WO2018072335A1 - 交友对象的推荐方法和装置 - Google Patents

交友对象的推荐方法和装置 Download PDF

Info

Publication number
WO2018072335A1
WO2018072335A1 PCT/CN2016/113615 CN2016113615W WO2018072335A1 WO 2018072335 A1 WO2018072335 A1 WO 2018072335A1 CN 2016113615 W CN2016113615 W CN 2016113615W WO 2018072335 A1 WO2018072335 A1 WO 2018072335A1
Authority
WO
WIPO (PCT)
Prior art keywords
feature tag
user feature
identification code
database
device identification
Prior art date
Legal status (The legal status 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 status listed.)
Ceased
Application number
PCT/CN2016/113615
Other languages
English (en)
French (fr)
Inventor
宋夏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guangzhou Shiyuan Electronics Thecnology Co Ltd
Original Assignee
Guangzhou Shiyuan Electronics Thecnology Co Ltd
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 Guangzhou Shiyuan Electronics Thecnology Co Ltd filed Critical Guangzhou Shiyuan Electronics Thecnology Co Ltd
Publication of WO2018072335A1 publication Critical patent/WO2018072335A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
    • H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2462—Approximate or statistical queries
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
    • H04L51/21—Monitoring or handling of messages
    • H04L51/222—Monitoring or handling of messages using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
    • 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

Definitions

  • the present invention relates to the field of computer technologies, and in particular, to a method and an apparatus for recommending a friend.
  • the invention provides a recommendation method and device for a friend object, which can improve the accuracy of the recommendation of the friend, thereby improving the success rate of the friend.
  • the method for recommending a friend object provided by the present invention specifically includes:
  • the method further includes:
  • first user feature tag includes at least one feature tag
  • second user feature tag includes at least one feature tag
  • the first user feature tag is matched with the second user feature tag stored in the local area, and when the matching is successful, the neighboring device identification code is stored in the database, and the method includes:
  • the database further includes a deposit time when the adjacent device identification code is stored in the database
  • the first user feature tag is matched with the second user feature tag stored in the local area, and when the matching is successful, the neighboring device identification code is stored in the database, and the method includes:
  • the neighboring device identification code exists in the database, determining that the time interval between the depositing time and the current time corresponding to the neighboring device identification code in the database is less than or equal to a preset standard And storing, in the time interval, the adjacent device identification code into the database, and generating a corresponding deposit time;
  • the adjacent device identification code does not exist in the database, the adjacent device identification code is stored in the database, and a corresponding deposit time is generated.
  • the number of times the neighboring device identification code appears in the database is counted, and when the number of occurrences is greater than a preset threshold, generating a neighbor corresponding to the recommended identifier of the neighboring device is generated.
  • the recommendation information of the user of the device includes:
  • the previous scan result list is a scan result list obtained by performing a broadcast information scan last time
  • first user feature tag and the second user feature tag are tags that describe a personal feature of the user.
  • the present invention further provides a recommendation device for a friend object, which specifically includes:
  • a scan result reading module configured to read a scan result in the current scan result list, to obtain a neighbor device identifier and a corresponding first user feature label included in each scan result;
  • a feature tag matching module configured to match the first user feature tag with a second user feature tag stored in advance, and store the adjacent device identification code in a database when the matching is successful;
  • a friend object recommendation module configured to count the number of occurrences of the neighboring device identification code in the database, and when the number of occurrences is greater than a preset threshold, generate a phase corresponding to the recommended identifier of the neighboring device Recommended information for users of neighboring devices.
  • the recommendation device of the friend object further includes:
  • a broadcast information scanning module for scanning broadcast information using short-range wireless technology
  • a scan result storage module configured to acquire the adjacent device identification code and the first user feature tag whenever the neighboring device identification code and the first user feature tag broadcast by the neighboring device are scanned, and the The neighboring device identification code and the first user feature tag are stored in the current scan result list in a one-to-one correspondence.
  • first user feature tag includes at least one feature tag
  • second user feature tag includes at least one feature tag
  • the feature tag matching module specifically includes:
  • a first matching unit configured to match the first user feature tag with the second user feature tag, and when the first user feature tag and the second user feature tag are the same or similar
  • the number of the feature tags is greater than a preset threshold, it is determined that the matching is successful, and the adjacent device identification code is stored in the database;
  • a second matching unit configured to match the first user feature tag with the second user feature tag, and when opposite features between the first user feature tag and the second user feature tag When the number of labels is less than a preset threshold, it is determined that the matching is successful, and the adjacent device identification code is stored in the database.
  • the database further includes a deposit time when the adjacent device identification code is stored in the database
  • the feature tag matching module specifically includes:
  • the same identification code determining unit is configured to match the first user feature tag with the second user feature tag, and determine whether the neighbor device identification code exists in the database when the matching is successful;
  • a first identification code storage unit configured to determine, between the storage time corresponding to the adjacent device identification code in the database, and the current time, if the neighboring device identification code exists in the database When the time interval is less than or equal to the preset standard time interval, the adjacent device identification code is stored in the database, and a corresponding deposit time is generated; or
  • the second identification code storage unit is configured to store the adjacent device identification code in the database if the adjacent device identification code does not exist in the database, and generate a corresponding deposit time.
  • the recommendation device of the friend object further includes:
  • a list similarity calculation module configured to calculate a similarity between the current scan result list and a previous scan result list; wherein the previous scan result list is a scan result list obtained by performing a broadcast information scan last time;
  • a scanning time adjustment module configured to compare the similarity with a preset upper threshold and a preset lower threshold respectively, and when the similarity is greater than the upper threshold, reduce the next broadcast information scanning The duration, when the similarity is less than the lower threshold, increasing the duration of the next broadcast information scan.
  • first user feature tag and the second user feature tag are tags that describe a personal feature of the user.
  • the method and device for recommending a friend of the present invention by matching the user feature tag in the local device with the user feature tag obtained by scanning, screening the user of the local device among the users of all the neighboring devices scanned Interesting objects such as hobbies and similar friends, and by setting a threshold for the number of matching successes, further screening the friends of the dating object, thereby improving the accuracy of the recommendation of the dating object, thereby improving the success rate of the friends.
  • FIG. 1 is a schematic flow chart of an embodiment of a method for recommending a friend object provided by the present invention
  • FIG. 2 is a schematic diagram of an operation process of a local device in an embodiment of a method for recommending a friend object provided by the present invention
  • FIG. 3 is a schematic structural diagram of an embodiment of a recommendation device for a dating object provided by the present invention.
  • FIG. 1 is a schematic flowchart diagram of an embodiment of a method for recommending a friend object provided by the present invention, including steps S11 to S13, as follows:
  • S11 Read the scan result in the current scan result list to obtain neighboring devices included in each of the scan results An identification code and a corresponding first user feature tag;
  • S12 Match the first user feature tag with a second user feature tag stored in advance, and store the adjacent device identification code in a database when the matching is successful;
  • the recommendation method of the friend object provided by the embodiment of the present invention is performed by the local device.
  • the local device uses short-range wireless technology (in particular, the short-range wireless technology is BLE technology) to scan and acquire user feature tags broadcasted by other devices in a certain range, and the users on the local device.
  • the feature tag and the user feature tag obtained by the scan are matched and judged, so that the user corresponding to the device whose matching success times reach a certain threshold is recommended to the user of the local device.
  • the user of the local device stores in advance a second user feature tag describing its own characteristics (eg, age, ancestor, hobbies, etc.) locally.
  • the local device scans and obtains the neighboring device identifier and the corresponding first user feature tag broadcast by the neighboring devices in a certain range, the neighboring device identifier and the first user feature tag obtained by the scan are used as the scan result.
  • the one-to-one correspondence is stored in the current scan result list.
  • the adjacent device identification code may be a MAC address of a neighboring device.
  • the local device reads the respective scan results from the current scan result list, thereby obtaining the adjacent device identification code and the corresponding first user feature tag in each scan result.
  • the local device matches the first user feature label in each scan result with the second user feature label stored locally and determines whether the match is successful. If the match is successful, the first user feature label corresponds to The adjacent device identification code is stored in the database; otherwise, it is not processed. In particular, the matching process can also be done in the cloud server.
  • the local device uploads the scan result and the local device identifier read from the current scan result list and the second user feature tag stored in the local to the cloud server, so that the cloud server pairs the first user feature tag and the second user.
  • the feature tag performs a matching judgment and returns the matching judgment result to the local device.
  • the local device identifier can be the MAC address of the local device.
  • the local device separately counts the number of occurrences of each adjacent device identification code in the database according to the neighboring device identification codes stored in the database, and compares the number of times obtained by each statistic with a preset threshold. If the number of occurrences of a neighboring device identifier is greater than the threshold, the recommendation information of the user who recommends the neighboring device corresponding to the neighboring device identifier is generated, and the user of the local device is prompted to find the friend object, wherein The reminder may be to push the recommendation information to the user, or the local device itself may vibrate, flash, and the like.
  • the local device uses the short-range wireless technology to broadcast the local device identification code and the locally stored second user feature tag to the T1 broadcast
  • the short-range wireless technology is used to connect other devices in a certain range.
  • the broadcasted neighboring device identification code and the corresponding first user feature tag are scanned for a duration of T2, and after the scanning is finished, the scan result obtained by the scanning is processed, and the loop is performed accordingly.
  • FIG 2 it is a local device. Schematic diagram of the running process.
  • the local device does not scan the neighbor device identifier broadcasted by the other device and the corresponding first user feature tag, or when the first user feature tag obtained by all the scans does not match the second user feature tag stored locally
  • the adjacent device identifiers stored in the database do not reach the preset threshold in the database
  • compare the current scan result list with the previous scan result list and adjust T1 and T2 according to the comparison result. value.
  • the current scan result list is obtained by scanning the information broadcast by other devices in a certain range around the local device, and the previous scan result list is scanned by the local device for information broadcasted by other devices in a certain range. obtain.
  • the friends of all the neighboring devices that are scanned are selected to be similar to the user interests of the local devices, and the pair is passed.
  • the number of matching successes is set to a threshold, so that the friends of the dating object are further filtered, so that the accuracy of the recommendation of the dating object can be improved, thereby improving the success rate of the friends.
  • the method further includes:
  • the local device broadcasts the short-range wireless technology (in particular, the short-range wireless technology is BLE technology) to other devices in a certain range around.
  • the information is scanned, and when the neighboring device identifier broadcasted by a neighboring device and the corresponding first user feature tag are scanned, the neighboring device identifier and the corresponding first user feature tag are acquired, and The obtained adjacent device identification code and the first user feature tag are stored in the current scan result list in a one-to-one correspondence with the scan result.
  • first user feature tag includes at least one feature tag
  • second user feature tag includes at least one feature tag
  • the first user feature tag is matched with the second user feature tag stored in the local area, and when the matching is successful, the neighboring device identification code is stored in the database, and the method includes:
  • the local device matches the obtained first user feature tag and the second user feature tag stored locally, and can compare the first user feature tag with the second user feature tag (eg, “like basketball” and “Like basketball” or similar (such as “like basketball” and “like NBA") number of feature tags, and compare the number of the same or similar feature tags with a preset threshold to achieve, It is also possible to count the number of feature tags of the opposite between the first user feature tag and the second user feature tag (eg, "like meat” and “vegan”), and the opposite feature tags The number is compared with a preset threshold to achieve a comparison.
  • the matching result is a successful match, and the first user feature tag is The corresponding adjacent device identification code is stored in the database.
  • the current location of the local device and the current time may be stored in the database correspondingly.
  • the current location of the local device can be obtained through a local GPS module, or can be obtained by communicating with other smart devices that can obtain the current location for Bluetooth communication.
  • the database further includes a deposit time when the adjacent device identification code is stored in the database
  • the first user feature tag is matched with the second user feature tag stored in the local area, and when the matching is successful, the neighboring device identification code is stored in the database, and the method includes:
  • the neighboring device identification code exists in the database, determining that the time interval between the depositing time and the current time corresponding to the neighboring device identification code in the database is less than or equal to a preset standard And storing, in the time interval, the adjacent device identification code into the database, and generating a corresponding deposit time;
  • the adjacent device identification code does not exist in the database, the adjacent device identification code is stored in the database, and a corresponding deposit time is generated.
  • the local device when the local device stores the successfully matched neighbor device identification code into the database, the local device generates the storage time of the adjacent device identifier in the database.
  • the local device determines whether the neighbor device identifier corresponding to the first user feature tag exists in the database, if any And determining whether the time interval between the deposit time and the current time corresponding to the neighbor device identifier stored in the database is less than or equal to a preset standard time interval, and if so, The scan result obtained by the local device is a new scan result, and the adjacent device identification code is stored in the database, and the corresponding deposit time is generated, and if not, no processing is performed. If the neighbor device identifier corresponding to the first user feature tag does not exist in the database, the neighbor device identifier corresponding to the first user feature tag is directly stored in the database, and a corresponding deposit time is generated. .
  • the counting of the number of occurrences of the neighboring device identification code in the database is performed, and when the number of occurrences is greater than a preset threshold, generating the recommendation of the neighboring device is generated.
  • the method further includes:
  • the previous scan result list is a scan result list obtained by performing a broadcast information scan last time
  • the local device calculates the similarity between the current scan result list and the previous scan result list, and calculates the obtained similarity and the preset upper limit respectively.
  • the threshold is compared with the preset lower threshold. If the similarity is greater than the upper threshold, it is considered that the scan result obtained by the scan is smaller than the scan result obtained by the previous scan, and the local device is in a place where the crowd mobility is small. Therefore, the duration of the next broadcast information scanning is appropriately reduced; if the similarity is smaller than the lower threshold, it is considered that the scan result obtained by the scan differs greatly from the scan result obtained by the previous scan, and the local device is in a crowd flow. A more sexual location, so the duration of the next broadcast information scan is appropriately increased.
  • first user feature tag and the second user feature tag are tags that describe a personal feature of the user.
  • the feature tags in the first user feature tag and the second user feature tag are tags that describe the user's personal characteristics (eg, age, ancestry, hobbies, etc.).
  • the method for recommending a friend object in the embodiment of the present invention matches the user feature tag in the local device with the user feature tag obtained by scanning, so as to filter out the user of the local device among the users of all the neighboring devices scanned.
  • Interesting hobbies and other similar friends and by setting a threshold on the number of matching successes, Further screening, so as to improve the accuracy of referrals, thus improving the success rate of friends.
  • the present invention also provides a recommendation device for a friend object, which can implement all the processes of the recommendation method of the friend object in the above embodiment.
  • FIG. 3 it is a schematic structural diagram of an embodiment of a recommendation device for a friend object provided by the present invention, which is specifically as follows:
  • the scan result reading module 31 is configured to read the scan result in the current scan result list to obtain the adjacent device identification code and the corresponding first user feature tag included in each scan result;
  • the feature tag matching module 32 is configured to match the first user feature tag with a second user feature tag stored in advance, and store the adjacent device identification code in a database when the matching is successful; ,
  • the friend object recommendation module 33 is configured to count the number of occurrences of the neighboring device identification code in the database, and when the number of occurrences is greater than a preset threshold, generate a recommendation corresponding to the adjacent device identification code. Recommended information for users of adjacent devices.
  • the recommendation device of the friend object further includes:
  • a broadcast information scanning module for scanning broadcast information using short-range wireless technology
  • a scan result storage module configured to acquire the adjacent device identification code and the first user feature tag whenever the neighboring device identification code and the first user feature tag broadcast by the neighboring device are scanned, and the The neighboring device identification code and the first user feature tag are stored in the current scan result list in a one-to-one correspondence.
  • first user feature tag includes at least one feature tag
  • second user feature tag includes at least one feature tag
  • the feature tag matching module 32 specifically includes:
  • a first matching unit configured to match the first user feature tag with the second user feature tag, and when the first user feature tag and the second user feature tag are the same or similar
  • the number of the feature tags is greater than a preset threshold, it is determined that the matching is successful, and the adjacent device identification code is stored in the database;
  • a second matching unit configured to match the first user feature tag with the second user feature tag, and when opposite features between the first user feature tag and the second user feature tag When the number of labels is less than a preset threshold, it is determined that the matching is successful, and the adjacent device identification code is stored in the database.
  • the database further includes a deposit time when the adjacent device identification code is stored in the database
  • the feature tag matching module 32 specifically includes:
  • the same identification code determining unit is configured to match the first user feature tag with the second user feature tag, and determine whether the neighbor device identification code exists in the database when the matching is successful;
  • a first identification code storage unit configured to determine, between the storage time corresponding to the adjacent device identification code in the database, and the current time, if the neighboring device identification code exists in the database When the time interval is less than or equal to the preset standard time interval, the adjacent device identification code is stored in the database, and a corresponding deposit time is generated; or
  • the second identification code storage unit is configured to store the adjacent device identification code in the database if the adjacent device identification code does not exist in the database, and generate a corresponding deposit time.
  • the recommendation device of the friend object further includes:
  • a list similarity calculation module configured to calculate a similarity between the current scan result list and a previous scan result list; wherein the previous scan result list is a scan result list obtained by performing a broadcast information scan last time;
  • a scanning time adjustment module configured to compare the similarity with a preset upper threshold and a preset lower threshold respectively, and when the similarity is greater than the upper threshold, reduce the next broadcast information scanning The duration, when the similarity is less than the lower threshold, increasing the duration of the next broadcast information scan.
  • first user feature tag and the second user feature tag are tags that describe a personal feature of the user.
  • the recommendation device of the friend object matches the user feature tag in the local device with the user feature tag obtained by scanning, so as to filter out the user of the local device among the users of all the neighboring devices scanned.
  • Interesting objects such as hobbies and similar friends, and by setting a threshold for the number of matching successes, further screening the friends of the dating object, thereby improving the accuracy of the recommendation of the dating object, thereby improving the success rate of the friends.

Landscapes

  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Probability & Statistics with Applications (AREA)
  • Computational Linguistics (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

本发明公开了一种交友对象的推荐方法和装置。所述交友对象的推荐方法包括：读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签；将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中；统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息。采用本发明，能够提高交友对象推荐的准确率，从而提高交友的成功率。

Description

交友对象的推荐方法和装置 技术领域
本发明涉及计算机技术领域，尤其涉及一种交友对象的推荐方法和装置。
背景技术
随着科学技术的发展，现如今市面上出现越来越多的社交交友软件。为了方便用户结交新的朋友，社交交友软件中大多设有“搜索附近的人”的功能，如微信中的“摇一摇”。但是，在现有技术中，设备在运行社交交友软件中的“搜索附近的人”的功能时，只要一搜索到附近一定范围内的设备，即向用户推荐该设备所对应的用户，而并不对搜索到的设备进行区分和筛选，因此会出现交友信息冗余的现象。用户收到过多的交友对象的推荐，而无法从中挑选出与自己兴趣爱好相近的陌生人作为新朋友，因此交友对象推荐的效果差，交友的成功率低。
发明内容
本发明提出一种交友对象的推荐方法和装置，能够提高交友对象推荐的准确率，从而提高交友的成功率。
本发明提供的一种交友对象的推荐方法，具体包括：
读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签；
将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中；
统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息。
进一步地，在所述读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签之前，还包括：
采用短程无线技术进行广播信息扫描；
每当扫描到相邻设备广播的相邻设备识别码和第一用户特征标签时，获取所述相邻设备识别码和所述第一用户特征标签，并将所述相邻设备识别码和所述第一用户特征标签一一对 应地存入当前扫描结果列表中。
进一步地，所述第一用户特征标签中包括至少一个特征标签；所述第二用户特征标签中包括至少一个特征标签；
则所述将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中，具体包括：
将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相同或者相似的特征标签的个数大于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中；或者，
将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相反的特征标签的个数小于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中。
进一步地，所述数据库中还包括将相邻设备识别码存入所述数据库时的存入时间；
则所述将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中，具体包括：
将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在匹配成功时，判断所述数据库中是否存在所述相邻设备标识码；
若所述数据库中存在所述相邻设备识别码，则在判断所述数据库中的所述相邻设备识别码所对应的存入时间与当前时间之间的时间间隔小于或者等于预设的标准时间间隔时，将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间；
若所述数据库中不存在所述相邻设备识别码，则将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间。
进一步地，在所述统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息之后，还包括：
计算所述当前扫描结果列表与先前扫描结果列表之间的相似度；其中，所述先前扫描结果列表为上一次进行广播信息扫描所获得的扫描结果列表；
将所述相似度分别与预设的上限阈值和预设的下限阈值进行比较，当所述相似度大于所述上限阈值时，减小下一次进行所述广播信息扫描的持续时间，当所述相似度小于所述下限阈值时，增加下一次进行所述广播信息扫描的持续时间。
进一步地，所述第一用户特征标签和所述第二用户特征标签均为描述用户的个人特征的标签。
相应地，本发明还提供了一种交友对象的推荐装置，具体包括：
扫描结果读取模块，用于读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签；
特征标签匹配模块，用于将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中；以及，
交友对象推荐模块，用于统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息。
进一步地，所述交友对象的推荐装置，还包括：
广播信息扫描模块，用于采用短程无线技术进行广播信息扫描；以及，
扫描结果存储模块，用于每当扫描到相邻设备广播的相邻设备识别码和第一用户特征标签时，获取所述相邻设备识别码和所述第一用户特征标签，并将所述相邻设备识别码和所述第一用户特征标签一一对应地存入当前扫描结果列表中。
进一步地，所述第一用户特征标签中包括至少一个特征标签；所述第二用户特征标签中包括至少一个特征标签；
所述特征标签匹配模块，具体包括：
第一匹配单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相同或者相似的特征标签的个数大于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中；或者，
第二匹配单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相反的特征标签的个数小于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中。
进一步地，所述数据库中还包括将相邻设备识别码存入所述数据库时的存入时间；
所述特征标签匹配模块，具体包括：
相同识别码判断单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在匹配成功时，判断所述数据库中是否存在所述相邻设备标识码；
第一识别码存储单元，用于若所述数据库中存在所述相邻设备识别码，则在判断所述数据库中的所述相邻设备识别码所对应的存入时间与当前时间之间的时间间隔小于或者等于预设的标准时间间隔时，将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间；或者，
第二识别码存储单元，用于若所述数据库中不存在所述相邻设备识别码，则将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间。
进一步地，所述交友对象的推荐装置，还包括：
列表相似度计算模块，用于计算所述当前扫描结果列表与先前扫描结果列表之间的相似度；其中，所述先前扫描结果列表为上一次进行广播信息扫描所获得的扫描结果列表；以及，
扫描时间调整模块，用于将所述相似度分别与预设的上限阈值和预设的下限阈值进行比较，当所述相似度大于所述上限阈值时，减小下一次进行所述广播信息扫描的持续时间，当所述相似度小于所述下限阈值时，增加下一次进行所述广播信息扫描的持续时间。
进一步地，所述第一用户特征标签和所述第二用户特征标签均为描述用户的个人特征的标签。
实施本发明，具有如下有益效果：
本发明提供的交友对象的推荐方法及装置，通过将本地设备中的用户特征标签与扫描获得的用户特征标签进行匹配，从而在扫描到的所有相邻设备的用户中筛选出与本地设备的用户兴趣爱好等较为相近的交友对象，并且通过对匹配成功次数设置阈值，从而对交友对象进行进一步的筛选，因此能够提高交友对象推荐的准确率，从而提高交友的成功率。
附图说明
图1是本发明提供的交友对象的推荐方法的一个实施例的流程示意图；
图2是本发明提供的交友对象的推荐方法的一个实施例中的一个本地设备的运行过程的示意图；
图3是本发明提供的交友对象的推荐装置的一个实施例的结构示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
参见图1，是本发明提供的交友对象的推荐方法的一个实施例的流程示意图，包括步骤S11至S13，具体如下：
S11：读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备 识别码和相对应的第一用户特征标签；
S12：将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中；
S13：统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息。
需要说明的是，本发明实施例提供的交友对象的推荐方法由本地设备执行。在本发明实施例中，本地设备采用短程无线技术(特别地，该短程无线技术为BLE技术)对周围一定范围内的其他设备广播的用户特征标签进行扫描和获取，并将本地设备上的用户特征标签和扫描获得的用户特征标签进行匹配判断，从而将匹配成功次数达到一定阈值的设备所对应的用户推荐给本地设备的用户。
在一个优选的实施方式中，本地设备的用户预先将描述自身特征(如：年龄、祖籍、兴趣爱好等)的第二用户特征标签存储于本地中。本地设备在扫描获得周围一定范围内的相邻设备所广播的相邻设备识别码和相对应的第一用户特征标签之后，将扫描获得的相邻设备识别码和第一用户特征标签作为扫描结果相互一一对应地存入当前扫描结果列表中。其中，相邻设备识别码可以为相邻设备的MAC地址。随后，本地设备从该当前扫描结果列表中读取各个扫描结果，从而获得每个扫描结果中的相邻设备识别码和相对应的第一用户特征标签。随后，本地设备将各个扫描结果中的第一用户特征标签分别与存储于本地的第二用户特征标签进行匹配并分别判断是否匹配成功，若匹配成功，则将该第一用户特征标签所对应的相邻设备识别码存入数据库中，否则，不作处理。特别地，该匹配过程还可以在云端服务器中完成。本地设备将从当前扫描结果列表中读取的各个扫描结果和本机设备识别码以及存储于本地的第二用户特征标签上传至云端服务器中，使云端服务器对第一用户特征标签和第二用户特征标签进行匹配判断，并将匹配判断结果返回至本地设备。其中，本机设备识别码可以为本地设备的MAC地址。最后，本地设备根据各个存入数据库中的相邻设备识别码，分别统计每个相邻设备识别码在该数据库中出现的次数，并将各个统计获得的次数与预先设置的阈值进行对比判断，若其中某一相邻设备识别码出现的次数大于该阈值，则生成推荐该相邻设备识别码所对应的相邻设备的用户的推荐信息，并提醒本地设备的用户找到了交友对象，其中，提醒的方式可以是向用户推送该推荐信息，也可以是本地设备本身震动、闪灯等等。
需要进一步说明的是，本地设备通过采用短程无线技术将本机设备识别码和本地存储的第二用户特征标签对外进行持续时间为T1的广播后，采用短程无线技术对周围一定范围内的其他设备广播的相邻设备识别码和相对应的第一用户特征标签进行持续时间为T2的扫描，并在扫描结束后，对扫描获得的扫描结果进行处理，依此循环。如图2所示，为一个本地设备 的运行过程的示意图。当本地设备没有扫描到其他设备广播的相邻设备识别码和相对应的第一用户特征标签时，或者当所有扫描获得的第一用户特征标签与存储于本地的第二用户特征标签均无法匹配时，或者当所有存入数据库中的相邻设备识别码在数据库中出现的次数均未达到预设的阈值时，比较当前扫描结果列表和先前扫描结果列表，并根据比较结果调整T1和T2的值。其中，当前扫描结果列表通过本地设备本次对周围一定范围内的其他设备所广播的信息进行扫描获得，先前扫描结果列表通过本地设备上一次对周围一定范围内的其他设备所广播的信息进行扫描获得。
通过将本地设备中的用户特征标签与扫描获得的用户特征标签进行匹配，从而在扫描到的所有相邻设备的用户中筛选出与本地设备的用户兴趣爱好等较为相近的交友对象，并且通过对匹配成功次数设置阈值，从而对交友对象进行进一步的筛选，因此能够提高交友对象推荐的准确率，从而提高交友的成功率。
进一步地，在所述读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签之前，还包括：
采用短程无线技术进行广播信息扫描；
每当扫描到相邻设备广播的相邻设备识别码和第一用户特征标签时，获取所述相邻设备识别码和所述第一用户特征标签，并将所述相邻设备识别码和所述第一用户特征标签一一对应地存入当前扫描结果列表中。
需要说明的是，在从当前扫描列表中读取扫描结果并进行匹配判断之前，本地设备采用短程无线技术(特别地，该短程无线技术为BLE技术)对周围一定范围内的其他设备所广播的信息进行扫描，每当扫描到某一相邻设备广播的相邻设备识别码和相对应的第一用户特征标签时，获取该相邻设备识别码和相对应的第一用户特征标签，并将获得的相邻设备识别码和第一用户特征标签作为扫描结果相互一一对应地存入当前扫描结果列表中。
进一步地，所述第一用户特征标签中包括至少一个特征标签；所述第二用户特征标签中包括至少一个特征标签；
则所述将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中，具体包括：
将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相同或者相似的特征标签的个数大于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中；或者，
将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相反的特征标签的个数小于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中。
需要说明的是，第一用户特征标签中和第二用户特征标签中均包括至少一个特征标签。本地设备在将获得的第一用户特征标签和存储于本地的第二用户特征标签进行匹配，可以通过统计第一用户特征标签与第二用户特征标签之间的相同(如：“喜欢篮球”和“喜欢篮球”)或者相似(如：“喜欢篮球”和“喜欢NBA”)的特征标签的个数，并将该相同或者相似的特征标签的个数与预设的阈值进行比较判断来实现，也可以通过统计第一用户特征标签与第二用户特征标签之间的相反(如：“喜欢吃肉”和“素食主义者”)的特征标签的个数，并将该相反的特征标签的个数与预设的阈值进行比较判断来实现。若该相同或者相似的特征标签的个数大于预设的阈值，或者该相反的特征标签的个数小于预设的阈值，则确定匹配结果为匹配成功，并将与该第一用户特征标签相对应的相邻设备识别码存入数据库中。
特别地，在将相邻设备识别码存入数据库的同时，还可以将本地设备的当前位置和当前时间等信息相对应地存入数据库。其中，本地设备的当前位置可以通过本地的GPS模块获得，也可以通过与其他能够获得当前位置的智能设备进行蓝牙通讯等通讯获得。
进一步地，所述数据库中还包括将相邻设备识别码存入所述数据库时的存入时间；
则所述将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中，具体包括：
将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在匹配成功时，判断所述数据库中是否存在所述相邻设备标识码；
若所述数据库中存在所述相邻设备识别码，则在判断所述数据库中的所述相邻设备识别码所对应的存入时间与当前时间之间的时间间隔小于或者等于预设的标准时间间隔时，将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间；
若所述数据库中不存在所述相邻设备识别码，则将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间。
需要说明的是，本地设备在将匹配成功的相邻设备识别码存入数据库时，在数据库中对应地生成该相邻设备识别码的存入时间。本地设备在将某一第一用户特征标签和存储于本地的第二用户特征标签进行匹配且匹配成功时，判断数据库中是否存在该第一用户特征标签所对应的相邻设备识别码，若存在，则判断存储于该数据库中的该相邻设备识别码所对应的存入时间与当前时间之间的时间间隔是否小于或者等于预设的标准时间间隔，若是，则认为本 地设备本次扫描所得的扫描结果为一个新的扫描结果，并将该相邻设备识别码存入数据库中，同时生成相对应的存入时间，若否，则不作处理。若数据库中不存在该第一用户特征标签所对应的相邻设备识别码，则直接将该第一用户特征标签所对应的相邻设备识别码存入数据库中，并生成相对应的存入时间。
通过在将相邻设备识别码等相邻设备的信息存入数据库之前，对数据库中的该相邻设备识别码的记录进行查询，从而使得在较短时间内的相同的相邻设备的记录不会被重复地存入数据库，保证了数据的准确性，进而能够进一步提高交友对象推荐的准确率。
在另一个优选地实施方式中，在所述统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息之后，还包括：
计算所述当前扫描结果列表与先前扫描结果列表之间的相似度；其中，所述先前扫描结果列表为上一次进行广播信息扫描所获得的扫描结果列表；
将所述相似度分别与预设的上限阈值和预设的下限阈值进行比较，当所述相似度大于所述上限阈值时，减小下一次进行所述广播信息扫描的持续时间，当所述相似度小于所述下限阈值时，增加下一次进行所述广播信息扫描的持续时间。
需要说明的是，本地设备在完成本次匹配判断并生成相应的推荐信息后，计算当前扫描结果列表与先前扫描结果列表之间的相似度，并将计算获得的相似度分别与预设的上限阈值和预设的下限阈值进行比较，若该相似度比上限阈值大，则认为本次扫描所得的扫描结果与上一次扫描所得的扫描结果差别较小，本地设备处于人群流动性较小的地点，因此适当减小下一次进行广播信息扫描的持续时间；若该相似度比下限阈值小，则认为本次扫描所得的扫描结果与上一次扫描所得的扫描结果差别较大，本地设备处于人群流动性较大的地点，因此适当增大下一次进行广播信息扫描的持续时间。
进一步地，所述第一用户特征标签和所述第二用户特征标签均为描述用户的个人特征的标签。
需要说明的是，第一用户特征标签和第二用户特征标签中的特征标签均为描述用户的个人特征(如：年龄、祖籍、兴趣爱好等)的标签。
本发明实施例提供的交友对象的推荐方法，通过将本地设备中的用户特征标签与扫描获得的用户特征标签进行匹配，从而在扫描到的所有相邻设备的用户中筛选出与本地设备的用户兴趣爱好等较为相近的交友对象，并且通过对匹配成功次数设置阈值，从而对交友对象进 行进一步的筛选，因此能够提高交友对象推荐的准确率，从而提高交友的成功率。另外，通过在将相邻设备识别码等相邻设备的信息存入数据库之前，对数据库中的该相邻设备识别码的记录进行查询，从而使得在较短时间内的相同的相邻设备的记录不会被重复地存入数据库，保证了数据的准确性，进而能够进一步提高交友对象推荐的准确率。
相应地，本发明还提供一种交友对象的推荐装置，能够实现上述实施例中的交友对象的推荐方法的所有流程。
参见图3，是本发明提供的交友对象的推荐装置的一个实施例的结构示意图，具体如下：
扫描结果读取模块31，用于读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签；
特征标签匹配模块32，用于将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中；以及，
交友对象推荐模块33，用于统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息。
进一步地，所述交友对象的推荐装置，还包括：
广播信息扫描模块，用于采用短程无线技术进行广播信息扫描；以及，
扫描结果存储模块，用于每当扫描到相邻设备广播的相邻设备识别码和第一用户特征标签时，获取所述相邻设备识别码和所述第一用户特征标签，并将所述相邻设备识别码和所述第一用户特征标签一一对应地存入当前扫描结果列表中。
进一步地，所述第一用户特征标签中包括至少一个特征标签；所述第二用户特征标签中包括至少一个特征标签；
所述特征标签匹配模块32，具体包括：
第一匹配单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相同或者相似的特征标签的个数大于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中；或者，
第二匹配单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相反的特征标签的个数小于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中。
进一步地，所述数据库中还包括将相邻设备识别码存入所述数据库时的存入时间；
所述特征标签匹配模块32，具体包括：
相同识别码判断单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在匹配成功时，判断所述数据库中是否存在所述相邻设备标识码；
第一识别码存储单元，用于若所述数据库中存在所述相邻设备识别码，则在判断所述数据库中的所述相邻设备识别码所对应的存入时间与当前时间之间的时间间隔小于或者等于预设的标准时间间隔时，将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间；或者，
第二识别码存储单元，用于若所述数据库中不存在所述相邻设备识别码，则将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间。
在另一个优选地实施方式中，所述交友对象的推荐装置，还包括：
列表相似度计算模块，用于计算所述当前扫描结果列表与先前扫描结果列表之间的相似度；其中，所述先前扫描结果列表为上一次进行广播信息扫描所获得的扫描结果列表；以及，
扫描时间调整模块，用于将所述相似度分别与预设的上限阈值和预设的下限阈值进行比较，当所述相似度大于所述上限阈值时，减小下一次进行所述广播信息扫描的持续时间，当所述相似度小于所述下限阈值时，增加下一次进行所述广播信息扫描的持续时间。
进一步地，所述第一用户特征标签和所述第二用户特征标签均为描述用户的个人特征的标签。
本发明实施例提供的交友对象的推荐装置，通过将本地设备中的用户特征标签与扫描获得的用户特征标签进行匹配，从而在扫描到的所有相邻设备的用户中筛选出与本地设备的用户兴趣爱好等较为相近的交友对象，并且通过对匹配成功次数设置阈值，从而对交友对象进行进一步的筛选，因此能够提高交友对象推荐的准确率，从而提高交友的成功率。另外，通过在将相邻设备识别码等相邻设备的信息存入数据库之前，对数据库中的该相邻设备识别码的记录进行查询，从而使得在较短时间内的相同的相邻设备的记录不会被重复地存入数据库，保证了数据的准确性，进而能够进一步提高交友对象推荐的准确率。
以上所述是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以作出若干改进和润饰，这些改进和润饰也视为本发明的保护范围。

Claims (12)

  1. 一种交友对象的推荐方法，其特征在于，包括：
    读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签；
    将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中；
    统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息。
  2. 如权利要求1所述的交友对象的推荐方法，其特征在于，在所述读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签之前，还包括：
    采用短程无线技术进行广播信息扫描；
    每当扫描到相邻设备广播的相邻设备识别码和第一用户特征标签时，获取所述相邻设备识别码和所述第一用户特征标签，并将所述相邻设备识别码和所述第一用户特征标签一一对应地存入当前扫描结果列表中。
  3. 如权利要求1所述的交友对象的推荐方法，其特征在于，所述第一用户特征标签中包括至少一个特征标签；所述第二用户特征标签中包括至少一个特征标签；
    则所述将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中，具体包括：
    将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相同或者相似的特征标签的个数大于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中；或者，
    将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相反的特征标签的个数小于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中。
  4. 如权利要求1所述的交友对象的推荐方法，其特征在于，所述数据库中还包括将相邻设备识别码存入所述数据库时的存入时间；
    则所述将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在 匹配成功时，将所述相邻设备识别码存入数据库中，具体包括：
    将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在匹配成功时，判断所述数据库中是否存在所述相邻设备标识码；
    若所述数据库中存在所述相邻设备识别码，则在判断所述数据库中的所述相邻设备识别码所对应的存入时间与当前时间之间的时间间隔小于或者等于预设的标准时间间隔时，将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间；
    若所述数据库中不存在所述相邻设备识别码，则将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间。
  5. 如权利要求1所述的交友对象的推荐方法，其特征在于，在所述统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息之后，还包括：
    计算所述当前扫描结果列表与先前扫描结果列表之间的相似度；其中，所述先前扫描结果列表为上一次进行广播信息扫描所获得的扫描结果列表；
    将所述相似度分别与预设的上限阈值和预设的下限阈值进行比较，当所述相似度大于所述上限阈值时，减小下一次进行所述广播信息扫描的持续时间，当所述相似度小于所述下限阈值时，增加下一次进行所述广播信息扫描的持续时间。
  6. 如权利要求1至5中任一项所述的交友对象的推荐方法，其特征在于，所述第一用户特征标签和所述第二用户特征标签均为描述用户的个人特征的标签。
  7. 一种交友对象的推荐装置，其特征在于，包括：
    扫描结果读取模块，用于读取当前扫描结果列表中的扫描结果，以获取每个所述扫描结果中包含的相邻设备识别码和相对应的第一用户特征标签；
    特征标签匹配模块，用于将所述第一用户特征标签与预先存储于本地的第二用户特征标签进行匹配，并在匹配成功时，将所述相邻设备识别码存入数据库中；以及，
    交友对象推荐模块，用于统计所述数据库中的所述相邻设备识别码出现的次数，当所述出现的次数大于预设的阈值时，生成推荐所述相邻设备识别码所对应的相邻设备的用户的推荐信息。
  8. 如权利要求7所述的交友对象的推荐装置，其特征在于，所述交友对象的推荐装置， 还包括：
    广播信息扫描模块，用于采用短程无线技术进行广播信息扫描；以及，
    扫描结果存储模块，用于每当扫描到相邻设备广播的相邻设备识别码和第一用户特征标签时，获取所述相邻设备识别码和所述第一用户特征标签，并将所述相邻设备识别码和所述第一用户特征标签一一对应地存入当前扫描结果列表中。
  9. 如权利要求7所述的交友对象的推荐装置，其特征在于，所述第一用户特征标签中包括至少一个特征标签；所述第二用户特征标签中包括至少一个特征标签；
    所述特征标签匹配模块，具体包括：
    第一匹配单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相同或者相似的特征标签的个数大于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中；或者，
    第二匹配单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在当所述第一用户特征标签与所述第二用户特征标签之间的相反的特征标签的个数小于预设的阈值时，确定匹配成功，并将所述相邻设备识别码存入所述数据库中。
  10. 如权利要求7所述的交友对象的推荐装置，其特征在于，所述数据库中还包括将相邻设备识别码存入所述数据库时的存入时间；
    所述特征标签匹配模块，具体包括：
    相同识别码判断单元，用于将所述第一用户特征标签与所述第二用户特征标签进行匹配，并在匹配成功时，判断所述数据库中是否存在所述相邻设备标识码；
    第一识别码存储单元，用于若所述数据库中存在所述相邻设备识别码，则在判断所述数据库中的所述相邻设备识别码所对应的存入时间与当前时间之间的时间间隔小于或者等于预设的标准时间间隔时，将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间；或者，
    第二识别码存储单元，用于若所述数据库中不存在所述相邻设备识别码，则将所述相邻设备识别码存入所述数据库中，并生成相应的存入时间。
  11. 如权利要求7所述的交友对象的推荐装置，其特征在于，所述交友对象的推荐装置，还包括：
    列表相似度计算模块，用于计算所述当前扫描结果列表与先前扫描结果列表之间的相似 度；其中，所述先前扫描结果列表为上一次进行广播信息扫描所获得的扫描结果列表；以及，
    扫描时间调整模块，用于将所述相似度分别与预设的上限阈值和预设的下限阈值进行比较，当所述相似度大于所述上限阈值时，减小下一次进行所述广播信息扫描的持续时间，当所述相似度小于所述下限阈值时，增加下一次进行所述广播信息扫描的持续时间。
  12. 如权利要求7至11中任一项所述的交友对象的推荐装置，其特征在于，所述第一用户特征标签和所述第二用户特征标签均为描述用户的个人特征的标签。
PCT/CN2016/113615 2016-10-19 2016-12-30 交友对象的推荐方法和装置 Ceased WO2018072335A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201610910504.6 2016-10-19
CN201610910504.6A CN106503122B (zh) 2016-10-19 2016-10-19 交友对象的推荐方法和装置

Publications (1)

Publication Number Publication Date
WO2018072335A1 true WO2018072335A1 (zh) 2018-04-26

Family

ID=58294221

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2016/113615 Ceased WO2018072335A1 (zh) 2016-10-19 2016-12-30 交友对象的推荐方法和装置

Country Status (2)

Country Link
CN (1) CN106503122B (zh)
WO (1) WO2018072335A1 (zh)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116834021A (zh) * 2023-08-16 2023-10-03 三星电子（中国）研发中心 由电子装置执行的机器人控制方法和电子装置
CN117150149A (zh) * 2023-10-26 2023-12-01 深圳市玺佳创新有限公司 一种线下近距离交友的方法、装置、物联手表和介质

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107316250A (zh) * 2017-07-20 2017-11-03 佛山潮伊汇服装有限公司 社交推荐方法及移动终端
CN109857927A (zh) * 2018-12-24 2019-06-07 深圳市珍爱捷云信息技术有限公司 用户推荐方法、装置、计算机设备及计算机可读存储介质
CN109816545A (zh) * 2019-03-26 2019-05-28 长安大学 一种校园交友系统及方法
US20250209458A1 (en) * 2023-12-21 2025-06-26 The Pnc Financial Services Group, Inc. Secret code system for correspondence identity verification

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101446961A (zh) * 2008-12-24 2009-06-03 腾讯科技（深圳）有限公司 在网络社区中对用户及其好友进行关联的方法及系统
CN103365913A (zh) * 2012-04-09 2013-10-23 腾讯科技（深圳）有限公司 一种搜索结果排序方法和装置
CN103581270A (zh) * 2012-08-08 2014-02-12 腾讯科技（深圳）有限公司 用户推荐方法和系统
CN105931123A (zh) * 2016-05-09 2016-09-07 深圳市永兴元科技有限公司 基于网络账号的好友推荐方法及装置

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103810192A (zh) * 2012-11-09 2014-05-21 腾讯科技（深圳）有限公司 一种用户的兴趣推荐方法和装置
CN103984972A (zh) * 2014-06-06 2014-08-13 重庆中陆承大科技有限公司 产品信息获取方法及装置和电子标签编码获取方法
US20160248864A1 (en) * 2014-11-19 2016-08-25 Unravel, Llc Social networking games including image unlocking and bi-directional profile matching

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101446961A (zh) * 2008-12-24 2009-06-03 腾讯科技（深圳）有限公司 在网络社区中对用户及其好友进行关联的方法及系统
CN103365913A (zh) * 2012-04-09 2013-10-23 腾讯科技（深圳）有限公司 一种搜索结果排序方法和装置
CN103581270A (zh) * 2012-08-08 2014-02-12 腾讯科技（深圳）有限公司 用户推荐方法和系统
CN105931123A (zh) * 2016-05-09 2016-09-07 深圳市永兴元科技有限公司 基于网络账号的好友推荐方法及装置

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116834021A (zh) * 2023-08-16 2023-10-03 三星电子（中国）研发中心 由电子装置执行的机器人控制方法和电子装置
CN117150149A (zh) * 2023-10-26 2023-12-01 深圳市玺佳创新有限公司 一种线下近距离交友的方法、装置、物联手表和介质
CN117150149B (zh) * 2023-10-26 2024-01-26 深圳市玺佳创新有限公司 一种线下近距离交友的方法、装置、物联手表和介质

Also Published As

Publication number Publication date
CN106503122B (zh) 2020-02-28
CN106503122A (zh) 2017-03-15

Similar Documents

Publication Publication Date Title
WO2018072335A1 (zh) 交友对象的推荐方法和装置
US11914639B2 (en) Multimedia resource matching method and apparatus, storage medium, and electronic apparatus
US11514716B2 (en) Face matching method and apparatus, storage medium
US9367756B2 (en) Selection of representative images
KR102038214B1 (ko) 계정 정보 획득 방법, 단말기, 서버 및 시스템
CN104239566B (zh) 视频搜索的方法及装置
US20210026883A1 (en) Image-to-image search method, computer-readable storage medium and server
CN108540755B (zh) 身份识别方法和装置
US20150193472A1 (en) Generating user insights from user images and other data
US20110243449A1 (en) Method and apparatus for object identification within a media file using device identification
CN107480236A (zh) 一种信息查询方法、装置、设备和介质
KR20130139338A (ko) 얼굴 인식
CN103577421A (zh) 一种应用二维码的方法、设备和系统
WO2020082831A1 (zh) 一种基于人脸的身份识别方法、装置及电子设备
CN111126457A (zh) 信息的获取方法和装置、存储介质和电子装置
CN111259200A (zh) 视频类别划分方法、装置、电子设备及存储介质
CN106910135A (zh) 用户推荐方法及装置
CN111797746B (zh) 人脸识别方法、装置及计算机可读存储介质
CN107526735B (zh) 一种关联关系的识别方法及装置
CN111966862A (zh) 基于虚拟现实的推送方法、装置、vr设备及存储介质
CN108024148B (zh) 基于行为特征的多媒体文件识别方法、处理方法及装置
CN108848404B (zh) 移动终端的二维码信息共享系统
US20230188776A1 (en) Information pushing method and apparatus
CN110413817B (zh) 用于对图片进行聚类的方法和设备
CN105095343A (zh) 信息处理方法、信息显示方法及装置

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: 16919118

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16919118

Country of ref document: EP

Kind code of ref document: A1