CN110196951A - User matching method and equipment - Google Patents
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- CN110196951A CN110196951A CN201910335666.5A CN201910335666A CN110196951A CN 110196951 A CN110196951 A CN 110196951A CN 201910335666 A CN201910335666 A CN 201910335666A CN 110196951 A CN110196951 A CN 110196951A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—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
- G06F16/9536—Search customisation based on social or collaborative filtering
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- 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
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
Abstract
The present invention provides a kind of user matching method and equipment, which comprises obtains user's characteristic information；Similarity and active user's target body collection between user are calculated according to the characteristic information, the body is for characterizing the group that the user characteristics are divided according to the degree of association；Selection and the matched target user of active user are concentrated in active user's target body using the similarity between the user.First select and the biggish other users of oneself degree of association, it is matched by the similarity of both sides, since the degree of association and similarity are that user both sides to be matched determine jointly, matched user both sides can be achieved and there is more common trait, so that a possibility that user, which may not need, takes a significant amount of time searching and user similar in oneself feature, and the stranger's social activity greatly improved is established.The a large amount of time can be saved when user's foundation is social, so that simple and efficient when stranger establishes social.Better experience is brought for user.
Description
Technical field
The present invention relates to the field of data mining, and in particular to a kind of user matching method and equipment.
Background technique
Social activity refers to the dealings of person to person in society, is people's (tool) transmitting information, friendship by way of certain
The consciousness of thought is flowed, to reach the social Activities of certain purpose.Current era, the variation of economy and society environment is so that people
Contacts between people seem more important.Because we only constantly associates with all kinds of personnel and information communication,
Oneself can be constantly enriched, develops oneself, expand oneself.
Application with Internet resources in life with the development of science and technology, interpersonal contacts start by
Internet realizes, can also be carried out by internet social between stranger, and realization further develop oneself and expand oneself
Purpose.For example, internet platform and the service of some leading stranger's social interaction servers have been had already appeared in the prior art, such as
People near search carries out dialogue on line, transmission network drift bottle etc..
However, social activity by being issued on entire platform and towards user group be all magnanimity grade, it is existing
Some stranger's social network-i i-platform majorities are that user recommends that the strange of matching chat can be carried out based on information such as region, ages
People, however, since whether the interest, hobby or even three sights that user does not know about the user of platform recommendation same or similar with oneself,
The social object of oneself intention can not accurately be navigated to by causing user to find social object again, even if there are oneself intentions
Social object, but may oneself not be the social object of other side's intention, even if successful match, since the intention of both sides is different
Or three sight difference cause also to be difficult to set up normal Social behaviors, at this point, user need by largely put question to, exchange determine it is double
Whether side is more appropriate social object, is established between the stranger for being social many and diverse inefficient.
Summary of the invention
In view of this, the present invention provides a kind of user matching method, to promote the probability and effect of stranger's social activity foundation
Rate.The matching process may include: acquisition user's characteristic information；According to the characteristic information calculate user between similarity and
Active user's target body collection, the body is for characterizing the group that the user characteristics are divided according to the degree of association；Using described
Similarity between user concentrates selection and the matched target user of active user in active user's target body.
Optionally, the user's characteristic information include at least one attributive character information of user and/or user extremely
Few behavioural characteristic letter.
Optionally, attributive character described in each user includes multiple levels；It is described to be calculated according to the characteristic information
Ownership goal body collection includes: that the level based on the user property feature calculates difference degree between the attributive character；Root
The degree of association with other users is calculated according to the difference degree；It chooses the degree of association and is greater than the user of preset value as active user's target
Body collection.
Optionally, the degree of association calculated according to the difference degree with other users；According to the user property feature
Classification calculate separately the score value of the degree of association of every kind of user property feature between user；The score value of the degree of association is summed to obtain
The degree of association of attributive character between user.
Optionally, the similarity between the calculating user according to the characteristic information includes: to be obtained according to user property feature
To user property vector；User behavior vector is obtained according to user behavior characteristics；Calculate user property vector between first away from
From and/or user behavior vector between second distance；The use is determined according to the first distance and/or the second distance
Similarity between family.
Optionally, described the distance between the user property vector that calculates includes: the included angle cosine value for calculating family attribute vector,
Using the included angle cosine value as the first distance between user property vector.
Optionally, it is described calculate user behavior vector between second distance include: calculate family behavior vector angle more than
String value, using the included angle cosine value as the second distance between user behavior vector.
Optionally, the similarity using between the user active user's target body concentrate selection with it is current
The matched target user of user includes: the activity of the user for obtaining the target body and concentrating；It is selected according to the activity of the user
The user for selecting predetermined number gathers as user to be matched；To the user in the user to be matched set according to it is described current
The similarity of user successively sorts from high to low；Sequence based on the similarity to the active user recommend target user into
Row matching.
Optionally, according to the activity of the user select the user of predetermined number as user to be matched set and it is described
User in the user to be matched set is successively wrapped between sequence from high to low according to the similarity of the active user
It includes: obtaining the screening conditions of user；The user in user's set to be matched is screened according to the screening conditions；Institute
It states successively to sort to the user in user's set to be matched from high to low according to the similarity with the active user and includes:
User in user's set to be matched after screening is successively arranged from high to low according to the similarity with the active user
Sequence.
The present invention also provides a kind of user's matching units, comprising: at least one processor；And with described at least one
Manage the memory of device communication connection；Wherein, the memory is stored with the instruction that can be executed by one processor, the finger
It enables and being executed by least one described processor, so that at least one described processor executes above-mentioned user matching method.
The user matching method and equipment provided according to the present invention is associated with by user's characteristic information to according to user characteristics
Degree user characteristics are grouped and calculated with the similarity between user, according to user's similarity reorganization not in find can with work as
The preceding matched target user of user matches active user.First according to user characteristics determine other users belonging to body collection, really
The fixed and higher user of active user's degree of correlation, matches user according to the similarity of user characteristics, due to the degree of association
It is that user both sides to be matched determine jointly with similarity, therefore, finds active user's target body collection using user characteristics
The middle higher user of similarity as active user matching target user, it can be achieved that matched user both sides exist it is more
Common trait, so that user, which may not need, takes a significant amount of time searching and user similar in oneself feature, the footpath between fields greatly improved
A possibility that stranger's social activity is established.The a large amount of time can be saved when user establishes social, when so that stranger establishing social
It is simple and efficient.Better experience is brought for user.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, is also possible to obtain other drawings based on these drawings.
Fig. 1 is the user matching method flow chart in the embodiment of the present invention；
Fig. 2 is the virtual device structure figure of user's coalignment in the embodiment of the present invention；
Fig. 3 is the schematic diagram of user's matching unit in the embodiment of the present invention.
Specific embodiment
Technical solution of the present invention is clearly and completely described below in conjunction with attached drawing, it is clear that described implementation
Example is a part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill
Personnel's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
As long as in addition, the non-structure each other of technical characteristic involved in invention described below different embodiments
It can be combined with each other at conflict.
Include a plurality of clients and at least one server in a social networks, passes through service between these user terminals
Device interacts, and interaction includes instant messaging and non-instant communication.Such as it can both be carried out by server between user real-time
Written communication, can also check the content of publication mutually, such as individual subscriber homepage delivers picture, delivers word content.
The present invention provides a kind of user matching methods, in social networks, there are a plurality of clients, each user terminal
Purpose is to find to meet oneself intention, and the stranger for oneself also complying with other people intentions establishes social activity, the purpose of the present invention is
Social activity is established in order to match the stranger that both sides have intention to user, in order to clearly demonstrate the purpose of the present invention, this implementation
Example is described in detail this method with the angle of one of user.This method can by social networks server or
Server cluster executes, and this method comprises the following steps as shown in Figure 1:
S1 obtains user's characteristic information.In the present embodiment, user's characteristic information may include user property feature letter
Breath, can also include user behavior characteristics information, wherein and user property feature may include the quantization characteristic of user, such as: it uses
Location, age, height, weight, Income situation, the brand of used terminal, the price at family etc.；User property feature can also wrap
Include virtual feature of user, such as education degree, learning ability, sociability, IQ, the feeling quotrient of user etc..Different features
It can be used as the attributive character of a user.The behavioural characteristic of alleged user can be include: user's active period, be
Take regular exercise and often do which movement, if like the hobbies of users such as tourism, the tourist destination arrived and
The behavioural habits of user.In the present embodiment, the alleged characteristic information for obtaining user can be filled out on platform by obtaining user
The acquisition of information of oneself write, the test topic that can also be carried out by user, gets by psychological analysis, can be with benefit
It is obtained with machine learning study user is usual using the habit of platform.It is put down for example, the behavioural characteristic of user can acquire user
When training sample of the usage behavior as machine learning model, machine learning model is trained, finally according to user's
Use habit obtains the behavioural characteristic of user, and specific training method is referred to the training method of other machines learning model,
It repeats no more in the present embodiment.
S2. the similarity and active user's target body collection between user are calculated according to characteristic information.In the present embodiment,
The body is for characterizing the group that user characteristics are divided according to the degree of association.In the present embodiment, user property feature may include more
It is a, these features can be divided into according to certain rules in different groupings, wherein each grouping can represent one
The body.The division of the body is illustrated below by citing, such as the attribute of user may include X attribute, Y attribute and Z belong to
Property, such as place city, the information (information such as brand, price) at age and mobile phone used can be respectively indicated, X attribute for example may be used
City where user can be divided into x level according to city rank, for example, a line city, two by city where thinking user
Line city, three line cities etc..Y attribute can be the age, for example, can according to age bracket to y level will be divided into the age, such as
It can be teenager, youth, middle age etc., Z attribute is, for example, cellphone information, can be divided into according to mobile phone price or branded counterparts machine
Z level.For convenience of description, in the present embodiment, X attribute can be denoted as D, Y attribute is denoted as A, Z attribute is denoted as C,
In, body type expression formula can be with are as follows: S=D | A | C, body type number can be with are as follows: x*y*z kind.It in the present embodiment, can be with
According to the attributive character of user, user can be divided into and which kind of body belonged to, i.e., the external feature of user carries out more intuitive
It divides, preliminary screening can be carried out to user in this way, for example, the rank in city where two users differs bigger, user A
In a line city, user B is in five line cities, then the living habit of two users or consumption view etc. may be different, then two use
The possible difference of the body at family is bigger, alternatively, other attributive character can be added, for example, the mobile phone valence of user A and user B
Lattice may differ by bigger, it may be considered that the habit of two personal use mobile phones is different, can be confirmed that certain personality differences compare
Greatly, then the possible difference of the body of user is bigger.It is described in detail below and how to determine the ownership goal body:
It is illustrated by taking two users as an example, wherein the body of user A are as follows: S1=D1|A1|C1；The body of user B is S2
=D2|A2|C2, difference degree between the level computation attribute feature based on user property feature, calculated according to difference degree and other
The degree of association of user；It chooses the degree of association and is greater than the user of preset value as active user's target body collection.For convenience of description, at this
In embodiment, it is illustrated by taking specific example as an example, such as: the difference degree of X attribute can be with are as follows:Wherein,
ds1s2For the difference degree of X attribute, D1For the quantized value of the X attribute of user A, D2The quantized value of the X attribute of position user B, with X attribute
For the city of user place, one line city of city where user A, city where user B is a line city, then user A and use
Difference degree of the family B on X attribute is 0；If B is in tier 2 cities, it may be considered that user A and difference of the user B on X attribute
Degree is 1.If in three line cities, it may be considered that difference degree of the user A and user B on X attribute is larger.In the present embodiment
In, user lesser for difference degree can consider that the degree of association between two users is larger, it specifically may refer to following formula:
Wherein, ds1s2The difference degree scoring of two users can be respectively indicated for the difference degree of X attribute, 9,6,0, in this reality
It applies in example and is merely illustrative, can also be scored using the different degree of association of other numerical representation methods.
It similarly, can difference according to the classification of Y attribute, between the level computation attribute feature based on user property feature
Degree, for example, Y attribute can be age of user, the age of two users can be user A and user B presetting between the time limit
Difference degree it is smaller, except the default time limit can be larger for difference degree, can specifically participate in following formula:
as1s2For the difference degree of X attribute, A1For the quantized value of the Y attribute (can be the age) of user A, A2The Y of position user B
The quantized value of attribute (can be the age), 6,0 can respectively indicate the difference degree scoring of two users, | A1-A2|For age of user
Difference, be merely illustrative in the present embodiment, can also using other numerical representation methods it is different the degree of association scoring.That is age gap
Not within 3 years it is considered that user difference degree it is smaller, 3 years or more can for difference degree it is larger.
It similarly, can difference according to the classification of Z attribute, between the level computation attribute feature based on user property feature
Degree, for example, Z attribute can be cellphone information used in user, between two users can be the difference of user A and user B
Degree is smaller, and except the default time limit can be that difference degree is larger, can specifically participate in following formula:
cs1s2For the difference degree of X attribute, C1For the quantized value of the Z attribute (can be mobile phone price) of user A, C2Position user B
Z attribute (can be mobile phone price) quantized value, 9,6,0 can respectively indicate two users difference degree scoring.In this reality
It applies in example and is merely illustrative, can also be scored using the different degree of association of other numerical representation methods.I.e. year mobile phone price more connects
It is close, it is believed that the difference degree of user is smaller, 3 years or more can be larger for difference degree.
It, can be special with multiple attributes of synthetic user after the quantized value of the difference degree for the multiple features for calculating each user
The difference metrization value of sign calculates active user to the degree of association of other users, for example, can be by the difference of multiple attributive character
Metrization value is added to obtain the value of the degree of association between user, specifically, may refer to following formula:
Wherein, vs1s2The quantized value of the degree of association of position active user and other users determines current use in the present embodiment
After family is to the degree of association of other users, judge whether the degree of association is greater than preset value, when being greater than preset value, determines that other users are
The target body of active user, can calculate separately the degree of association of active user Yu multiple users, determine active user's target body
Shell collection.
In the present embodiment, the similarity between user can also be calculated according to characteristic information.In the present embodiment, Yong Hute
Reference breath can also include that at least one behavioural characteristic of user is believed, in the present embodiment, be used according to user property feature
Family attribute vector；User behavior vector is obtained according to user behavior characteristics；Calculate user property vector between first distance and/
Or the second distance between user behavior vector；The similarity between user is determined according to first distance and/or second distance.Specifically
, the attributive character of user may include it is multiple, the behavior of user also may include it is multiple, user property feature is quantified
An available n attribute vector, can be denoted as: P=(p1, p2..., pn).Wherein, p1…pnRespectively user property feature
Dimension, for example, the place city of user, age, cellphone information etc. can be used as the dimension of attribute vector.To user behavior
Feature carries out quantifying an available m attribute vector, can be denoted as: Q=(q1, q2..., qm).Wherein, p1 ... pn distinguishes
For the dimension of user property feature, for example, user liked movement, user active period, user the trip liked
Mode etc. can be used as the dimension of user's row vector.
In the present embodiment, it can use first between attribute vector and/or behavior vector calculating user property vector
Second distance between distance and/or user behavior vector, specifically, can with first distance and second distance can for Euclidean away from
From can also be co sinus vector included angle value.It can be illustrated by taking co sinus vector included angle value as an example in the present embodiment, specifically, to
Measuring angle can be indicated using following formula:
Wherein, Pi is different vectors from Pj.
Specifically, using the attribute vector angle of above formula two users of calculating can be with cos (PAPB), wherein PA is user A
Attribute vector, PB be user B attribute vector.Use the behavior vector angle of above formula two users of calculating can be with cos
(PAPB), wherein QA is the behavior vector of user A, and QB is the behavior vector of user B.Using attribute value as user property vector it
Between first distance.Using behavior co sinus vector included angle value as the second distance between user behavior vector.
In the present embodiment, the similarity that user can be individually characterized using first distance or second distance, can also adopt
With the similarity of first distance and the characterized user of second distance, specifically, the value range of co sinus vector included angle value be [-
1,1], when co sinus vector included angle value is 1, then it is assumed that two vectors are identical, think that two vectors are completely opposite when being -1.With
This can define the similarity of user.
S3. selection is concentrated to use with the matched target of active user in active user's target body using the similarity between user
Family.After obtaining the target body collection of user, the activity of the user that the target body is concentrated is obtained；It is selected according to the activity of the user
The user for selecting predetermined number gathers as user to be matched；I.e. selection obtains the highest preceding n of liveness from each target body
A user forms user's set to be matched.Obtain the screening conditions of user；User to be matched is gathered according to screening conditions
In user screen；To the user in the user to be matched set after screening according to the similarity with active user by up to
It is low successively to sort.Sequence based on similarity recommends target user to match active user.Matched user can be realized
There is more common trait in both sides, so that user, which may not need, takes a significant amount of time searching and the similar use of oneself feature
A possibility that family, the stranger's social activity greatly improved is established.Better experience is brought for user.
The present invention also provides a kind of user's coalignments, as shown in Fig. 2, the device includes:
Acquiring unit 10 obtains user's characteristic information；Computing unit 20, for calculating the phase between user according to characteristic information
Like degree and active user's target body collection, the body is for characterizing the group that user characteristics are divided according to the degree of association；Matching unit
30, for concentrating selection and the matched target user of active user in active user's target body using the similarity between user.
The present invention also provides a kind of user interaction monitoring device, as shown in figure 3, include one or more processors 41 with
And memory 42, in Fig. 3 by taking a processor 43 as an example.
Control unit can also include: input unit 43 and output device 44.
Processor 41, memory 42, input unit 43 and output device 44 can be connected by bus or other modes,
In Fig. 3 for being connected by bus.
Processor 41 can be central processing unit (Central Processing Unit, CPU).Processor 41 can be with
For other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
The combination of the chips such as discrete hardware components or above-mentioned all kinds of chips.General processor can be microprocessor or the processing
Device is also possible to any conventional processor etc..
Memory 42 is used as a kind of non-transient computer readable storage medium, can be used for storing non-transient software program, non-
Transient computer executable program and module, as the user in the embodiment of the present application matches corresponding program instruction/module.Place
Non-transient software program, instruction and the module that reason device 41 is stored in memory 42 by operation, thereby executing server
The user matching method of above method embodiment is realized in various function application and data processing.
Memory 42 may include storing program area and storage data area, wherein storing program area can storage program area,
Application program required at least one function；Storage data area can store the use institute according to the processing unit of server operation
The data etc. of creation.In addition, memory 42 may include high-speed random access memory, it can also include non-transient memory,
A for example, at least disk memory, flush memory device or other non-transient solid-state memories.In some embodiments, it deposits
Optional reservoir 42 includes the memory remotely located relative to processor 41, these remote memories can be by being connected to the network extremely
Network connection device.The example of above-mentioned network include but is not limited to internet, intranet, local area network, mobile radio communication and
A combination thereof.
Input unit 43 can receive the number or character information of input, and generate the user with the processing unit of server
Setting and the related key signals input of function control.Output device 44 may include that display screen etc. shows equipment.
One or more module is stored in memory 42, when being executed by one or more processor 41, is executed
Method as shown in Figure 1.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Obviously, the above embodiments are merely examples for clarifying the description, and does not limit the embodiments.It is right
For those of ordinary skill in the art, can also make on the basis of the above description it is other it is various forms of variation or
It changes.There is no necessity and possibility to exhaust all the enbodiments.And it is extended from this it is obvious variation or
It changes still within the protection scope of the invention.
Claims (10)
1. a kind of user matching method characterized by comprising
Obtain user's characteristic information；
Similarity and active user's target body collection between user are calculated according to the characteristic information, the body is for characterizing
The group that the user characteristics are divided according to the degree of association；
Selection and the matched target of active user are concentrated in active user's target body using the similarity between the user
User.
2. the method as described in claim 1, which is characterized in that the user's characteristic information includes at least one category of user
At least one behavior characteristic information of property characteristic information and/or user.
3. method according to claim 2, which is characterized in that attributive character described in each user includes multiple levels；
It is described to include: according to characteristic information calculating ownership goal body collection
Level based on the user property feature calculates the difference degree between the attributive character；
The degree of association with other users is calculated according to the difference degree；
It chooses the degree of association and is greater than the user of preset value as active user's target body collection.
4. method as claimed in claim 3, which is characterized in that described calculated according to the difference degree is associated with other users
Degree includes:
The score value of the degree of association of every kind of user property feature between user is calculated separately according to the classification of the user property feature；
The degree of association of attributive character summing to obtain user between the score value of the degree of association.
5. method according to claim 2, which is characterized in that the similarity calculated according to the characteristic information between user
Include:
User property vector is obtained according to user property feature；
User behavior vector is obtained according to user behavior characteristics；
Calculate the first distance between user property vector and/or the second distance between user behavior vector；
The similarity between the user is determined according to the first distance and/or the second distance.
6. method as claimed in claim 5, which is characterized in that the distance between described calculating user property vector includes:
Calculate family attribute vector included angle cosine value, using the included angle cosine value as first between user property vector away from
From.
7. method as claimed in claim 5, which is characterized in that the second distance packet calculated between user behavior vector
It includes:
Calculate family behavior vector included angle cosine value, using the included angle cosine value as second between user behavior vector away from
From.
8. such as the described in any item methods of claim 3-7, which is characterized in that the similarity using between the user is in institute
The concentration selection of active user's target body, which is stated, with the matched target user of active user includes:
Obtain the activity of the user that the target body is concentrated；
The user of predetermined number is selected to gather as user to be matched according to the activity of the user；
It successively sorts from high to low to the user in user's set to be matched according to the similarity with the active user；
Sequence based on the similarity recommends target user to match the active user.
9. method according to claim 8, which is characterized in that
According to the activity of the user select the user of predetermined number as user to be matched set and it is described to it is described to
With user set in user according to the active user similarity from high to low successively sequence between include:
Obtain the screening conditions of user；
The user in user's set to be matched is screened according to the screening conditions；
The user in user's set to be matched successively arranges from high to low according to the similarity with the active user
Sequence includes:
To the user in the user to be matched set after screening according to the similarity with the active user from high to low according to
Minor sort.
10. a kind of user's matching unit characterized by comprising at least one processor；And with it is described at least one processing
The memory of device communication connection；Wherein, the memory is stored with the instruction that can be executed by one processor, described instruction
It is executed by least one described processor, so that at least one described processor perform claim requires described in any one of 1-9
User matching method.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910335666.5A CN110196951A (en) | 2019-04-24 | 2019-04-24 | User matching method and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910335666.5A CN110196951A (en) | 2019-04-24 | 2019-04-24 | User matching method and equipment |
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| CN110196951A true CN110196951A (en) | 2019-09-03 |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110782342A (en) * | 2019-10-29 | 2020-02-11 | 北京明略软件系统有限公司 | Method and device for verifying correctness of new channel feature engineering based on binary classification model |
| CN111506674A (en) * | 2020-05-12 | 2020-08-07 | 支付宝(杭州)信息技术有限公司 | Matching method and device |
| CN112559893A (en) * | 2021-01-11 | 2021-03-26 | 引粒网络科技(上海)有限公司 | User recommendation method in internet matching social scene |
-
2019
- 2019-04-24 CN CN201910335666.5A patent/CN110196951A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110782342A (en) * | 2019-10-29 | 2020-02-11 | 北京明略软件系统有限公司 | Method and device for verifying correctness of new channel feature engineering based on binary classification model |
| CN111506674A (en) * | 2020-05-12 | 2020-08-07 | 支付宝(杭州)信息技术有限公司 | Matching method and device |
| CN111506674B (en) * | 2020-05-12 | 2023-11-03 | 支付宝(杭州)信息技术有限公司 | Matching method and device |
| CN112559893A (en) * | 2021-01-11 | 2021-03-26 | 引粒网络科技(上海)有限公司 | User recommendation method in internet matching social scene |
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