user;
  • a feature extraction unit configured to determine a plurality of images configured with position annotations, and extract a feature imaging element from the plurality of images
  • a screening unit configured to screen out images associated with the demand target from the plurality of images according to the characteristic imaging element
  • a recommendation unit configured to perform resource recommendation according to a position label configured in an image associated with the demand target and the physical position.
  • the names of these units do not constitute a limitation on the unit itself in some cases.
  • the demand target determination unit may also be described as a “unit that determines the physical location of the user and the user ’s demand target”.
  • the present application also provides a computer-readable medium on which a computer program is stored, and the program is executed by a processor to implement a method as described in any one of the foregoing embodiments.
  • the present application further provides a computer-readable medium, which may be included in the device described in the foregoing embodiments; or may exist separately without being assembled into the device.
  • the computer-readable medium carries one or more programs, and when the one or more programs are executed by the device, the device causes the device to: determine a user's physical location and a user's demand target; determine a plurality of images configured with position annotations And extracting feature imaging elements from the plurality of images; filtering images associated with the demand target from the plurality of images according to the feature imaging elements; and according to the images associated with the demand target
  • the configured position label and the physical position are used for resource recommendation.
  • first, second, the first, or “the second” used in the various embodiments of the present application may modify various components with sequence and / or Importance is irrelevant, but these expressions do not limit the corresponding components.
  • the above expression is only configured for the purpose of distinguishing the element from other elements.
  • the first user equipment and the second user equipment represent different user equipments, although both are user equipments.
  • a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.
  • an element eg, a first element
  • another element e.g., a second element
  • another element e.g., a second element
  • the one element is directly connected to the other element or the one element is indirectly connected to the other element via another element (eg, a third element).
  • an element for example, the first element
  • the second element no element (for example, the third element) is inserted between the two elements.

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Abstract

La présente invention porte sur un procédé et sur un appareil de recommandation de ressource, sur un dispositif électronique et sur un support lisible par ordinateur. Une manière spécifique de mettre en œuvre le procédé consiste : à déterminer un emplacement physique d'un utilisateur et une cible d'exigence de l'utilisateur ; à déterminer de multiples images dotées de marques d'emplacement, et à extraire des éléments d'imagerie caractéristiques à partir des multiples images ; à filtrer une image associée à la cible d'exigence à partir des multiples images en fonction des éléments d'imagerie caractéristiques ; et à recommander une ressource en fonction de la marque d'emplacement fournie dans une image associée à la cible d'exigence ainsi qu'en fonction de l'emplacement physique. La solution technique des modes de réalisation de la présente invention améliore la convivialité d'une interaction basée sur un emplacement.
PCT/IB2018/057156 2018-08-27 2018-09-18 Procédé et appareil de recommandation de ressource, dispositif électronique et support lisible par ordinateur WO2020044094A1 (fr)

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