CN106709750B - User recommendation method and device - Google Patents
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Abstract
The embodiment of the invention discloses a user recommendation method and device, which are applied to the technical field of network information. In the method of this embodiment, a server in the user recommendation system may obtain, according to a user binding information base, a plurality of second users that match with the information of the plurality of dimensions of the first user, and select a recommended user for the first user according to matching degrees corresponding to the plurality of second users. Compared with the prior art that single-dimensional information is adopted for user recommendation, the user recommended in the embodiment can cover multiple aspects of information of the user to be recommended (namely the first user), so that the requirements of the user can be met as much as possible; and the user binding information base comprises the user real name information of each user, so that the accuracy of the finally obtained recommended user is higher.
Description
Technical Field
The invention relates to the technical field of network information, in particular to a user recommendation method and device.
Background
At present, many applications have a user recommendation function, generally, the user recommendation function is to perform user recommendation according to information of other users associated with one user account or information of a user group, so that information of other users recommended for a certain user is relatively limited, and sometimes, the recommended information of other users is not desired to be searched by the user.
Disclosure of Invention
The embodiment of the invention provides a user recommendation method and device, which can be used for recommending information of other users for a certain user according to information of multiple dimensions.
The embodiment of the invention provides a user recommendation method, which comprises the following steps:
acquiring at least one of the following matching information: the method comprises the following steps that registration information of a first user, information of other users bound with the first user, query information of the first user and recent operation information of the first user are obtained;
searching a plurality of second users matched with the at least one piece of matching information according to a preset user binding information base; the user binding information base comprises registration information of each user in a plurality of users, and the registration information comprises real-name information of the users;
respectively calculating the matching degree of each second user in the plurality of second users and the at least one piece of matching information;
and selecting a recommended user of the first user from the plurality of second users according to the calculated matching degree and outputting the recommended user to the client of the first user.
An embodiment of the present invention further provides a user recommendation apparatus, including:
an information acquisition unit configured to acquire at least one of the following matching information: the method comprises the following steps that registration information of a first user, information of other users bound with the first user, query information of the first user and recent operation information of the first user are obtained;
the user searching unit is used for searching a plurality of second users matched with the at least one piece of matching information acquired by the information acquiring unit according to a preset user binding information base; the user binding information base comprises registration information of each user in a plurality of users, and the registration information comprises real-name information of the users;
a calculating unit, configured to calculate a matching degree between each of the plurality of second users and the at least one piece of matching information;
and the user recommending unit is used for selecting the recommended user of the first user from the plurality of second users according to the matching degree calculated by the calculating unit and outputting the recommended user to the client of the first user.
As can be seen, in the method of this embodiment, the server in the user recommendation system obtains, according to the user binding information base, a plurality of second users that match the information of the plurality of dimensions of the first user, and selects a recommended user for the first user according to the matching degrees corresponding to the plurality of second users. Compared with the prior art that single-dimensional information is adopted for user recommendation, the user recommended in the embodiment can cover multiple aspects of information of the user to be recommended (namely the first user), so that the requirements of the user can be met as much as possible; and the user binding information base comprises the user real name information of each user, so that the accuracy of the finally obtained recommended user is higher.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of a user recommendation method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a user recommendation device according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of another user recommendation device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of another user recommendation device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
An embodiment of the present invention provides a user recommendation method, which is mainly applied to a user recommendation system (such as a social relationship platform, a car pooling service system, or an online-offline transaction system, etc.), where the user recommendation system may include a client and a server, the method of the embodiment is a method executed by the server in the user recommendation system, and a flowchart is shown in fig. 1, and includes:
The other user information bound with the first user refers to other user information which is stored in a server of the user recommendation system and corresponds to the registration information of the first user; the query information of the first user refers to information included in a user recommendation request sent to the server by the client of the first user, for example, the user recommendation request is to request to recommend owner information of a vehicle whose destination is south mountain, and the query information may include owner information of a vehicle whose destination is south mountain, and the like.
The recent operation information of the first user refers to information that the first user operates information of other users within a recent preset time (such as within a week or a day) and the like, which are stored in a server of the user recommendation system, for example, for a car sharing service, the recent operation information may be owner information and the like that the first user recently enjoys the car sharing service.
When a user (e.g., a first user) needs the user recommendation system to perform user recommendation, a user recommendation interface provided by a client in the user recommendation system, such as a user recommendation interface, a user query interface, or an information query interface, may be triggered by the first user, so that a server in the user recommendation system may receive a user recommendation request sent by the client of the first user, so as to trigger the process of this embodiment. Or the server may directly actively trigger the flow of the embodiment, instead of being passively triggered by the user recommendation request sent by the client.
The user binding information base may further include information such as recent operation information of the user, where the recent operation information of the user refers to information that the user operates information of other users within a recent preset time (for example, within a week or a day). The user real name information may include the identity card information of the user, and specifically may include information such as an identity card number, a name, an age, a place of the user's mouth, and the like. The registration information may further include: user preferences, user signatures, user account information, and the like.
It can be understood that any user may store the registration information of the user in the server of the user recommendation system by the registration method, specifically, in the process of user registration, the server of the user recommendation system may provide an interface for user registration to the client, where the interface includes an input interface of the registration information of the user, so that the user may input the registration information to the interface and submit the registration information to the server of the user recommendation system; after receiving a registration request of a user sent by a client of the user, a server includes at least one registration message in the registration request, wherein the registration message includes real name information of the user; the server needs to authenticate the real-name information of the user, for example, check whether the identification number and the name correspond to each other, and if the authentication is passed, the server stores at least one registration information of the user. It should be noted that, during the process of registering the user in the server, the user may input part of the registration information into the user registration interface provided by the server and submit the registration information to the server for storage, and then the user may add and modify the registration information stored in the server.
And 103, respectively calculating the matching degree of each second user in the plurality of second users and at least one piece of matching information by the server.
For the matching degree corresponding to a certain second user, if the certain second user is matched with more than two pieces of matching information, when the server calculates the matching degree of the certain second user, the server may use the sum of matching values of the certain second user respectively matched with the more than two pieces of matching information as the matching degree of the second user; or, the mathematical calculation value of the weighted value of the matching value of the certain second user respectively matched with the two or more pieces of matching information is used as the matching degree of the second user.
The matching value of the second user matching with a certain matching information may be set according to actual needs, for example, according to the importance of a certain matching information in all matching information, the matching value matching with the matching information may be set to be higher.
And step 104, the server selects a recommended user of the first user from the plurality of second users according to the matching degree calculated in the step 103 and outputs the recommended user to the client of the first user, namely, the recommended user and the information of the recommended user are sent to the client corresponding to the first user for display. Specifically, the server may select at least one of the plurality of second users with a higher matching degree as the recommended user.
Further, after the server in the user recommendation system recommends a user for the first user and displays the recommended user to the client of the first user, the first user may select one of the users to perform an actual operation, such as adding a certain recommended user as a bound user of the first user, or selecting and dialing out a telephone of the certain recommended user, and the like, and when the server in the user recommendation system receives information sent by the client of the first user and indicating that the first user operates the information of the certain recommended user among the recommended users, the operation information of the certain recommended user and the registration information of the first user may be correspondingly stored. It is convenient to recommend the first user for other users later.
For example: in the car-sharing service system, a user selects and queries car-sharing information with Shenzhen nan shan as a destination through a client, and submits the car-sharing information to a server, namely the client sends a user recommendation request to the server, and the user recommendation request comprises query information; after the server receives the user recommendation request, the server finds that no relevant owner information exists, other users matched with at least one piece of matching information are found according to a user binding information base preset in the server, for example, the server finds a user who uses the car-sharing service, the real-name account address is a user in Shenzhen south mountain, a user who recently uses the car-sharing service to south mountain and the like as users to be recommended, the matching degrees corresponding to the users are calculated, and a plurality of recommended users are displayed to clients of the users. Therefore, the carpooling information does not need to be issued in the carpooling service system, and the users needed by the users can be recommended to the client.
As can be seen, in the method of this embodiment, the server in the user recommendation system obtains, according to the user binding information base, a plurality of second users that match the information of the plurality of dimensions of the first user, and selects a recommended user for the first user according to the matching degrees corresponding to the plurality of second users. Compared with the prior art that single-dimensional information is adopted for user recommendation, the user recommended in the embodiment can cover multiple aspects of information of the user to be recommended (namely the first user), so that the requirements of the user can be met as much as possible; and the user binding information base comprises the user real name information of each user, so that the accuracy of the finally obtained recommended user is higher.
An embodiment of the present invention further provides a user recommendation device, a schematic structural diagram of which is shown in fig. 2, and the user recommendation device may specifically include:
an information obtaining unit 10, configured to obtain at least one of the following matching information: the method comprises the steps of registering information of a first user, information of other users bound with the first user, query information of the first user and recent operation information of the first user.
The information obtaining unit 10 may actively initiate a user recommendation process, or directly obtain the user binding information base after receiving a user recommendation request sent by the client of the first user.
And the user searching unit 11 is configured to search, according to a preset user binding information base, a plurality of second users matched with the at least one piece of matching information acquired by the information acquiring unit 10. Specifically, the user search unit 11 may match information in the user binding information base with at least one matching information, and regard a user corresponding to the information matched with the at least one matching information as the second user. The user binding information base comprises registration information of each user in a plurality of users, the registration information comprises user real-name information, the user binding information base also comprises recent operation information of the user and the like, and the user real-name information comprises identity card information of the user.
A calculating unit 12, configured to calculate a matching degree between each of the plurality of second users searched by the user searching unit 11 and the at least one piece of matching information.
For the matching degree corresponding to a certain second user, if the certain second user matches with more than two pieces of matching information, the calculating unit 12 may, specifically, when calculating the matching degree of the certain second user, use the sum of matching values of the certain second user matching with the more than two pieces of matching information respectively as the matching degree of the second user; or, the calculating unit 12 is specifically configured to use a mathematical calculation value of a weighted value of a matching value that the certain second user matches with more than two pieces of matching information, as the matching degree of the second user.
The matching value of the second user matching with a certain matching information may be set according to actual needs, for example, according to the importance of a certain matching information in all matching information, the matching value matching with the matching information may be set to be higher.
And the user recommending unit 13 is configured to select a recommended user of the first user from the plurality of second users according to the matching degree calculated by the calculating unit 12, and output the recommended user to the client of the first user. The user recommending unit 13 may select at least one second user with a higher matching degree from the plurality of second users as the recommending user.
As can be seen, in the user recommendation apparatus in this embodiment, the user searching unit 11 obtains a plurality of second users matched with the information of the plurality of dimensions of the first user according to the preset user binding information base, and the user recommendation unit 13 selects a recommended user for the first user according to the matching degrees corresponding to the plurality of second users. Compared with the prior art that single-dimensional information is adopted for user recommendation, the user recommended in the embodiment can cover multiple aspects of information of the user to be recommended (namely the first user), so that the requirements of the user can be met as much as possible; and the user binding information base comprises the user real name information of each user, so that the accuracy of the finally obtained recommended user is higher.
Referring to fig. 3, in a specific embodiment, the user recommendation device may further include an operation storage unit 14, a request receiving unit 15 and a registration unit 16, in addition to the structure shown in fig. 2, specifically:
and an operation storage unit 14, configured to receive information that is sent by the client of the first user and that the first user operates information of a certain recommended user among the recommended users, and store operation information of the certain recommended user and registration information of the first user in a corresponding manner.
A request receiving unit 15, configured to receive a registration request of a user sent by a client of the user, where the registration request includes at least one registration information of the user, where the registration information includes user real-name information;
and the registration unit 16 is used for authenticating the real-name information of the user, and storing at least one registration information of the user if the authentication is passed.
In this embodiment, the request receiving unit 15 and the registering unit 16 may store the real-name information of the user in the user recommending apparatus, so that the information acquiring unit 10 may acquire the real-name information from the information registered by the registering unit 16; in this embodiment, after the user recommending unit 13 selects a recommending user for the first user, the recommending user can be sent to the client of the first user for display, so that the first user can operate information of a certain recommending user through the client, and when the operation storing unit 14 receives the information for operating the information of a certain recommending user, the information is stored, so that the first user can be conveniently recommended to other users.
The embodiment of the present invention further provides a user recommendation apparatus, a schematic structural diagram of which is shown in fig. 4, the user recommendation apparatus may generate relatively large differences due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 20 (e.g., one or more processors) and a memory 21, and one or more storage media 22 (e.g., one or more mass storage devices) storing the application programs 221 or the data 222. Wherein the memory 21 and the storage medium 22 may be a transient storage or a persistent storage. The program stored on the storage medium 22 may include one or more modules (not shown), each of which may include a sequence of instruction operations for the user recommendation device. Still further, the central processor 30 may be configured to communicate with the storage medium 22 to execute a series of instructional operations on the storage medium 22 on the user recommendation device.
The user recommendation device may also include one or more power supplies 23, one or more wired or wireless network interfaces 24, one or more input-output interfaces 25, and/or one or more operating systems 223, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and the like.
The steps executed by the server in the user recommendation system in the above method embodiment may be based on the structure of the user recommendation device shown in fig. 4.
The embodiment of the present invention may also provide a user recommendation system, which mainly includes a server and a client, where the structure of the server may be the structure of the user recommendation device shown in any one of fig. 2 to fig. 4, which is not described herein again. The client is mainly a client of the first user, and may send the user recommendation request to the server, may also send information that the first user operates on information of a certain recommended user among the recommended users and a registration request of the first user to the server, and may also receive the recommended user selected by the first user and output by the server.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
The user recommendation method and device provided by the embodiment of the invention are described in detail above, a specific example is applied in the text to explain the principle and the implementation of the invention, and the description of the above embodiment is only used to help understanding the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A user recommendation method, comprising:
when a server of a user recommendation system receives a user recommendation request sent by a client of a first user, acquiring a plurality of matching information: the first user registration information, other user information bound with the first user, the first user query information, and the first user recent operation information, wherein the first user query information refers to information included in a user recommendation request sent to the server by a client of the first user, and the first user recent operation information refers to information stored in the server and used by the first user to operate the other user information within a recent preset time;
searching a plurality of second users matched with the plurality of matching information according to a preset user binding information base; the second user is a part of users except the first user in the user binding information base, the user binding information base comprises registration information of each user in a plurality of users, and the registration information comprises user real name information; the user real name information comprises identity card information of a user;
respectively calculating the matching degree of each second user in the plurality of second users and the plurality of matching information;
and selecting a recommended user of the first user from the plurality of second users according to the calculated matching degree and outputting the recommended user to the client of the first user.
2. The method according to claim 1, wherein if a second user matches with more than two matching information, calculating a matching degree of the second user with the more than two matching information includes:
taking the sum of the matching values of the certain second user respectively matched with more than two pieces of matching information as the matching degree of the certain second user;
or, taking a mathematical calculation value of a weighted value of a matching value of the certain second user and the more than two matching information as the matching degree of the certain second user.
3. The method of claim 1, wherein the method further comprises:
and receiving information, sent by the client of the first user, for operating the information of one recommended user among the recommended users, and correspondingly storing the operating information of the one recommended user and the registration information of the first user.
4. The method of any one of claims 1 to 3, wherein before obtaining the following matching information, the method further comprises:
receiving a registration request of a user sent by a client of the user, wherein the registration request comprises the at least one registration message, and the registration request comprises user real name information of the user;
and authenticating the user real name information, and storing at least one registration information of the user if the authentication is passed.
5. A user recommendation device, comprising:
the information obtaining unit is used for obtaining the following matching information when a server of the user recommendation system receives a user recommendation request sent by a client of a first user: the first user registration information, other user information bound with the first user, the first user query information, and the first user recent operation information, wherein the first user query information refers to information included in a user recommendation request sent to the server by a client of the first user, and the first user recent operation information refers to information stored in the server and used by the first user to operate the other user information within a recent preset time;
the user searching unit is used for searching a plurality of second users matched with the plurality of matching information acquired by the information acquiring unit according to a preset user binding information base; the second user is a part of users except the first user in the user binding information base, the user binding information base comprises registration information of each user in a plurality of users, and the registration information comprises user real name information; the user real name information comprises identity card information of a user;
a calculating unit, configured to calculate matching degrees between each of the plurality of second users and the plurality of matching information respectively;
and the user recommending unit is used for selecting the recommended user of the first user from the plurality of second users according to the matching degree calculated by the calculating unit and outputting the recommended user to the client of the first user.
6. The apparatus of claim 5,
the calculating unit is specifically configured to, if a certain second user matches with more than two pieces of matching information, take a sum of matching values that match the certain second user with the more than two pieces of matching information respectively as a matching degree of the second user;
or, the calculating unit is specifically configured to, if a certain second user matches with more than two pieces of matching information, take a mathematical calculation value of a weighted value of matching values that respectively match with the certain second user and the more than two pieces of matching information as the matching degree of the certain second user.
7. The apparatus of claim 5, further comprising:
and the operation storage unit is used for receiving information which is sent by the client of the first user and is used for the first user to operate the information of one recommended user in the recommended users, and correspondingly storing the operation information of the one recommended user and the registration information of the first user.
8. The apparatus of any of claims 5 to 7, further comprising:
a request receiving unit, configured to receive a registration request of a first user sent by a client of the user, where the registration request includes the at least one registration information, and includes user real-name information of the user;
and the registration unit is used for authenticating the real-name information of the user and storing at least one registration information of the user if the authentication is passed.
9. A computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the user recommendation method of any of claims 1 to 4.
10. A user recommendation device comprising a processor and a memory, said processor configured to implement instructions;
the memory is used for storing a plurality of instructions for being loaded by the processor and executing the user recommendation method according to any one of claims 1 to 4.
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| PCT/CN2016/101745 WO2017084455A1 (en) | 2015-11-18 | 2016-10-11 | User recommendation method and apparatus |
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| CN201510796777.8A CN106709750B (en) | 2015-11-18 | 2015-11-18 | User recommendation method and device |
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| CN101072194B (en) * | 2007-04-29 | 2010-12-08 | 腾讯科技（深圳）有限公司 | Method and system for searching information utilizing instant messaging system |
| CN101847226A (en) * | 2009-12-17 | 2010-09-29 | 广州市盈海文化传播有限公司 | Method and system for recommending opposite sex friend in social network service SNS community |
| CN102281207A (en) * | 2010-06-11 | 2011-12-14 | 百度在线网络技术（北京）有限公司 | Method for determining user matching degree and matching users chatting in social network and equipment thereof |
| JP5589081B2 (en) * | 2010-09-08 | 2014-09-10 | 株式会社日立製作所 | Computer system management method and management apparatus |
| CN102075573A (en) * | 2011-01-07 | 2011-05-25 | 北京邮电大学 | Method and system for automatically recommending learning partner in distance education social network service (ESNS) |
| US9563720B2 (en) * | 2013-02-06 | 2017-02-07 | Wespeke, Inc. | Matching users of a network based on profile data |
| CN103914559A (en) * | 2014-04-14 | 2014-07-09 | 小米科技有限责任公司 | Network user screening method and network user screening device |
| CN110162717B (en) * | 2014-06-05 | 2022-11-01 | 网易（杭州）网络有限公司 | Method and device for recommending friends |
| CN104239399B (en) * | 2014-07-14 | 2017-08-01 | 上海交通大学 | Potential friend recommendation method in social networks |
| CN104615775B (en) * | 2015-02-26 | 2018-08-07 | 北京奇艺世纪科技有限公司 | A kind of user's recommendation method and device |
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