WO2018107991A1 - 一种实体信息验证方法及装置 - Google Patents

一种实体信息验证方法及装置 Download PDF

Info

Publication number
WO2018107991A1
WO2018107991A1 PCT/CN2017/114434 CN2017114434W WO2018107991A1 WO 2018107991 A1 WO2018107991 A1 WO 2018107991A1 CN 2017114434 W CN2017114434 W CN 2017114434W WO 2018107991 A1 WO2018107991 A1 WO 2018107991A1
Authority
WO
WIPO (PCT)
Prior art keywords
entity
information
candidate
condition
entities
Prior art date
Application number
PCT/CN2017/114434
Other languages
English (en)
French (fr)
Inventor
薛克兢
吴鹏志
Original Assignee
阿里巴巴集团控股有限公司
薛克兢
吴鹏志
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 阿里巴巴集团控股有限公司, 薛克兢, 吴鹏志 filed Critical 阿里巴巴集团控股有限公司
Priority to KR1020197020440A priority Critical patent/KR102225194B1/ko
Priority to JP2019531989A priority patent/JP6773909B2/ja
Priority to EP17881231.9A priority patent/EP3557514A4/en
Publication of WO2018107991A1 publication Critical patent/WO2018107991A1/zh
Priority to US16/440,868 priority patent/US10531225B2/en
Priority to US16/693,595 priority patent/US10681492B1/en
Priority to US16/895,778 priority patent/US10966052B2/en
Priority to US17/215,822 priority patent/US11212641B2/en

Links

Images

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
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
    • 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
    • G06Q30/018—Certifying business or products
    • 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
    • G06Q30/018—Certifying business or products
    • G06Q30/0185—Product, service or business identity fraud
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
    • 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
    • H04W4/029—Location-based management or tracking services

Definitions

  • the present application relates to the field of computer technologies, and in particular, to a method and device for verifying physical information.
  • the user is usually required to upload some entity information and perform entity verification.
  • the entity information may include location information, name information, real-life image, and the like.
  • the entity information of the physical store provided by the merchant is verified; the entity information of the company provided by the user is verified.
  • the prior art generally uses manual review to verify the location information and the real-life image in the entity information, for example, manually checking the location information of the physical store provided by the merchant and the image of the store; for example, the company provided to the user Location information and company images are manually reviewed.
  • the embodiment of the present application provides an entity information verification method for improving the accuracy of verifying entity information.
  • the embodiment of the present application provides an entity information verification apparatus for improving the accuracy of the verification entity information.
  • An entity information verification method includes:
  • An entity information verification apparatus includes: a first determining unit, a second determining unit, and a verifying unit, wherein
  • the first determining unit determines location information in the entity information sent by the user
  • the second determining unit determines, according to the location information, a set of candidate entities that satisfy a preset relationship with the location of the entity, where the entity does not include the entity;
  • the verification unit verifies the entity information according to the judgment result of the candidate entity information corresponding to the candidate entity set by the user under preset verification conditions.
  • the foregoing at least one technical solution adopted by the embodiment of the present application can achieve the following beneficial effects: determining, according to location information in the entity information sent by the user, a set of candidate entities that satisfy a preset condition with the entity and do not include the entity, The verification is performed according to the judgment result of the candidate entity information corresponding to the candidate entity set under the preset verification condition.
  • the manual verification is more subjectively judging the authenticity of the entity information itself, and the verification accuracy is low.
  • the solution bypasses the entity itself, and is more objective according to the user's understanding of the surrounding environment of the entity. Verify the authenticity of the entity from the side, thus improving the accuracy of the verification.
  • the program reduces or even avoids manual audit interventions, thereby improving the timeliness of the verification process.
  • FIG. 1 is a schematic flowchart of an entity information verification method according to Embodiment 1 of the present application.
  • FIG. 2 is a schematic flowchart of a method for verifying entity information according to Embodiment 2 of the present application
  • FIG. 3 is a schematic flowchart of a physical store verification method according to Embodiment 3 of the present application.
  • FIG. 4 is a schematic diagram of a geographic location of a physical store provided by Embodiment 3 of the present application.
  • FIG. 5 is a schematic diagram of determining a candidate entity store according to an adjacent condition according to Embodiment 3 of the present application;
  • FIG. 6 is a schematic diagram of a selection interface provided by Embodiment 3 of the present application.
  • FIG. 7 is a structural diagram of an entity information verification apparatus according to Embodiment 4 of the present application.
  • the prior art generally uses manual auditing to verify location information and real-life images in the entity information.
  • the merchant provides location information of the physical store (eg, “XX Street XX”) and Shop images (such as shop facade photos, store interior layout photos, etc.), business personnel can not go to the field to verify each entity information, the vast majority can only rely on experience or experience, the subjective judgment of authenticity of this information, this
  • location information e.g., “XX Street XX”
  • Shop images such as shop facade photos, store interior layout photos, etc.
  • Step 11 Determine location information in the entity information sent by the user.
  • An entity can refer to an object that exists in reality.
  • the verification of entity information mentioned in this application is to determine whether an entity actually exists in reality.
  • the entity information is verified in the Internet service, it may be whether the physical store of the merchant is real or not, and whether the user's work unit exists or not, so the entity mentioned here may be a physical store or a work unit.
  • the entity information may include location information, name information, real-life image, etc., for example, for a physical store, the location information may be a geographic location; the name information may be a name of the store; the real-life image may be a photo of the facade of the store, Interior decoration, decoration, layout photos, etc.
  • the entity information sent by the user may be received, and the location information in the entity information is determined. For example, "XX Street XX”.
  • coordinate information (such as "Nxxxx, Exxxx") sent by the user through the terminal may be received, and specifically, may be transmitted through a GPS (Global Positioning System), a Beidou satellite navigation system, or the like.
  • the entity in this embodiment may be referred to as an entity to be verified, that is, an entity that has not been successfully verified.
  • Step 12 Determine, according to the location information, a set of candidate entities that satisfy a preset relationship with the location relationship of the entity.
  • the entity information of the verification entity is directly verified. Since it is impossible to determine whether the entity to be verified exists, it is difficult to determine the authenticity without performing on-site verification.
  • the inventor has repeatedly thought that the entity is relatively fixed, such as the geographical location of the physical store, the geographical location of the work unit, the geographical location of the public place, etc., and the probability of frequent relocation is small. So if the entity is real, then the merchant (user) is not only familiar with the entity in which it is located, but also familiar with nearby entities. Therefore, in the case where the authenticity of the entity to be verified cannot be determined, it can be utilized from the side.
  • the entity near the entity to be verified the information of the entity to be verified is verified. However, when the merchant (user) is familiar with the nearby entities, it is also unfamiliar to the entity far away from the entity to be verified, so it is also possible to use the entity far from the entity to be verified to verify from the side. The entity's information is verified.
  • this step may determine an entity having a certain relationship with the location of the entity to be verified according to the location information of the entity to be verified, and perform verification according to the user's knowledge of the entity. That is, in this step, the set of candidate entities that meet the preset condition may be determined, and the specific preset condition may be adjacent to the entity to be verified (satisfying the neighboring condition), or may not be adjacent to the entity to be verified (satisfying Non-adjacent condition). Whether the neighboring condition is satisfied can be filtered by the preset distance threshold, and whether the non-adjacent condition is satisfied can be filtered not only by the preset distance threshold but also by the area division in the geographical location.
  • the step may search for an entity whose distance from the entity to be verified is less than 200 meters according to the location information of the entity to be verified, and determine the set as a candidate entity.
  • a quantity such as three or four, and select three from all entities that satisfy the preset condition. Entity collection.
  • the step may include: determining, according to the location information, a first entity set that satisfies an adjacent condition with a location relationship of the entity, and/or determining a location relationship with the entity according to the location information.
  • a second set of entities satisfying non-contiguous conditions determining the first set of entities and/or the second set of entities as a set of candidate entities.
  • the candidate entity set may include only the entity that is closer to the entity to be verified, or only the entity that is farther away from the entity to be verified, and may include both the entity closer to the entity to be verified and the to-be-verified entity.
  • An entity that is farther away from the entity Considering that the user is more familiar with the environment in the vicinity of the entity than the environment farther away from the entity, it is more effective to verify the entity by the first entity set satisfying the proximity condition with the location relationship of the entity, so in one embodiment
  • the set of candidate entities includes at least a first set of entities.
  • the information about the entity to be verified can be verified from the side to be verified by the entity to be verified. Therefore, this step may not include the candidate entity when determining the location relationship with the entity that satisfies the preset condition. The entity being verified.
  • the identified candidate entity needs to have high authenticity, for example, it may be a well-known entity (large-scale shopping mall, shopping center, chain brand physical store, etc.), it can be said that it is certain To a certain extent, the authenticity of the candidate entity indirectly determines the authenticity of the verification entity information.
  • Step 13 Verify the entity information according to the judgment result of the candidate entity information corresponding to the candidate entity set under the preset verification condition.
  • the candidate entity set has been determined, and the entity to be verified is not included in the set, so the candidate entity information corresponding to the candidate entity set can be provided to the user, and the preset verification condition is also Provided to the user, the information of the entity to be verified is verified according to the judgment result of the candidate entity information under the preset verification condition.
  • the set of candidate entities determined in step 12 includes three entities satisfying the neighboring condition and five entities satisfying the non-adjacent condition.
  • the candidate entity information corresponding to the 8 candidate entities may be sent to the user together (or one by one), and together with the verification condition of sending “select nearby entities”. After that, the result of the selection of the candidate entity by the user can be obtained. If the three entities selected by the user are the same as the three entities satisfying the adjacent condition, the verification can be verified.
  • the candidate entity information corresponding to the eight candidate entities may also be sent to the user one by one, together with the verification condition of sending the “select remote entity”. Thereafter, the user's judgment result on the candidate entity can be obtained. If the user determines that the "farther entity" is the same as any three of the five entities satisfying the non-adjacent condition (that is, the correct rate exceeds 50%), then the verification can be performed. by.
  • the set of candidate entities that meet the preset condition and does not include the entity is determined according to the location information of the entity, according to the preset verification condition of the user.
  • the entity is verified by the judgment result of the candidate entity information corresponding to the candidate entity set.
  • the manual verification is more subjectively judging the authenticity of the entity information itself, and the verification accuracy is low.
  • the solution bypasses the entity itself, and is more objective according to the user's understanding of the surrounding environment of the entity. Verify the authenticity of the entity from the side, thus improving the accuracy of the verification.
  • the program can reduce or even avoid manual review interventions, thereby improving the timeliness of the verification process.
  • Step 21 Determine location information in the entity information sent by the user.
  • This step is similar to step 11 in Embodiment 1, and will not be described again.
  • Step 22 Determine, according to the location information, a first entity set that satisfies an adjacent condition with a location relationship of the entity, and determine the first entity set as a candidate entity set.
  • step 12 in the embodiment 1, it has been mentioned that considering that the environment in the vicinity of the user (to be verified) entity is more familiar than the environment farther away from the entity, the first condition of the adjacent condition is satisfied by the positional relationship with the entity.
  • the entity set is more effective for verifying the entity, so this step can determine, according to the location information, the first entity set that satisfies the neighboring condition with the location relationship of the entity, and then directly determines the first actual set as the candidate entity set. That is, each of the candidate entity sets and the location relationship with the entity to be verified all satisfy the neighboring condition, that is, the candidate entities are all in the vicinity of the entity to be verified.
  • the proximity condition may be set to a circle with the position information as the center and the radius being the preset first threshold.
  • the first threshold may be 200 meters.
  • the determined set of candidate entities are entities with a center of the entity and a radius of 200 meters.
  • the first entity set (ie, the set of candidate entities) in this step also needs to have higher authenticity.
  • the number of entities in the candidate entity set may be preset, but needs to have a certain number, for example, 3 to 8. In practical applications, if the first entity that meets the adjacent condition, less than 2, can be converted into a manual audit, or the preset first threshold is expanded, for example, from 200 meters to 500 meters, so as to satisfy the collection of the first entity. Requirements. In the first entity set, the entity to be verified may also not be included.
  • Step 23 Send the proximity condition to the user.
  • the user may first provide a preset verification condition, for example, let the user select a nearby entity, so the proximity condition may be sent to the user. For example, "within 200 meters" and so on.
  • Step 24 Receive the selection result of the user from the set of candidate entities.
  • the candidate entity information corresponding to the candidate entity set may be sent to the user together with the sending of the verification condition in step 23, and a corresponding operation interface is set, so that the user can perform selection to receive the user from the candidate entity set.
  • Select the result For example, the candidate entity set includes eight candidate entities, and the candidate entity information corresponding to the eight candidate entities may be displayed together or one by one to the user, and the function buttons for implementing selection or one by one determination may be set in the operation interface, and then the waiting for receiving may be waited for. User's selection result.
  • the candidate entity information may include candidate entity name information, candidate entity real-life image, and candidate entity trademark information, and may be displayed during the display process. All of the above three items may be displayed, or only one of them may be displayed, and a combination of any two may be displayed.
  • Step 25 Verify the entity information according to the selection result.
  • the candidate entity is in the vicinity of the to-be-verified entity, and the entity to be verified is verified according to the result of the user selection.
  • the step may include: selecting the candidate entity and the first entity in the selection result. Matching is performed; when the matching degree satisfies the passing condition, the verification passes. If the match does not satisfy the pass condition, the verification fails.
  • the pass condition may be that the matching degree is greater than 50%, and the candidate entity set includes 8 first entities. If the user can select 5 (including the above) from the 8 first entities, the verification succeeds. If the user selects only 3 out of these 8 pieces, the verification fails, or it is converted to manual review and the verification is continued.
  • the location relationship with the entity is determined to satisfy the neighboring condition, and the candidate entity set that does not include the entity is determined, according to the user, the candidate is in the neighboring condition.
  • the judgment result of the candidate entity information corresponding to the entity set is verified.
  • the subjective judgment of the authenticity of the entity information itself is guided by manual review.
  • the problem of low verification accuracy is that the solution bypasses the entity itself, and according to the user's understanding of the surrounding environment of the entity, the entity near the entity to be verified is more objectively verified from the side to verify the authenticity of the entity to be verified. Thereby improving the accuracy of the verification.
  • e-commerce As has been described in the background art, e-commerce, social networking, and even banking can be accomplished through the Internet.
  • platform Internet e-commerce platform
  • O2O Online To Offline
  • the platform often needs to verify the physical store to determine whether the physical store exists.
  • the existing technology usually uses manual review to verify the location information and real-life images in the physical store, but the verification accuracy is low. . There is no guarantee of timeliness.
  • Embodiment 1 provides a physical store verification method for improving the accuracy of verifying a physical store.
  • the flow of the method is shown in Figure 3 and includes the following steps:
  • Step 31 Determine location information in the physical store information sent by the user.
  • the physical store information may include location information, and may also include name information, real-life images, trademark information, and the like.
  • location information may be coordinates including latitude and longitude.
  • Step 32 Determine, according to the location information, a first entity store set that satisfies the proximity condition with the location relationship of the physical store, and a second physical store set that satisfies the non-adjacent condition with the location relationship of the physical store.
  • "physical store 1" is the name information of the physical store transmitted by the user, and "physical store 2", “physical store 3", and the like are existing physical stores.
  • the position of the "physical store 1" in the figure is the position corresponding to the position information (including the coordinates of the latitude and longitude) in the physical store information.
  • the adjacent condition is that the position information is the center of the circle, and the radius is within a circular range of 200 meters, as shown in FIG.
  • the dotted circle is a circle with a radius of 200 meters centered on the position of "physical store 1".
  • there are three physical stores namely "physical store 2" and “physical store 3".
  • "Physical Store 4" these three physical stores are determined as the first physical store collection.
  • the non-adjacent condition is that the position information is the center of the circle and the radius is preset to a circular range of 2000 meters. Outside the circular range, there are multiple physical stores, and three "physical stores n" and “physical stores n” are selected therefrom. -1", "physical store n-2", determined as a second physical store collection.
  • Step 33 Determine the first physical store set and the second physical store set as the candidate physical store set.
  • Step 34 Send the neighboring condition and the candidate entity store information corresponding to the candidate entity store set to the user.
  • the neighboring condition is that the position information of the physical store to be verified is centered, and the radius is within a circular range of 200 meters. Then, in this step, as shown in FIG. 6, the proximity condition is sent to the user as a verification condition, and only three physical stores can be selected. For example, you can send "select 3 stores closer to you" to the user.
  • the candidate entity store information corresponding to the candidate physical store set such as the name information of the candidate physical store, and the live view image are transmitted to the user.
  • Step 35 Receive the result of the selection of the user from the set of candidate entity stores.
  • the user is provided with a selected interface so that the user can select and return the selected result.
  • this step it has been set to select only three physical stores, so this step can receive three physical stores that the user selects from the set of candidate physical stores.
  • Step 36 Match the candidate entity store in the selection result with the first entity store set; when the matching degree satisfies the passing condition, the verification passes.
  • the pass condition is that the matching degree is not less than 50%, so only when the three physical stores selected by the user are two or three of "physical store 2", "physical store 3", and "physical store 4" Verify pass Over.
  • Embodiment 3 according to the location information in the physical store information sent by the user, it is determined that the location relationship with the physical store meets the proximity condition, and the first physical store collection that does not include the physical store, and the physical store The location relationship satisfies the second entity store collection of non-adjacent conditions, and the two entity store collections are determined as the candidate entity store collection.
  • the physical store is verified based on the determination result of the candidate entity store information corresponding to the candidate entity store set under the adjacent condition. Compared with the prior art, the manual verification is more subjectively judging the authenticity of the physical store information itself, and the verification accuracy is low.
  • the solution bypasses the physical store itself, and according to the user's understanding of the surrounding environment of the physical store, It is more objective to verify the authenticity of the physical store from the side, thus improving the accuracy of verification.
  • the program can reduce or even avoid manual review interventions, thereby improving the timeliness of the verification process.
  • Embodiment 4 provides an entity information verification apparatus for improving the accuracy of verifying entity information.
  • the device includes: a first determining unit 41, a second determining unit 42, and a verifying unit 43, wherein
  • the first determining unit 41 may determine location information in the entity information sent by the user;
  • the second determining unit 42 may determine, according to the location information, a set of candidate entities that satisfy a preset condition with the location relationship of the entity, where the set of candidate entities does not include an entity;
  • the verification unit 43 can verify the entity information according to the judgment result of the candidate entity information corresponding to the candidate entity set by the user under the preset verification condition.
  • the second determining unit 42 can
  • the first set of entities and/or the second set of entities are determined as a set of candidate entities.
  • the set of candidate entities includes at least the first entity set, and the preset verification condition is an adjacent condition,
  • the entity information is verified according to the selection result.
  • the verification unit 43 can
  • the verification passes.
  • the proximity condition includes: a circle having a position as a center and a radius within a circular range of a preset first threshold.
  • the candidate entity information may include at least one of the following:
  • Candidate entity name information candidate entity real-world image; candidate entity trademark information.
  • the apparatus provided in Embodiment 4 is configured to determine, according to the location information in the entity information sent by the user, a set of candidate entities that meet the preset condition and do not include the entity, according to the preset verification condition of the user. The result of the determination of the candidate entity information corresponding to the candidate entity set is verified.
  • the manual verification is more subjectively judging the authenticity of the entity information itself, and the verification accuracy is low.
  • the solution bypasses the entity itself, and is more objective according to the user's understanding of the surrounding environment of the entity. Verify the authenticity of the entity from the side, thus improving the accuracy of the verification.
  • the program reduces or even avoids manual audit interventions, thereby improving the timeliness of the verification process.
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment in combination of software and hardware.
  • the application may employ computer-usable storage media (including but not limited to disk storage, in one or more of the computer-usable program code embodied therein.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
  • RAM random access memory
  • ROM read only memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape storage or other magnetic storage
  • PRAM phase change memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • RAM random access memory
  • ROM read only memory
  • EEPROM electrically erasable programmable read only memory
  • flash memory or other memory technology
  • CD-ROM compact disc
  • DVD digital versatile disc
  • magnetic cassette magnetic tape storage or other magnetic storage
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware.
  • the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Development Economics (AREA)
  • Strategic Management (AREA)
  • Accounting & Taxation (AREA)
  • General Business, Economics & Management (AREA)
  • Economics (AREA)
  • Finance (AREA)
  • Marketing (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Image Analysis (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

一种实体信息验证方法及装置，用于提高验证实体信息的准确性。所述方法包括：确定用户发送的实体信息中的位置信息（11）；根据所述位置信息，确定与所述实体的位置关系满足预设条件的候选实体集合（12），所述候选实体集合中不包含所述实体；根据所述用户在预设验证条件下对所述候选实体集合对应的候选实体信息的判断结果，对所述实体信息进行验证（13）。

Description

一种实体信息验证方法及装置 技术领域
本申请涉及计算机技术领域，尤其涉及一种实体信息验证方法及装置。
背景技术
随着互联网的发展，越来越多的业务可以通过互联网完成，比如电子商务、网络社交、甚至是银行业务等。基于真实性、以及安全性的考虑，通常会要求用户上传一些实体信息，进行实体验证，比如，实体信息可以包括位置信息、名称信息、实景图像等。具体比如，对商家提供的实体店铺的实体信息进行验证；对用户提供的公司的实体信息进行验证等。
现有技术通常采用人工审核的方式，对实体信息中的位置信息和实景图像的进行验证，比如，对商家提供的实体店铺的位置信息以及店铺图像进行人工审核；又如，对用户提供的公司位置信息以及公司图像进行人工审核。
但是，现实环境中，位置信息和实景图像复杂多变，人工审核不可能逐一实地核查每个实体的位置信息和实景图像的真实性，只能根据经验或阅历较为主观地进行验证；其次，伪造位置信息和实景图像极为简单，这会给人工审核造成很大的干扰，所以现有技术基于位置信息和实景图像的组合，通过人工审核的方式，对实体信息进行验证，准确性很低。此外，人工审核还受工作时间和人力的限制，时效性很难持续保证。
发明内容
本申请实施例提供一种实体信息验证方法，用于提高验证实体信息的准确性。
本申请实施例提供一种实体信息验证装置，用于提高验证实体信息的准确性。
本申请实施例采用下述技术方案：
一种实体信息验证方法，包括：
确定用户发送的实体信息中的位置信息；
根据所述位置信息，确定与所述实体的位置关系满足预设条件的候选实体集合，所述候选实体集合中不包含所述实体；
根据所述用户在预设验证条件下对所述候选实体集合对应的候选实体信息的判断结果，对所述实体信息进行验证。
一种实体信息验证装置，包括：第一确定单元、第二确定单元以及验证单元，其中，
所述第一确定单元，确定用户发送的实体信息中的位置信息；
所述第二确定单元，根据所述位置信息，确定与所述实体的位置关系满足预设条件的候选实体集合，所述候选实体集合中不包含所述实体；
所述验证单元，根据所述用户在预设验证条件下对所述候选实体集合对应的候选实体信息的判断结果，对所述实体信息进行验证。
本申请实施例采用的上述至少一个技术方案能够达到以下有益效果：根据用户发送的实体信息中的位置信息，确定与该实体的位置关系满足预设条件、且不包含该实体的候选实体集合，根据该用户在预设验证条件下对该候选实体集合对应的候选实体信息的判断结果，进行验证。相比于现有技术通过人工审核较为主观地判断实体信息本身的真实性而导致的验证准确性较低的问题，本方案绕过实体本身，根据用户对实体周围环境的了解情况，较为客观的从侧面验证实体的真实性，从而提高了验证的准确性。此外，本方案减少、甚至可以避免人工审核的干预，从而提高了验证过程的时效性。
附图说明
此处所说明的附图用来提供对本申请的进一步理解，构成本申请的一部分，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：
图1为本申请实施例1提供的一种实体信息验证方法的流程示意图；
图2为本申请实施例2提供的一种实体信息验证方法的流程示意图；
图3为本申请实施例3提供的一种实体店铺验证方法的流程示意图；
图4为本申请实施例3提供的实体店铺地理位置的示意图；
图5为本申请实施例3提供的根据临近条件确定候选实体店铺的示意图；
图6为本申请实施例3提供的选取界面的示意图；
图7为本申请实施例4提供的实体信息验证装置的结构图。
具体实施方式
为使本申请的目的、技术方案和优点更加清楚，下面将结合本申请具体实施例及相应的附图对本申请技术方案进行清楚、完整地描述。显然，所描述的实施例仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
以下结合附图，详细说明本申请各实施例提供的技术方案。
实施例1
如前所述，现有技术通常采用人工审核的方式，对实体信息中的位置信息和实景图像的进行验证，比如，商家提供了实体店铺的位置信息(如，“XX街道XX号”)以及店铺图像(如店铺门面照片、店铺内装修布局照片等)，业务人员不可能去实地核实每个实体信息，绝大多数只能根据经验或阅历，对这些信息较为主观地判断真实性，这本就没有一个标准去判断真实性，并且随时计算机软件的发展，伪造位置信息和实景图像极为简单，所以基于上述两点，人工审核的方式准确性很低。此外，人工审核毕竟受工作时间和人力的限制，所以也很难保证时效性。基于上述缺陷，本申请实施例提供了一种实体信息验证方法，用于提高验证实体信息的准确性。该方法的流程如图1所示，包括下述步骤：
步骤11：确定用户发送的实体信息中的位置信息。
实体可以是指现实中真实存在的物体，比如，本申请中提到的对实体信息进行验证，就是确定实体是否真正存在于现实中。互联网业务中进行实体信息验证时，可以是验证商家的实体店铺是否真实存在，用户的工作单位是否真实存在等，所以这里提到的实体，就可以是实体店铺、工作单位等。
在前文已经介绍，实体信息可以包括位置信息、名称信息、实景图像等，比如对于实体店铺而言，位置信息可以是地理位置；名称信息可以是店铺的名称；实景图像可以是店铺的门面照片、店铺内装修、装饰、布局照片等。
当需要对用户发送的实体信息进行验证时，可以接收用户发送的实体信息，并确定出实体信息中的位置信息。比如“XX街道XX号”。在实际应用中，也可以接收用户通过终端发送的坐标信息(如“Nxxxx，Exxxx”)等，具体地，可以通过GPS(Global Positioning System，全球定位系统)、北斗卫星导航系统等进行发送。
为了便于说明，可以将本实施例中的实体称为待验证实体，即还未验证成功的实体。
步骤12：根据该位置信息，确定与该实体的位置关系满足预设条件的候选实体集合。
现有技术，是直接对待验证实体的实体信息进行验证，由于原本就无法确定该待验证实体是否存在，所以如果不进行实地核查，很难确定其真实性。而发明人经过反复思考发现，实体是相对固定的，比如实体店铺的地理位置、工作单位的地理位置、公共场所的地理位置等，频繁搬迁的概率很小。所以如果实体是真实存在的，那么商家(用户)不仅对自己所处的实体比较熟悉，并且对附近的实体也较为熟悉，所以，在无法确定待验证实体真实性的情况，可以从侧面，利用待验证实体附近的实体，对待验证实体的信息进行验证。然而，商家(用户)对附近的实体较为熟悉的同时，对与待验证实体距离较远的实体也比较陌生，所以，也可以从侧面，利用与待验证实体较远的实体，对待验证 实体的信息进行验证。
所以，根据上文的分析，本步骤可以根据待验证实体的位置信息，确定与该待验证实体的位置具有一定关系的实体，并根据用户对这些实体的了解情况进行验证。即本步骤可以确定与该实体的位置关系满足预设条件的候选实体集合，具体的预设条件，可以与待验证实体较为临近(满足临近条件)，也可以是与待验证实体不临近(满足非临近条件)。是否满足临近条件可以通过预设距离阈值进行过滤，而是否满足非临近条件不仅可以通过预设距离阈值进行过滤，还可以根据地理位置中的区域划分进行过滤。比如，预设条件可以是“小于200米”，则本步骤就可以根据待验证实体的位置信息，查找与该待验证实体的距离小于200米的实体，并确定为候选实体集合。在实际应用中，考虑到确定出过多的实体意义不大，所以一般可以预先设定一个数量，比如3个、4个等，从满足预设条件的所有实体中，选取3个，组成候选实体集合。
在前文已经介绍，从侧面既可以利用待验证实体附近的实体，对待验证实体的信息进行验证，又可以利用与待验证实体较远的实体，对待验证实体的信息进行验证。所以，在一种实施方式中，本步骤可以包括：根据该位置信息，确定与该实体的位置关系满足临近条件的第一实体集合，和/或根据该位置信息，确定与该实体的位置关系满足非临近条件的第二实体集合；将该第一实体集合和/或该第二实体集合确定为候选实体集合。即候选实体集合中，既可以只包含与待验证实体较近的实体，也可以只包含与待验证实体较远的实体，还可以既包含与待验证实体较近的实体，又包含与待验证实体较远的实体。考虑到用户对实体附近的环境相比于与实体较远的环境更为熟悉，通过与实体的位置关系满足临近条件的第一实体集合对实体进行验证更为有效，所以在一种实施方式中，候选实体集合至少包含第一实体集合。
前文已经提到，可以从侧面利用待验证实体附近的实体，对待验证实体的信息进行验证，所以，本步骤在确定与该实体的位置关系满足预设条件的候选实体集合时，可以不包括待验证的实体。
需要说明的是，在本步骤中，确定出的候选实体需要具备较高的真实性，比如可以是知名度较高的实体(大型商场、购物中心、连锁品牌实体店等)，可以说，在一定程度上，候选实体的真实性间接决定了验证实体信息的真实性。
步骤13：根据该用户在预设验证条件下对候选实体集合对应的候选实体信息的判断结果，对该实体信息进行验证。
在上一步骤中，已经确定出了候选实体集合，该集合中不包含待验证的实体，所以此时可以将候选实体集合对应的候选实体信息，提供给该用户，以及将预设验证条件也提供给该用户，根据用户在预设验证条件下对这些候选实体信息的判断结果，对待验证实体的信息进行验证。
比如，步骤12中确定出的候选实体集合中，包括3个满足临近条件的实体以及5个满足非临近条件的实体。可以将这8个候选实体对应的候选实体信息，一并(或逐一)发送给用户，并连同发送“选择附近实体”的验证条件。此后，就可以获取用户对候选实体的选取结果，如果用户选取的3个实体与3个满足临近条件的实体相同，则可以验证通过。还可以将这8个候选实体对应的候选实体信息，逐一发送给用户，并连同发送“选择较远实体”的验证条件。此后，就可以获取用户对候选实体的判断结果，如果用户判断出的“较远实体”与5个满足非临近条件的实体中的任意3个相同(即正确率超过50％)，则可以验证通过。
采用实施例1提供的方法，根据用户发送的实体信息中的位置信息，确定与该实体的位置关系满足预设条件、且不包含该实体的候选实体集合，根据该用户在预设验证条件下对该候选实体集合对应的候选实体信息的判断结果，对该实体进行验证。相比于现有技术通过人工审核较为主观地判断实体信息本身的真实性而导致的验证准确性较低的问题，本方案绕过实体本身，根据用户对实体周围环境的了解情况，较为客观的从侧面验证实体的真实性，从而提高了验证的准确性。此外，本方案可以减少、甚至避免人工审核的干预，从而提高了验证过程的时效性。
实施例2
基于与实施例1相同的发明思路，对本申请进行更详细地阐述，从而在本申请实施例中提供一种实体信息验证方法，用于提高验证实体信息的准确性。该方法的流程如图2所示，包括下述步骤：
步骤21：确定用户发送的实体信息中的位置信息。
本步骤与实施例1中的步骤11类似，不再赘述。
步骤22：根据该位置信息，确定与该实体的位置关系满足临近条件的第一实体集合，并将该第一实体集合确定为候选实体集合。
在实施例1介绍步骤12时，已经提到，考虑到用户对(待验证)实体附近的环境相比于与实体较远的环境更为熟悉，通过与实体的位置关系满足临近条件的第一实体集合对实体进行验证更为有效，所以本步骤就可以根据位置信息，确定与该实体的位置关系满足临近条件的第一实体集合，之后将该第一实际集合直接确定为候选实体集合。即该候选实体集合中的每个实体，与待验证实体的位置关系全部满足临近条件，也即候选实体全部在该待验证实体附近。比如，可以将临近条件设置为以位置信息为圆心，半径为预设第一阈值的圆形范围内，具体比如，第一阈值可以是200米。则确定出的候选实体集合，均为与实体为圆心，半径200米之类的实体。
在介绍步骤12中已经提到，确定出的候选实体需要具备较高的真实性，所以本步骤中的第一实体集合(即候选实体集合)也需要具备较高的真实性。其中，候选实体集合中实体的个数可以预先设定，但需要具备一定的数量，比如3个至8个。在实际应用中，如果满足临近条件的第一实体，少于2个，则可以转换为人工审核，或扩大预设第一阈值，比如由200米扩大到500米，以便满足对第一实体集合的要求。在第一实体集合中，也可以不包含待验证的实体。
步骤23：将该临近条件发送给该用户。
为了得到用户对候选实体集合中每个实体的判断结果，可以先提供给用户一个预设的验证条件，比如，让用户选出附近的实体，所以可以将该临近条件发送给该用户。比如，“200米之内”等。
步骤24：接收该用户从候选实体集合中的选取结果。
在实际应用中，可以与步骤23发送验证条件时一同将候选实体集合对应的候选实体信息发送给该用户，并设置相应的操作界面，使用户可以进行选取，以便接收用户从候选实体集合中的选取结果。比如候选实体集合中包含8个候选实体，可以将这8个候选实体对应的候选实体信息，一起或逐一展示给该用户，在操作界面中设置实现选取或逐一判断的功能按键，便可以等待接收用户的选取结果。
在展示过程中，可以将候选实体信息中的一种或多种信息进行展示，比如候选实体信息中可以包含候选实体名称信息、候选实体实景图像、候选实体商标信息，则在展示过程中，可以将上述三者全部展示，也可以只展示一者，还可以展示任意两者的组合。
步骤25：根据该选取结果，对该实体信息进行验证。
由于候选实体全部在该待验证实体附近，所以就可以根据用户的选取结果，对该待验证实体信息进行验证，具体地，本步骤可以包括：将该选取结果中的候选实体与第一实体集合进行匹配；当匹配程度满足通过条件时，验证通过。若匹配程度不满足通过条件，则验证失败。比如，通过条件可以是匹配程度大于50％，候选实体集合中包含8个第一实体，如果用户能够从这8个第一实体中选取出5个(含以上)，则验证成功。如果用户从这8个只选取出3个，则验证失败，或者转换为人工审核，继续验证。
采用实施例2提供的方法，根据用户发送的实体信息中的位置信息，确定与该实体的位置关系满足临近条件、且不包含该实体的候选实体集合，根据该用户在临近条件下对该候选实体集合对应的候选实体信息的判断结果，进行验证。相比于现有技术通过人工审核较为主观地判断实体信息本身的真实性而导 致的验证准确性较低的问题，本方案绕过实体本身，根据用户对实体周围环境的较为了解的特点，通过待验证实体附近的实体，较为客观的从侧面验证待验证实体的真实性，从而提高了验证的准确性。
实施例3
在背景技术中已经介绍，电子商务、网络社交、甚至是银行业务均可以通过互联网完成。随着经济的发展，尤其是电子商务的发展，商家可以将原本在实体店铺(线下)出售的商品通过注册在互联网电子商务平台(简称平台)(线上)上的虚拟店铺进行出售，即O2O(Online To Offline)，是指将线下的商务机会与互联网结合，通过虚拟店铺展示实体店铺。平台往往需要对实体店铺进行验证，确定是否真的存在这个实体店铺，但是现有技术通常采用人工审核的方式，对实体店铺中的位置信息和实景图像的进行验证，但是验证的准确性较低。也不能保证时效性。所以，基于与实施例1相同的发明思路，作为实施例1的延伸。本申请实施例提供了一种实体店铺验证方法，用于提高验证实体店铺的准确性。该方法的流程如图3所示，包括下述步骤：
步骤31：确定用户发送的实体店铺信息中的位置信息。
用户若要在平台上注册虚拟店铺，就需要先将实体店铺的信息进行上传，以便对其进行验证。实体店铺信息中可以包含位置信息，还可以包含名称信息、实景图像、商标信息等。比如，位置信息可以是包含经纬度的坐标。
步骤32：根据位置信息，确定与该实体店铺的位置关系满足临近条件的第一实体店铺集合，以及与该实体店铺的位置关系满足非临近条件的第二实体店铺集合。
如图4所示，“实体店铺1”为用户发送的实体店铺的名称信息，“实体店铺2”、“实体店铺3”等为已经存在的、真实的实体店铺。“实体店铺1”在图中的位置，为实体店铺信息中的位置信息(包含经纬度的坐标)对应的位置。临近条件为以该位置信息为圆心，半径为预设200米的圆形范围内，则如图5所示， 虚线圆形即为以“实体店铺1”的位置为圆心，半径为200米的圆形，在虚线圆形范围内，存在3个实体店铺，分别是“实体店铺2”、“实体店铺3”、“实体店铺4”，将这三个实体店铺确定为第一实体店铺集合。
非临近条件为以该位置信息为圆心，半径为预设2000米的圆形范围外，在这个圆形范围外，存在多个实体店铺，从中选择3个“实体店铺n”、“实体店铺n-1”、“实体店铺n-2”，确定为第二实体店铺集合。
步骤33：将第一实体店铺集合和第二实体店铺集合确定为候选实体店铺集合。
本步骤中，可以将“实体店铺2”、“实体店铺3”、“实体店铺4”以及“实体店铺n”、“实体店铺n-1”、“实体店铺n-2”，确定为候选实体店铺集合。
步骤34：将临近条件、以及候选实体店铺集合对应的候选实体店铺信息发送给该用户。
在步骤32中，临近条件为以待验证实体店铺的位置信息为圆心，半径为预设200米的圆形范围内。则本步骤就可以如图6所示，将这个临近条件作为验证条件发送给用户，并且设定只能选择3个实体店铺。比如，可以将“选出3个距离您较近的店铺”发送给用户。
与此同时，将候选实体店铺集合对应的候选实体店铺信息，比如候选实体店铺的名称信息、以及实景图像，发送给该用户。
步骤35：接收该用户从候选实体店铺集合中的选取结果。
如图6所示，为用户提供选取的界面，使用户可以选取并返回选取的结果。在前一步骤中已经设定只能选择3个实体店铺，所以，本步骤就可以接收用户从候选实体店铺集合中选取的3个实体店铺。
步骤36：将选取结果中的候选实体店铺与第一实体店铺集合进行匹配；当匹配程度满足通过条件时，验证通过。
通过条件为匹配程度不小于50％，所以只有当用户选取的3个实体店铺中，是“实体店铺2”、“实体店铺3”、“实体店铺4”中的两个或三个，才可以验证通 过。
采用实施例3提供的方法，根据用户发送的实体店铺信息中的位置信息，确定与该实体店铺的位置关系满足临近条件、且不包含该实体店铺的第一实体店铺集合、以及与该实体店铺的位置关系满足非临近条件的第二实体店铺集合，并将两实体店铺集合确定为候选实体店铺集合。根据该用户在临近条件下对该候选实体店铺集合对应的候选实体店铺信息的判断结果，对该实体店铺进行验证。相比于现有技术通过人工审核较为主观地判断实体店铺信息本身的真实性而导致的验证准确性较低的问题，本方案绕过实体店铺本身，根据用户对实体店铺周围环境的了解情况，较为客观的从侧面验证实体店铺的真实性，从而提高了验证的准确性。此外，本方案可以减少、甚至避免人工审核的干预，从而提高了验证过程的时效性。
实施例4
基于相同的发明构思，实施例4提供了一种实体信息验证装置，用于提高验证实体信息的准确性。该装置如图7所示，包括：第一确定单元41、第二确定单元42以及验证单元43，其中，
第一确定单元41，可以确定用户发送的实体信息中的位置信息；
第二确定单元42，可以根据位置信息，确定与实体的位置关系满足预设条件的候选实体集合，候选实体集合中不包含实体；
验证单元43，可以根据用户在预设验证条件下对候选实体集合对应的候选实体信息的判断结果，对实体信息进行验证。
在一种实施方式中，第二确定单元42，可以
根据位置信息，确定与实体的位置关系满足临近条件的第一实体集合，和/或
根据位置信息，确定与实体的位置关系满足非临近条件的第二实体集合；
将第一实体集合和/或第二实体集合确定为候选实体集合。
在一种实施方式中，候选实体集合至少包含第一实体集合，且预设验证条件为临近条件，则
验证单元43，可以
将临近条件发送给用户；
接收用户从候选实体集合中的选取结果；
根据选取结果，对实体信息进行验证。
在一种实施方式中，验证单元43，可以
将选取结果中的候选实体与第一实体集合进行匹配；
当匹配程度满足通过条件时，验证通过。
在一种实施方式中，临近条件，包括：以位置信息为圆心，半径为预设第一阈值的圆形范围内。
在一种实施方式中，候选实体信息，可以包括下述至少一种：
候选实体名称信息；候选实体实景图像；候选实体商标信息。
采用实施例4提供的装置，根据用户发送的实体信息中的位置信息，确定与该实体的位置关系满足预设条件、且不包含该实体的候选实体集合，根据该用户在预设验证条件下对该候选实体集合对应的候选实体信息的判断结果，进行验证。相比于现有技术通过人工审核较为主观地判断实体信息本身的真实性而导致的验证准确性较低的问题，本方案绕过实体本身，根据用户对实体周围环境的了解情况，较为客观的从侧面验证实体的真实性，从而提高了验证的准确性。此外，本方案减少、甚至可以避免人工审核的干预，从而提高了验证过程的时效性。
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、 CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器 (EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括要素的过程、方法、商品或者设备中还存在另外的相同要素。
本领域技术人员应明白，本申请的实施例可提供为方法、系统或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
以上仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。

Claims (10)

  1. 一种实体信息验证方法，其特征在于，包括：
    确定用户发送的实体信息中的位置信息；
    根据所述位置信息，确定与所述实体的位置关系满足预设条件的候选实体集合，所述候选实体集合中不包含所述实体；
    根据所述用户在预设验证条件下对所述候选实体集合对应的候选实体信息的判断结果，对所述实体信息进行验证。
  2. 如权利要求1所述的方法，其特征在于，根据所述位置信息，确定与所述实体的位置关系满足预设条件的候选实体集合，包括：
    根据所述位置信息，确定与所述实体的位置关系满足临近条件的第一实体集合，和/或
    根据所述位置信息，确定与所述实体的位置关系满足非临近条件的第二实体集合；
    将所述第一实体集合和/或所述第二实体集合确定为候选实体集合。
  3. 如权利要求2所述的方法，其特征在于，所述候选实体集合至少包含所述第一实体集合，且所述预设验证条件为满足所述临近条件，则
    根据所述用户在预设验证条件下对所述候选实体集合对应的候选实体信息的判断结果，对所述实体信息进行验证，包括：
    将所述临近条件发送给所述用户；
    接收所述用户从所述候选实体集合中的选取结果；
    根据所述选取结果，对所述实体信息进行验证。
  4. 如权利要求3所述的方法，其特征在于，根据所述选取结果，对所述实体信息进行验证，包括：
    将所述选取结果中的候选实体与所述第一实体集合进行匹配；
    当匹配程度满足通过条件时，验证通过。
  5. 如权利要求2所述的方法，其特征在于，所述临近条件，包括：以所 述位置信息为圆心，半径为预设第一阈值的圆形范围内。
  6. 如权利要求1所述的方法，其特征在于，所述候选实体信息，包括下述至少一种：
    候选实体名称信息；候选实体实景图像；候选实体商标信息。
  7. 一种实体信息验证装置，其特征在于，包括：第一确定单元、第二确定单元以及验证单元，其中，
    所述第一确定单元，确定用户发送的实体信息中的位置信息；
    所述第二确定单元，根据所述位置信息，确定与所述实体的位置关系满足预设条件的候选实体集合，所述候选实体集合中不包含所述实体；
    所述验证单元，根据所述用户在预设验证条件下对所述候选实体集合对应的候选实体信息的判断结果，对所述实体信息进行验证。
  8. 如权利要求7所述的装置，其特征在于，所述第二确定单元，
    根据所述位置信息，确定与所述实体的位置关系满足临近条件的第一实体集合，和/或
    根据所述位置信息，确定与所述实体的位置关系满足非临近条件的第二实体集合；
    将所述第一实体集合和/或所述第二实体集合确定为候选实体集合。
  9. 如权利要求8所述的装置，其特征在于，所述候选实体集合至少包含所述第一实体集合，且所述预设验证条件为所述临近条件，则
    所述验证单元，
    将所述临近条件发送给所述用户；
    接收所述用户从所述候选实体集合中的选取结果；
    根据所述选取结果，对所述实体信息进行验证。
  10. 如权利要求9所述的装置，其特征在于，所述验证单元，
    将所述选取结果中的候选实体与所述第一实体集合进行匹配；
    当匹配程度满足通过条件时，验证通过。
PCT/CN2017/114434 2016-12-14 2017-12-04 一种实体信息验证方法及装置 WO2018107991A1 (zh)

Priority Applications (7)

Application Number Priority Date Filing Date Title
KR1020197020440A KR102225194B1 (ko) 2016-12-14 2017-12-04 엔티티 정보를 검증하는 방법 및 장치
JP2019531989A JP6773909B2 (ja) 2016-12-14 2017-12-04 エンティティ情報検証方法およびデバイス
EP17881231.9A EP3557514A4 (en) 2016-12-14 2017-12-04 METHOD AND DEVICE FOR CHECKING INFORMATION FROM AN ENTITY
US16/440,868 US10531225B2 (en) 2016-12-14 2019-06-13 Method and apparatus for verifying entity information
US16/693,595 US10681492B1 (en) 2016-12-14 2019-11-25 Method and apparatus for verifying entity information
US16/895,778 US10966052B2 (en) 2016-12-14 2020-06-08 Method and apparatus for verifying entity information
US17/215,822 US11212641B2 (en) 2016-12-14 2021-03-29 Method and apparatus for verifying entity information

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201611152681.9A CN107038589B (zh) 2016-12-14 2016-12-14 一种实体信息验证方法及装置
CN201611152681.9 2016-12-14

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US16/440,868 Continuation US10531225B2 (en) 2016-12-14 2019-06-13 Method and apparatus for verifying entity information

Publications (1)

Publication Number Publication Date
WO2018107991A1 true WO2018107991A1 (zh) 2018-06-21

Family

ID=59530785

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/114434 WO2018107991A1 (zh) 2016-12-14 2017-12-04 一种实体信息验证方法及装置

Country Status (7)

Country Link
US (4) US10531225B2 (zh)
EP (1) EP3557514A4 (zh)
JP (1) JP6773909B2 (zh)
KR (1) KR102225194B1 (zh)
CN (1) CN107038589B (zh)
TW (1) TWI696086B (zh)
WO (1) WO2018107991A1 (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115099316A (zh) * 2022-06-10 2022-09-23 湖北工业大学 基于安全内积函数的多客户端人工智能分类方法及系统

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107038589B (zh) 2016-12-14 2019-02-22 阿里巴巴集团控股有限公司 一种实体信息验证方法及装置
US11587097B2 (en) * 2017-08-17 2023-02-21 James A. STOB Organization location verification
CN110189087A (zh) * 2018-02-22 2019-08-30 阿里巴巴集团控股有限公司 一种数据处理方法及计算设备
CN110633803B (zh) * 2019-08-16 2023-06-02 创新先进技术有限公司 一种线下信息核实的方法和系统
EP4184411A4 (en) * 2020-07-15 2023-08-09 Sony Group Corporation IMAGE PROCESSING DEVICE AND INFORMATION PROCESSING SYSTEM
CN114328656A (zh) * 2021-12-17 2022-04-12 中国银联股份有限公司 真实门店的验证方法、装置、设备及存储介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102687141A (zh) * 2009-06-04 2012-09-19 诺基亚公司 用于团体提供的场所数据的集成的方法和设备
WO2015165071A1 (en) * 2014-04-30 2015-11-05 Google Inc. Identifying entities to be investigated using storefront recognition
CN105323073A (zh) * 2015-11-16 2016-02-10 腾讯科技（深圳）有限公司 一种身份验证方法、装置和系统
CN107038589A (zh) * 2016-12-14 2017-08-11 阿里巴巴集团控股有限公司 一种实体信息验证方法及装置

Family Cites Families (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5774525A (en) * 1995-01-23 1998-06-30 International Business Machines Corporation Method and apparatus utilizing dynamic questioning to provide secure access control
US20020175211A1 (en) * 2001-03-19 2002-11-28 Francisco Dominquez Time and attendance system with verification of employee identity and geographical location
US7174462B2 (en) * 2002-11-12 2007-02-06 Intel Corporation Method of authentication using familiar photographs
JP2004272691A (ja) * 2003-03-10 2004-09-30 Fujitsu Ltd 物件情報登録方法および物件情報登録装置
US8229458B2 (en) * 2007-04-08 2012-07-24 Enhanced Geographic Llc Systems and methods to determine the name of a location visited by a user of a wireless device
JP2009168773A (ja) * 2008-01-21 2009-07-30 Nissan Motor Co Ltd ナビゲーション装置および情報提供方法
US7889101B2 (en) * 2008-04-14 2011-02-15 Alpine Electronics, Inc Method and apparatus for generating location based reminder message for navigation system
US20100250599A1 (en) * 2009-03-30 2010-09-30 Nokia Corporation Method and apparatus for integration of community-provided place data
US9710491B2 (en) * 2009-11-02 2017-07-18 Microsoft Technology Licensing, Llc Content-based image search
US8200247B1 (en) * 2010-02-08 2012-06-12 Google Inc. Confirming a venue of user location
US20110313779A1 (en) * 2010-06-17 2011-12-22 Microsoft Corporation Augmentation and correction of location based data through user feedback
US20120290383A1 (en) * 2011-05-15 2012-11-15 James David Busch Systems and Methods to Advertise a Physical Business Location with Digital Location-Based Coupons
US10386492B2 (en) * 2013-03-07 2019-08-20 Trimble Inc. Verifiable authentication services based on global navigation satellite system (GNSS) signals and personal or computer data
US9715003B2 (en) * 2013-03-15 2017-07-25 Facebook, Inc. Multi-factor location verification
JP2016541199A (ja) * 2013-12-06 2016-12-28 ザ ダン アンド ブラッドストリート コーポレーションＴｈｅ Ｄｕｎ Ａｎｄ Ｂｒａｄｓｔｒｅｅｔ Ｃｏｒｐｏｒａｔｉｏｎ モバイル通信及び測位通信により企業についてのデータを収集するための方法及びシステム
US9402189B2 (en) 2014-07-02 2016-07-26 Here Global B.V. Method and apparatus for providing activity-based map job
KR101646733B1 (ko) * 2014-12-29 2016-08-09 주식회사 오리진픽스 미디어 데이터 분류 방법 및 그 장치
CN104636482B (zh) * 2015-02-16 2019-03-26 百度在线网络技术（北京）有限公司 用于确定目标地址的方法和装置
KR20170001924A (ko) * 2015-06-26 2017-01-05 주식회사 씽크풀 휴대단말에서 촬영된 디지털 이미지의 유효성 검증 시스템 및 방법
US10057242B2 (en) * 2015-07-31 2018-08-21 Digital Authentication Technologies, Inc. Location authentication using multispectral imaging
US20170046891A1 (en) * 2015-08-12 2017-02-16 Tyco Fire & Security Gmbh Systems and methods for location identification and tracking using a camera
US10339174B2 (en) * 2016-02-24 2019-07-02 Time Keeping Systems, Inc. Automated location visit verification for officer monitoring systems
US10412096B2 (en) * 2017-04-18 2019-09-10 Visa International Service Association Wireless authentication based on location data
CN107687141A (zh) 2017-07-24 2018-02-13 周国京 一种防撞栏上的新型防撞球
US11120118B2 (en) * 2017-11-22 2021-09-14 International Business Machines Corporation Location validation for authentication

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102687141A (zh) * 2009-06-04 2012-09-19 诺基亚公司 用于团体提供的场所数据的集成的方法和设备
WO2015165071A1 (en) * 2014-04-30 2015-11-05 Google Inc. Identifying entities to be investigated using storefront recognition
CN105323073A (zh) * 2015-11-16 2016-02-10 腾讯科技（深圳）有限公司 一种身份验证方法、装置和系统
CN107038589A (zh) * 2016-12-14 2017-08-11 阿里巴巴集团控股有限公司 一种实体信息验证方法及装置

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3557514A4 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115099316A (zh) * 2022-06-10 2022-09-23 湖北工业大学 基于安全内积函数的多客户端人工智能分类方法及系统

Also Published As

Publication number Publication date
US20190313203A1 (en) 2019-10-10
US20210219093A1 (en) 2021-07-15
KR102225194B1 (ko) 2021-03-10
US10531225B2 (en) 2020-01-07
EP3557514A1 (en) 2019-10-23
CN107038589B (zh) 2019-02-22
US10966052B2 (en) 2021-03-30
US20200304939A1 (en) 2020-09-24
TW201822045A (zh) 2018-06-16
TWI696086B (zh) 2020-06-11
CN107038589A (zh) 2017-08-11
US20200169835A1 (en) 2020-05-28
JP2020513632A (ja) 2020-05-14
US11212641B2 (en) 2021-12-28
US10681492B1 (en) 2020-06-09
JP6773909B2 (ja) 2020-10-21
EP3557514A4 (en) 2019-12-25
KR20190097151A (ko) 2019-08-20

Similar Documents

Publication Publication Date Title
WO2018107991A1 (zh) 一种实体信息验证方法及装置
CN112491551B (zh) 基于区块链的数据验证方法及装置、电子设备
US10491375B2 (en) Secure verification of conditions of a contract using a set of verification tools
WO2020186819A1 (zh) 产品数据处理
US9892402B2 (en) Financial authorization of an online transaction based on a location and an identifier of a user device
US10885522B1 (en) Updating merchant location for cardless payment transactions
US20200005316A1 (en) Method and System for Determining Terminal Locations
US9578457B2 (en) Privacy-based device location proximity
US20220300938A1 (en) Virtual point of sale
US20230128174A1 (en) Proportional markers on a map
TW201802732A (zh) 資料風險控制的方法及裝置
US20230018081A1 (en) Method, System, and Computer Program Product for Determining Relationships of Entities Associated with Interactions
US20180182140A1 (en) Systems and Methods for a Digital Map and Canvas Layer
US10373221B1 (en) On-device directory search
US20160034861A1 (en) Method and apparatus of controlling network payment
US9787557B2 (en) Determining semantic place names from location reports
US11227220B2 (en) Automatic discovery of data required by a rule engine
US11924226B2 (en) Device analytics engine
RU2699577C1 (ru) Способ и система поиска мошеннических транзакций
US20170032368A1 (en) Systems and Methods for Authenticating Account Users
US20160012520A1 (en) System And Method Of Administering Auctions
US20230401582A1 (en) Identifying accurate locations of in-person payment card transactions to detect location-based payment card anomalies
US20240104249A1 (en) System and method for providing third party access to a system
KR20150113223A (ko) 가상 poi 생성 시스템 및 방법
WO2024173813A1 (en) Modified peer-to-peer platforms and platform services for enhancing collaboration within a digital ecosystem

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17881231

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2019531989

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 20197020440

Country of ref document: KR

Kind code of ref document: A

ENP Entry into the national phase

Ref document number: 2017881231

Country of ref document: EP

Effective date: 20190715