CN104408043B

CN104408043B - A kind of information processing method and server

Info

Publication number: CN104408043B
Application number: CN201410555108.7A
Authority: CN
Inventors: 常晓猛; 贺鹏; 陈川; 岳亚丁; 王巨宏; 管刚; 乐阳; 李清泉
Original assignee: Tencent Technology Shenzhen Co Ltd; Shenzhen University
Current assignee: Tencent Technology Shenzhen Co Ltd; Shenzhen University
Priority date: 2014-10-17
Filing date: 2014-10-17
Publication date: 2019-02-22
Anticipated expiration: 2034-10-17
Also published as: CN104408043A

Abstract

The invention discloses a kind of information processing method and servers, wherein the described method includes: obtaining user's spatio-temporal activity information of each user in group according to user-generated content；The first information is determined according to user's spatio-temporal activity information, and the first screening parameter is determined according to the first information；The first information is for characterizing user in the variation of Spatial Dimension；The second information is determined according to user's spatio-temporal activity information, and the second screening parameter is determined according to second information；Second information is for characterizing user in the variation of time dimension；It is concentrated according to preset strategy from screening parameter and chooses first screening parameter and/or second screening parameter, filtered out and the most matched target user of first user from the corresponding candidate user group of the first user in the group according to first screening parameter and/or second screening parameter.

Description

A kind of information processing method and server

Technical field

The present invention relates to the mechanics of communication of internet area more particularly to a kind of information processing methods and server.

Background technique

Present inventor at least has found exist in the related technology during realizing the embodiment of the present application technical solution Following technical problem:

Current internet development is rapid, and interpersonal communication exchange channel is more and more abundant.Wherein blog, space, Microblogging, wechat, the various friend-making modes such as communication and platform already become the social irreplaceable a part of people in time, they are total It is same to constitute social networks complicated on network.

The rise of social networks, has largely widened the friend-making range between people, and user is flat in social networks More people can be recognized on platform, how effectively to find the good friend properly associated, become research topic important at present, be based on this The demand of problem, friend recommendation function is more and more important.And in existing friend recommendation method, commonly include: 1) according to The essential information of fill data is matched when the login account of family, carries out friend recommendation based on similarity height later；2) basis The far and near of orientation distance carries out friend recommendation between user；3) friend recommendation is carried out in a manner of the good friend of commending friends.

Following problems exist in the prior art:

One, for above scheme 1) for, there are information is incomplete or information is false for the basic document filled in due to user May, if only being matched based on these essential informations and recommending to be bound to that the phase of user's real information cannot be well reflected Like property, cause the precision for carrying out friend recommendation not high；

Two, for above scheme 2) for, the distance of distance can not recommend suitable potential good friend well, can also lead Cause the precision for carrying out friend recommendation not high；

Three, for above scheme 3) for, the potential good friend of the good friend of good friend not necessarily user, in this way into Row friend recommendation, the precision that similarly will lead to progress friend recommendation be not high.

Summary of the invention

In view of this, the embodiment of the present invention is desirable to provide a kind of information processing method and server, solve at least existing The above problem existing for technology can accurately, effectively find suitable friendship to improve the precision of friend recommendation for user Past good friend provides higher success rate.

The technical solution of the embodiment of the present invention is achieved in that

The embodiment of the invention provides a kind of information processing methods, which comprises

User's spatio-temporal activity information of each user in group is obtained according to user-generated content；

The first information is determined according to user's spatio-temporal activity information, determines that the first screening is joined according to the first information Number；The first information is for characterizing user in the variation of Spatial Dimension；

The second information is determined according to user's spatio-temporal activity information, determines that the second screening is joined according to second information Number；Second information is for characterizing user in the variation of time dimension；

It is concentrated according to preset strategy from screening parameter and chooses first screening parameter and/or second screening parameter, According to first screening parameter and/or second screening parameter from the corresponding candidate user of the first user in the group It is filtered out in group and the most matched target user of first user.

In above scheme, the method also includes:

Third screening parameter is determined according to first screening parameter and second screening parameter；

The screening parameter is written in the third screening parameter to concentrate, further according to first screening parameter and/ Or second screening parameter and/or the third screening parameter are from the corresponding candidate user group of the first user in the group In filter out and the most matched target user of first user.

In above scheme, user's spatio-temporal activity information that each user in group is obtained according to user-generated content, packet Include the one or more of following manner:

Mode one: user is searched in the user-generated content and logs in and exit the letter of spatio-temporal activity caused by server Breath；

Mode two: spatio-temporal activity information caused by user and server communication is searched in the user-generated content；

Mode three: the related generated spatio-temporal activity information of registering of user is searched in the user-generated content；

Mode four: user is searched in the user-generated content and uploads spatio-temporal activity letter caused by related trip track Breath.

It is described that user is searched in the user-generated content when logging in and exiting caused by server in above scheme Empty action message, comprising:

It logs in and exits by record user and search to obtain the spatio-temporal activity information using the log information of APP；

The spatio-temporal activity information includes at least: user's history is logged in and is exited using the temporal information of APP and/or internet Protocol IP address information and/or cellular base station information and/or GPS information and/or information of place names and/or WIFI information.

In above scheme, the lookup user in the user-generated content and space-time caused by server communication are living Dynamic information includes:

The letter sent in handshaking procedures is kept according to assigned frequency and server during using APP by record user Breath is searched and obtains the spatio-temporal activity information；

The spatio-temporal activity information includes at least: time and/or the IP address of user and server active and passive communication And/or cellular base station information and/or GPS information and/or place name and/or WIFI information.

It is described that the related generated spatio-temporal activity letter of registering of user is searched in the user-generated content in above scheme Breath；

The spatio-temporal activity is obtained using the information searching of registering of APP active upload to server by record user to believe Breath；

The spatio-temporal activity information includes at least: user registers the POI information and/or temporal information and/or ground of point of interest Manage location information and/or text information and/or pictorial information.

In above scheme, when the lookup user in the user-generated content uploads caused by related trip track Empty action message includes:

It searches to obtain the spatio-temporal activity letter using the trace information of APP active upload to server by record user Breath；

The spatio-temporal activity information includes at least: the starting point of user trajectory and the POI information of terminal and/or temporal information And/or geographical location information；And/or

The POI information and/or temporal information and/or geographical location information of user's trajectory paths point between Origin And Destination.

It is described that the first information is determined according to user's spatio-temporal activity information in above scheme, comprising:

The extraction of spatial information of Spatial Dimension involved in user's spatio-temporal activity information is come out, and is isolated explicit Spatial information and implicit spatial information；

After converting explicit spatial information for the implicit spatial information, using the explicit spatial information as One sampled point simultaneously obtains the second sampled point of gridding by mesh mapping resampling；

By second sampled point according to the coordinate of user access point and the frequency of access point, pass through preset interpolation strategies The spatial dimension and Density Distribution of User Activity are generated, and using the spatial dimension of the User Activity and Density Distribution as described in The first information.

It is described that first screening parameter is determined according to the first information in above scheme, comprising:

Judge first user main activities range whether the main activities at least one alternative candidate user group There is overlapping in range, obtain judging result；

The judging result is that when there is overlapping, the candidate user group of overlapping will be present as corresponding with first user Candidate user group；

Obtain all users in candidate user group corresponding with first user；

It is used respectively with described first according to all users described in the spatial dimension of the User Activity and Density Distribution operation User Activity spatial distribution index of similarity between family, and using the User Activity spatial distribution index of similarity as described in First screening parameter.

It is described that second information is determined according to user's spatio-temporal activity information in above scheme, comprising:

The extraction of spatial information of time dimension involved in user's spatio-temporal activity information is come out, to the space extracted All access points of user in information carry out the access point set from high to Low sequence, after being sorted according to its access frequency；

Each point that access point after successively traversing the sequence is concentrated, obtains the accumulated probability of each point, when described every When the accumulated probability of a point is greater than a threshold value, the point that will be greater than the threshold value is denoted as user and resides access point；

The space-time trajectory sequence that access point generates user's common activities is resided by the user after traversal, and will be described The space-time trajectory sequence of user's common activities is as second information.

It is described that second screening parameter is determined according to second information in above scheme, comprising:

Obtain all users in candidate user group corresponding with first user；

According to all users described in the space-time trajectory Sequence Operation Theory of user's common activities respectively with first user Between user's space-time trajectory index of similarity, and using user's space-time trajectory index of similarity as it is described second screening join Number.

The embodiment of the invention provides a kind of server, the server includes:

Module is obtained, for obtaining user's spatio-temporal activity information of each user in group according to user-generated content；

First determining module, for determining the first information according to user's spatio-temporal activity information, according to first letter It ceases and determines the first screening parameter；The first information is for characterizing user in the variation of Spatial Dimension；

Second determining module, for determining the second information according to user's spatio-temporal activity information, according to second letter It ceases and determines the second screening parameter；Second information is for characterizing user in the variation of time dimension；

Processing module chooses first screening parameter and/or described for concentrating according to preset strategy from screening parameter Second screening parameter, according to first screening parameter and/or second screening parameter from the first user in the group It is filtered out in corresponding candidate user group and the most matched target user of first user.

In above scheme, the server further include:

Third determining module, for determining third screening ginseng according to first screening parameter and second screening parameter Number；

Processing module is further used for that the screening parameter concentration is written the third screening parameter into, further basis First screening parameter and/or second screening parameter and/or the third screening parameter are from first in the group It is filtered out in the corresponding candidate user group of user and the most matched target user of first user.

In above scheme, the acquisition module is further used for using one or more acquisition groups including following manner User's spatio-temporal activity information of each user in group:

In above scheme, the acquisition module further include:

First searches submodule, searches to obtain institute using the log information of APP for logging in and exiting by record user State spatio-temporal activity information；

In above scheme, the acquisition module further include:

Second searches submodule, for being protected during using APP according to assigned frequency and server by record user It holds the information searching sent in handshaking procedures and obtains the spatio-temporal activity information；

In above scheme, the acquisition module further include:

Third searches submodule, and user is searched in the user-generated content in relation to when registering generated for described Empty action message；

In above scheme, the acquisition module further include:

4th searches submodule, for being searched by record user using the trace information of APP active upload to server Obtain the spatio-temporal activity information；

In above scheme, first determining module further include:

First extracting sub-module, for by the extraction of spatial information of Spatial Dimension involved in user's spatio-temporal activity information Out, and explicit spatial information and implicit spatial information are isolated；

Mapping submodule will be described explicit after converting explicit spatial information for the implicit spatial information Spatial information obtain the second sampled point of gridding as the first sampled point and by mesh mapping resampling；

The first information generates submodule, for by second sampled point according to the coordinate of user access point and access point Frequency generates the spatial dimension and Density Distribution of User Activity by preset interpolation strategies, and by the sky of the User Activity Between range and Density Distribution as the first information.

In above scheme, first determining module further include:

First judging submodule, for judging whether the main activities range of first user alternative waits at least one It selects the main activities range of user group to there is overlapping, obtains judging result；The judging result is that when there is overlapping, weight will be present Folded candidate user group is as candidate user group corresponding with first user；

First acquisition submodule, for obtaining all users in candidate user group corresponding with first user；

First similarity exponent arithmetic submodule, for the spatial dimension and Density Distribution operation according to the User Activity All users User Activity spatial distribution index of similarity between first user respectively, and the user is living Spatial distribution index of similarity is moved as first screening parameter.

In above scheme, second determining module further include:

Second extracting sub-module, for by the extraction of spatial information of time dimension involved in user's spatio-temporal activity information Out, all access points of user in the spatial information extracted obtain from high to Low sequence according to its access frequency Access point set after to sequence；

Traversal searches submodule, and each point concentrated for successively traversing the access point after the sequence obtains each point Accumulated probability, when the accumulated probability of each point is greater than a threshold value, will be greater than the point of the threshold value, to be denoted as user resident Access point；

Second information generates submodule, resides access point by the user after being used to traverse and generates user's common activities Space-time trajectory sequence, and using the space-time trajectory sequence of user's common activities as second information.

In above scheme, second determining module further include:

Second judgment submodule, for judging whether the main activities range of first user alternative waits at least one It selects the main activities range of user group to there is overlapping, obtains judging result；The judging result is that when there is overlapping, weight will be present Folded candidate user group is as candidate user group corresponding with first user；

Second acquisition submodule, for obtaining all users in candidate user group corresponding with first user；

Second similarity exponent arithmetic submodule, for the space-time trajectory Sequence Operation Theory institute according to user's common activities State user space-time trajectory index of similarity of all users respectively between first user, and by user's space-time trajectory Index of similarity is as second screening parameter.

The information processing method of the embodiment of the present invention includes: the user that each user in group is obtained according to user-generated content Spatio-temporal activity information；The first information is determined according to user's spatio-temporal activity information, and the first sieve is determined according to the first information Select parameter；The first information is for characterizing user in the variation of Spatial Dimension；It is determined according to user's spatio-temporal activity information Second information determines the second screening parameter according to second information；Second information is for characterizing user in time dimension Variation；It is concentrated according to preset strategy from screening parameter and chooses first screening parameter and/or second screening parameter, root According to first screening parameter and/or second screening parameter from the corresponding candidate user group of the first user in the group In filter out and the most matched target user of first user.

Using the embodiment of the present invention, by the first information and second for characterizing the two different dimensions of room and time respectively Information further obtains corresponding first screening parameter and the second screening parameter, passes through the first screening parameter and the second screening ginseng Number is filtered out from the corresponding candidate user group of the first user in the group to be used with the most matched target of first user Family, to improve the precision of friend recommendation, can for user accurately, effectively find the good friend properly associated and provide more High success rate.

Detailed description of the invention

Fig. 1 is the implementation process schematic diagram of embodiment of the present invention method one；

Fig. 2 is the implementation process schematic diagram of embodiment of the present invention method two；

Fig. 3 is the implementation process schematic diagram of embodiment of the present invention method three；

Fig. 4 is the schematic diagram using a social networks of the embodiment of the present invention；

Fig. 5 is to have mobile schematic diagram using a social network user position of the embodiment of the present invention；

Fig. 6 is the second sampling point set for being mapped to gridding from the first sampled point set using one of the embodiment of the present invention The schematic diagram of conjunction；

Fig. 7 is the inside composed structure schematic diagram of server example one of the present invention；

Fig. 8 is a kind of external universal architecture schematic diagram of server of the embodiment of the present invention two；

Fig. 9 is the inside composed structure schematic diagram of server example three of the present invention.

Specific embodiment

The implementation of technical solution is described in further detail with reference to the accompanying drawing.

Embodiment of the method one:

The embodiment of the invention provides a kind of information processing methods, as shown in Figure 1, which comprises

Step 101, user's spatio-temporal activity information that each user in group is obtained according to user-generated content；

Step 102 determines the first information according to user's spatio-temporal activity information, determines first according to the first information Screening parameter；The first information is for characterizing user in the variation of Spatial Dimension；

Step 103 determines the second information according to user's spatio-temporal activity information, determines second according to second information Screening parameter；Second information is for characterizing user in the variation of time dimension；

Step 104 is concentrated from screening parameter according to preset strategy and chooses first screening parameter and/or second sieve Parameter is selected, it is corresponding from the first user in the group according to first screening parameter and/or second screening parameter It is filtered out in candidate user group and the most matched target user of first user.

Using the embodiment of the present invention, by the first information and second for characterizing the two different dimensions of room and time respectively Information further obtains corresponding first screening parameter and the second screening parameter, passes through the first screening parameter and the second screening ginseng Number is filtered out from the corresponding candidate user group of the first user in the group to be used with the most matched target of first user Family, to improve the precision of friend recommendation, can for user accurately, effectively find the good friend properly associated and provide more High success rate

Embodiment of the method two:

Based on embodiment of the method one, by taking the application of a specific field of social network as an example, such as blog, space, microblogging, Wechat, in time communication etc., wherein any one all constitutes the complicated social networks based on user；

The first information is the spatial dimension and Density Distribution of User Activity in social networks, corresponding the first obtained screening ginseng Number is User Activity spatial distribution index of similarity；Second information is the space-time trajectory sequence of user's common activities in social networks Column, corresponding the second obtained screening parameter are user's space-time trajectory index of similarity；

The then information processing method of the embodiment of the present invention, as shown in Figure 2, which comprises

Step 201, user's spatio-temporal activity information that each user in group is obtained according to user-generated content；

Step 202, the spatial dimension and Density Distribution that the User Activity is determined according to user's spatio-temporal activity information；

Step 203, the space-time trajectory sequence that user's common activities are determined according to user's spatio-temporal activity information；

Step 204 calculates the User Activity spatial distribution according to the spatial dimension and Density Distribution of the User Activity Index of similarity；

Step 205 calculates user's space-time trajectory similitude according to the space-time trajectory sequence of user's common activities Index；

Step 206 according to preset strategy is sieved using the combination of single screening parameter or multiple screening parameters Choosing chooses the User Activity spatial distribution index of similarity and/or user's space-time trajectory index of similarity to correspond to；

Step 207, according to the User Activity spatial distribution index of similarity and/or user's space-time trajectory similitude User's sequence is carried out in the corresponding candidate user group of the first user in group described in exponent pair, is used with filtering out with described first The most matched target user in family.

The above-mentioned steps process of the embodiment of the present invention is not restricted to current statement, adjustable sequence as needed, For example, the sequence of step 202 and step 203 can exchange, the sequence of step 204 and step 205 can also be exchanged.

Embodiment of the method three:

The first information is the spatial dimension and Density Distribution of User Activity in social networks, corresponding the first obtained screening ginseng Number is User Activity spatial distribution index of similarity；Second information is the space-time trajectory sequence of user's common activities in social networks Column, corresponding the second obtained screening parameter are user's space-time trajectory index of similarity；It is screened according to the first screening parameter and second The third screening parameter that parameter obtains is that User Activity space-time combines index of similarity；

The then information processing method of the embodiment of the present invention, as shown in Figure 3, which comprises

Step S205, referred to according to the User Activity spatial distribution index of similarity and user's space-time trajectory similitude Number calculates User Activity space-time and combines index of similarity；

It step S206, according to preset strategy is sieved using the combination of single screening parameter or multiple screening parameters Choosing chooses the User Activity spatial distribution index of similarity, user's space-time trajectory index of similarity and/or use to correspond to Activity space-time in family combines index of similarity；

Step S207, referred to according to the User Activity spatial distribution index of similarity, user's space-time trajectory similitude Several and/or User Activity space-time joint index of similarity in the corresponding candidate user group of the first user in the group to carrying out User's sequence, to filter out and the most matched target user of first user.

Using the embodiment of Fig. 2-Fig. 3, three screening parameters: user's space-time trajectory index of similarity, the user Movable space-time joint index of similarity, the User Activity space-time combine index of similarity, they respectively can be separately as sieve Select parameter, can also any combination of two or three combine together, for (or being waited to the corresponding candidate user group of the first user Choose friendly collection) in user sequence, the sequence of sequence is felt into priority, to filter out most matched target user, is used for Friend recommends, and sorts near preceding, be with first user either from spatially or from the time it is upper for be all most The target user matched.

In conclusion in this case, information processing scheme of the invention is actually a kind of based on user's space activity The friend recommendation scheme of range distribution and space-time trajectory similitude, for this friend recommendation scheme, can from blog, space, Microblogging, wechat, obtain in social networks described in communication etc. in time user log in, register with the geographical location information such as activity trajectory, Access time and frequency information, these information belong to user's spatio-temporal activity information, then according to user's spatio-temporal activity information The spatial dimension (boundary or radius) and Density Distribution (intensity or probability) of 1. User Activity can be got；When can also be according to user Empty action message obtains the main space-time trajectory sequence of 2. user.

To, according to it is above-mentioned 1. and 2. information respectively obtains User Activity spatial distribution index of similarity and the user when Empty track index of similarity, further according to User Activity spatial distribution index of similarity and user's space-time trajectory similitude Index can also calculate User Activity space-time joint index of similarity.For single user (i.e. described first user), root According to one of above-mentioned each index or a variety of, candidate user collection is ranked up and is its commending friends.Based on User Activity The friend recommendation of spatial distribution and space-time trajectory similitude can catch user to find known strange human psychological, the good friend of recommendation Chance height is met under acceptance and line, it is long that the friend relation of formation maintains the time, is conducive to improve and recommends efficiency, further extends Friend relation circle and improve friend relation network structure.

Based on above method embodiment two-tri-, in one preferred embodiment of the embodiment of the present invention, generated according to user in Hold the combination for obtaining that user's spatio-temporal activity information includes one or more of mode:

Mode one: the spatio-temporal activity letter that user logged in and exited server info generation is searched in user-generated content Breath；

Mode two: the spatio-temporal activity information of the information of user and server communication is searched in user-generated content；

Mode three: user is searched in user-generated content in relation to the spatio-temporal activity information registered；

Mode four: the spatio-temporal activity information for the related trip track that user uploads is searched in user-generated content.

1) it is based on above method embodiment two-tri-, it is described raw in user in one preferred embodiment of the embodiment of the present invention Include: at the spatio-temporal activity information generated when user logs in and exit APP is searched in content

Time and/or IP address and/or cellular base station information and/or the GPS information of APP are logged in and exited in user's history And/or place name and/or WIFI information etc..

As shown in figure 4, including user 11- user 15 in social networks, the base station base station 21- 23 is respectively to user 11- user Administered user in 15 carries out signal transmitting and signal receives, it is ensured that user can be existed by the mobile data network that base station is supported It is exchanged in social networks, such as more people's chat clusters, more people's networkings are played games, and more people's video callings or voice communication etc. can also It is carried out using mobile data network using downloading with single user, using application, using a series of application operatings such as unloading, user It is interacted by the mobile data network that base station covers with server 41 and server 42, to obtain candidate good friend's collection from server, Chat messages record, game, multimedia resources such as video or music etc. further include a relaying in order to ensure the network coverage 31, except of course that mobile data network, can also include WIFI network, not show in figure.

In the present embodiment, by taking user 11 as an example, user is seeing view using the search dog Video Applications installed on notebook Frequently, logging in and exit the time of the search dog Video Applications in record user's history is respectively at 9 points in the morning and 12 noon, and user 11 IP address, the geographical location etc. with longitude and latitude mark that user 11 is obtained by GPS positioning, when these information both include Between, it also include spatial information, an example of the as described spatio-temporal activity information, this is an example, unlimited depending on concrete condition In description here.

2) it is based on above method embodiment two-tri-, in one preferred embodiment of the embodiment of the present invention, in user generates User is searched in appearance with spatio-temporal activity information when server communication includes:

The time and/or IP address and/or cellular base station information of user and server active and passive communication and/or GPS Information and/or place name and/or WIFI information etc..

In the present embodiment, by taking user 15 as an example, user is played games using surfing Internet with cell phone, is needed this interior from server 42 Hold server and obtain its game resource stored, can just play games after downloading to game resource from server, certainly, server 42, in addition to storing game resource, can also store video, the multimedia messages such as audio.User is recorded actively to logical with server Letter, the time to server request game resource are 8 points at night, and it is on weekend that server timing, which recommends the time of video to user, 10 points of noon, the title of 15 geographic location of user, such as user 15 drink coffee in Startbuck, while online is played games, and record The entitled new middle Startbuck etc. closed in current position, it also includes spatial information that these information, which both include the time, and the as described space-time is living One example of dynamic information, only example depending on concrete condition is not limited to description here for this.

3) it is based on above method embodiment two-tri-, in one preferred embodiment of the embodiment of the present invention, in user generates User is searched in appearance in relation to the spatio-temporal activity information registered includes:

User registers the time that point of interest (POI, Point of interest) is put；And/or

User registers the geographical location of POI point；Wherein, the geographical location of POI point includes place name and/or latitude and longitude information.

POI information is an information word in geography information, be retail shop based on geography information, public service website and Bus station etc. builds or is capable of providing the information of the services sites of service.Usual each POI information may include services sites Title and/or the information such as corresponding code, the service type of offer and traffic.It can be by being pushed away to accurate user Its interested POI is recommended, to improve the user satisfaction of user, while it is corresponding to enable POI to be recommended that it is accurately positioned Success rate is recommended in potential user group and raising.In the present embodiment, by taking user 12 as an example, user 12 holds digital PDA and registers certainly Position where oneself, such as user have a meal in restaurant, can be to oneself current interested vegetable in public comment application software On evaluated and made a blueprint, POI information may include the name in restaurant, the speciality in restaurant, the geographical location in restaurant, and user registers With the time of comment, these information both include the time, also include spatial information, a reality of the as described spatio-temporal activity information Example, only example depending on concrete condition is not limited to description here for this.

4) it is based on above method embodiment two-tri-, in one preferred embodiment of the embodiment of the present invention, in user generates The spatio-temporal activity information of the related trip track of lookup user upload includes: in appearance

The starting point of user trajectory, the time of terminal and/or geographical location information；Wherein, the geographical location information packet Include POI and/or place name and/or latitude and longitude information；

The time of user trajectory approach point and/or geographical location information.

As shown in figure 5, including user 11- user 15 in social networks, the base station base station 21- 23 is respectively to user 11- user Administered user in 15 carries out signal transmitting and signal receives, it is ensured that user can be existed by the mobile data network that base station is supported It is exchanged in social networks, such as more people's chat clusters, more people's networkings are played games, and more people's video callings or voice communication etc. can also It is carried out using mobile data network using downloading with single user, using application, using a series of application operatings such as unloading, user It is interacted by the mobile data network that base station covers with server 41 and server 42, to obtain candidate good friend's collection from server, Chat messages record, game, multimedia resources such as video or music etc. further include a relaying in order to ensure the network coverage 31, except of course that mobile data network, can also include WIFI network, not show in figure.

It is to be herein pointed out 13 position of user changes, by starting point A, between a series of Origin And Destinations Point, if X1-X3 reaches home B, the position of user 12 also changes, and is reached home E by starting point D.

In the present embodiment, the starting point of user trajectory, terminal, there are also the intermediate trace points institutes between starting point and terminal Time and/or position, such as 10 points of the morning of 13 Saturday of user go up island coffee in a coffee-house-where starting point location A, The drink of coffee-house is commented on, is registered, navigation software is opened during walking, records intermediate trace points Latitude and longitude information, walking reach duck king restaurant, also record the latitude and longitude information where arrival time and duck king restaurant, these Information both includes the time, also includes spatial information, and an example of the as described spatio-temporal activity information, this is an example, depending on Concrete condition is not limited to description here.

It is used in one preferred embodiment of the embodiment of the present invention according to social networks based on above method embodiment two-tri- Family generates content UGC and obtains time and the frequency information that user's spatio-temporal activity information includes all access locations of user.

Embodiment of the method four:

Based on above method embodiment two to three, step 202 is specifically included:

Step 2021 will be related to the element of user's geographical location information, including log in IP, place name, POI, coordinate and WIFI Information uniformly converts longitude and latitude by alignment by union algorithm and/or place name coordinate database for these implicit spatial informations Information；

Step 2022, by global map gridding, generate the regular grid of 30 " * 30 " (being similar to 1km*1km)；

Step 2023, according to the movable coordinate information of user's history and frequency information, all spatio-temporal activity points of user are existed It is mapped on grid, with the coordinate for falling in grid element center coordinate substitution actual activity point, access to uniform grid point is fallen in The frequency adds up；

Step 2024, by the spatio-temporal activity point Unify legislation of all griddings obtained in step 201 be < L_x,p_x,f_x(t) >, L_xFor x-th point of coordinate (Lon_x,Lat_x), p_xFor the accumulative access frequency of x-th of grid points, f_xIt (t) is xth point in the time Frequency distribution in dimension；

Step 2025, according to the coordinate of user access point and the frequency of access point, using spatial interpolation algorithm (recommend instead away from From interpolation algorithm or ordinary kriging interpolation algorithm), interpolation radius is R₀(it is recommended as 30 ") generate user's space motion frequency point Cloth (density) figure Γ_x, the frequency values of grid m are Γ_x(m), given frequency threshold value H0 (recommending threshold value is 0.01), with grid space Motion frequency is H₀The curve surrounded is calculated as the spatio-temporal activity range boundary W of user_x。

In one preferred embodiment of the embodiment of the present invention, step 204 can according to the User Activity spatial dimension of acquisition and Density Distribution information calculates User Activity spatial distribution index of similarity Sim_area, it can be realized by following formula (1):

Wherein S_xAnd S_yRespectively indicate the spatio-temporal activity range boundary W of user x and y_xAnd W_yThe pixel set of covering.

Embodiment of the method five:

Based on above method embodiment two to four, step 203 is specifically included:

Step 2031 arranged from the low sequence of height according to its access frequency { p } to all access points of user { L } Access point set { < L after sequence₁,p₁,f₁(t)>,<L₂,p₂,f₂(t)>,<L₃,p₃,f₃(t)>,…<L_n,p_n,f_n(t)>}；

Step 2032 successively traverses the point that the access point after sorting in C1 is concentrated, and calculates accumulated probabilityUntil K-th point, so thatP0 is accumulated probability threshold value (recommending P0 is 95%), obtains user's frequentation and asks stationary point collection Θ={ < L₁,p₁,f₁(t)>,<L₂,p₂,f₂(t)>,<L₃,p₃,f₃(t)>,…<L_k,p_k,f_k(t)>}。

In one preferred embodiment of the embodiment of the present invention, step 205 can according to the User Activity spatial dimension of acquisition and Space-time trajectory sequence calculates user's space-time trajectory index of similarity Sim_route, it can be realized by following formula (2):

Wherein K indicates user Θ_xAnd Θ_yThe stationary point number of overlapping.

Embodiment of the method six:

This method embodiment is that the User Activity sky is obtained according to the spatial dimension and Density Distribution of the User Activity Between distribution similarity index, and then user's space-time trajectory phase is obtained according to the space-time trajectory sequence of user's common activities Like sex index, finally, pass through the User Activity spatial distribution index of similarity and user's space-time trajectory index of similarity User's sequence screening that candidate good friend concentrates is carried out, to therefrom find most matched target user, specific embodiment includes:

Step 301 generates content (UGC, Users Generate Content) acquisition user according to social network user Spatio-temporal activity information.

Here, user-generated content is Users Generate Content, is abbreviated as UGC.

Specifically, user-generated content includes user's open source information, individualized signature, the microblogging of publication, blog, reprints text Chapter, information of registering log in APP information, with server communication information etc..

Here, according to the user-generated content of social networks, during obtaining user's spatio-temporal activity information, space-time is obtained Action message includes one of such as under type or a variety of:

Mode one: the spatio-temporal activity letter that user logged in and exited server info generation is searched in user-generated content Breath.Specifically can log in and exit the log information of APP by recording user, log in and exit including user APP time and/or IP address and/or cellular base station information and/or GPS position information and/or WIFI information etc..

Mode two: the spatio-temporal activity information of the information of user and server communication is searched in user-generated content.Specifically The spatio-temporal activity sent in handshaking procedures can be kept according to set frequency and server during using APP by record user Information, including the continually changing spatio-temporal activity information of user, time and/or IP address and/or cellular base station letter including variation Breath and/or GPS position information and/or WIFI information etc..

Mode three: user is searched in user-generated content in relation to the spatio-temporal activity information registered.Record can specifically be passed through Register information of the user using APP active upload to server, the POI information registered including user and/or geographic coordinate information And/or temporal information and/or word content and/or pictorial information etc..

Mode four: spatio-temporal activity information of the user in relation to track of going on a journey is searched in user-generated content.Can specifically it pass through It records user and uses trace information of the APP active upload to server, the POI information of starting point and terminal including user trajectory And/or during temporal information and/or geographic coordinate information and/or User Activity in seconds the continually changing time and/ Or geographic coordinate information, by calculate acquire about the configuration information during User Activity, including average speed, acceleration Deng and/or the information stayed of user, the starting and terminate the time that geographical location and/or user including stationary point are stayed, and/ Or POI information near residence time and/or stationary point etc..

Step 302, user's spatio-temporal activity information according to acquisition, calculate the spatial dimension and Density Distribution of User Activity.

Wherein, the spatio-temporal activity information of user, space and time two corresponding with spatial position including User Activity The information of aspect.

The spatial information of the user obtained from user-generated content also includes implicit-null including explicit spatial information Between information.Explicit spatial information, that is, true latitude and longitude coordinates.Implicit spatial information can be turned by certain way Turn to the information of coordinate information.Implicit coordinate information includes IP address and/or place name and/or the base station that user logs in APP Position and/or POI information and/or WIFI information etc..

Implicit coordinate information by alignment by union algorithm and/or is based on place name coordinate database, needs to unite herein One is converted into explicit spatial information, i.e. latitude and longitude coordinates.

Here, the spatial dimension of User Activity is not the location information of user arrived, but passes through spatial point information Next space face information and frequency information with frequency interpolation.

Here, space interpolation does not utilize the latitude and longitude coordinates information and frequency information of luv space point directly, needs pair These points carry out geographic grid mapping and resampling.

Specifically, according to the spatio-temporal activity information of user, using spatial interpolation algorithm, obtain user's main activities range and Spatial Density Distribution, comprising:

A1, the element of user's geographical location information will be related to, including logs in IP, place name, POI, coordinate and WIFI information, By implicit spatial information, explicit space is uniformly converted into based on place name coordinate database and/or by alignment by union algorithm Information, i.e. latitude and longitude coordinates；

A2, by global map gridding, generate the regular grid of 30 " * 30 " (being similar to 1km*1km)；

A3, all spatio-temporal activity points of user are mapped and resampling on grid, to falling in uniform grid point Visitation frequency adds up, with the coordinate for falling in grid element center coordinate substitution actual activity point；

Here, the initial samples point obtained before carrying out the mapping and resampling, i.e., obtain according to practical longitude and latitude To the positions of all spatio-temporal activity points of user be properly termed as the first sampled point, as shown in fig. 6, where user 11- user 14 First sampled point constitutes sampled point set S1, and the sampled point obtained after carrying out the mapping and resampling is properly termed as Second sampled point, the second sampled point where user 11- user 14 constitute sampled point set S2, can be intuitive from Fig. 6 Find out the benefit by this mapping and resampling mode, i.e., are as follows: can be by initial more dispersed each user controllable Within the scope of the grid of mathematics scope carry out again in proportion mapping and resampling, will increase user appearance frequency and probability, In order to preferably carry out subsequent operation statistics.

A4, by the spatio-temporal activity point Unify legislation of all griddings obtained in step A be < L_x,p_x,f_x(t) >, L_xIt is Coordinate (the Lon of x point_x,Lat_x), p_xFor the accumulative access frequency of x-th of grid points, f_xIt (t) is xth point on time dimension Frequency distribution；

A5, according to the coordinate of user access point and the frequency of access point, utilize spatial interpolation algorithm (to recommend interpolation Algorithm or ordinary kriging interpolation algorithm), interpolation radius is R₀It is (close that (be recommended as 30 ") generates the distribution of user's space motion frequency Degree) figure Γ_x, the frequency values of grid m are Γ_x(m), given frequency threshold value H0 (recommending threshold value is 0.01), with grid space activity frequency Rate is H₀The curve surrounded is calculated as the spatio-temporal activity range boundary W of user_x；

For threshold value H0 between 0 and 1, threshold value is bigger, and user's main activities range of screening is smaller.

Step 303, user's spatio-temporal activity information according to acquisition, calculate the space-time trajectory sequence of User Activity.

Specifically, calculating the specific mistake of the space-time trajectory sequence of User Activity according to user's spatio-temporal activity information of acquisition Journey includes:

B1. all access points of user { L } are carried out from the low sequence of height, after being sorted according to its access frequency { p } Access point set { < L₁,p₁,f₁(t)>,<L₂,p₂,f₂(t)>,<L₃,p₃,f₃(t)>,…<L_n,p_n,f_n(t)>}；

B2. the point concentrated the access point after sorting in C1 is successively traversed, accumulated probability is calculatedUntil k-th Point, so thatP0 is accumulated probability threshold value (recommends P0 be 95%), obtain user's frequentation ask stationary point collection Θ=< L₁,p₁,f₁(t)>,<L₂,p₂,f₂(t)>,<L₃,p₃,f₃(t)>,…<L_k,p_k,f_k(t)>}；

Step 304 calculates User Activity spatial distribution according to the User Activity spatial dimension and Density Distribution information of acquisition Index of similarity.

Refer to specifically, calculating User Activity spatial distribution similitude according to User Activity spatial dimension and Density Distribution information Several detailed processes include:

C1. it is directed to specific user x, first has to obtain the candidate user collection in the space operation of the user with similitude Ω_x, to reduce operand.Whether candidate user collection can have with its main activities range and specified user's main activities range There is this index of overlapping to be judged.Since the main activities range of user is an irregular polygon, Spatial Overlap is being done Algorithms T-cbmplexity is higher when operation, can be substituted with the minimum outsourcing rectangle of scope of activities.

C2. to all user y in candidate user collection, the activity space point between specific user x and candidate user y is calculated Cloth index of similarity Sim_areaIt may be implemented by following formula (1):

Space-time trajectory between user is calculated in step 305, according to User Activity spatial dimension and Density Distribution information Index of similarity.

Refer to specifically, calculating space-time trajectory similitude between user according to User Activity spatial dimension and Density Distribution information Several detailed processes include:

D1. it is directed to specific user x, first has to obtain the candidate user collection in the space operation of the user with similitude Ω_x, step is the same as 0051.

D2. to all user y in candidate user collection, the space-time trajectory phase between specific user x and candidate user y is calculated Like sex index Sim_routeIt may be implemented by following formula (2):

In step 306, according to User Activity spatial distribution index of similarity and space-time trajectory index of similarity, to user's Candidate user collection is ranked up and is its commending friends.

Specifically, according to User Activity spatial distribution index of similarity and space-time trajectory index of similarity, to the time of user Selection family collection is ranked up and is that the detailed process of its commending friends includes:

E1. it is directed to specific user x, to its good friend's candidate collection Ω_xInterior all user y (y ∈ Ω_x), according to user y and x it Between User Activity spatial distribution index of similarity, be ranked up from height is low, user successively recommended under specific user.

E2. and/or it is directed to specific user x, to its good friend's candidate collection Ω_xInterior all user y (y ∈ Ω_x), according to user y User Activity space-time trajectory index of similarity between x, is ranked up from height is low, user is successively recommended specific user Under.

The embodiment of the present invention is sampled, by obtaining user's spatio-temporal activity information in user-generated content, is obtained more true Real User Activity spatial dimension, Spatial Density Distribution and space-time track sets, have overlapping to specific user's main activities range All users, based on activity space distribution similarity index and/or space-time trajectory index of similarity between user, according to similar Property is from the low sequence of height to specific user's commending friends.Activity space has height between user obtained by the embodiment of the present invention Plyability, User Activity habit have high similarity, are conducive to improve friend recommendation acceptance.

It need to be noted that: the description of following electronic equipment item, with the above method description be it is similar, with method Beneficial effect description, does not repeat them here.For undisclosed technical detail in electronic equipment embodiment of the present invention, the present invention is please referred to The description of embodiment of the method.

Server example one:

The embodiment of the invention provides a kind of servers, as shown in fig. 7, server 401 includes:

Module 4011 is obtained, for obtaining user's spatio-temporal activity information of each user in group according to user-generated content；

First determining module 4012, for determining the first information according to user's spatio-temporal activity information, according to described One information determines the first screening parameter；The first information is for characterizing user in the variation of Spatial Dimension；

Second determining module 4013, for determining the second information according to user's spatio-temporal activity information, according to described Two information determine the second screening parameter；Second information is for characterizing user in the variation of time dimension；

Processing module 4015, for concentrated according to preset strategy from screening parameter choose first screening parameter and/or Second screening parameter, according to first screening parameter and/or second screening parameter from first in the group It is filtered out in the corresponding candidate user group of user and the most matched target user of first user.

In one preferred embodiment of the embodiment of the present invention, the server further include:

Third determining module 4014, for determining that third is sieved according to first screening parameter and second screening parameter Select parameter；

Processing module 4015 is further used for that the screening parameter concentration is written the third screening parameter into, further According to first screening parameter and/or second screening parameter and/or the third screening parameter from the group It is filtered out in the corresponding candidate user group of first user and the most matched target user of first user.

In one preferred embodiment of the embodiment of the present invention, the acquisition module is further used for using including with lower section User's spatio-temporal activity information of each user in one or more acquisition groups of formula:

In one preferred embodiment of the embodiment of the present invention, the acquisition module further include:

In one preferred embodiment of the embodiment of the present invention, first determining module further include:

In one preferred embodiment of the embodiment of the present invention, second determining module further include:

Server example two:

The embodiment of the invention provides a kind of servers, are based on server example one, with a specific social networks neck For the application in domain, such as blog, space, microblogging, wechat, in time communication etc., wherein any one is all constituted based on user Complicated social networks；

Under this application scenarios, as shown in figure 8, the server for the information processing that the present invention is used for is actually a kind of base In the distribution of user's space scope of activities and the friend recommendation scheme of space-time trajectory similitude, the server can be recommendation service Device, Fig. 8 are to be different from internal module composite structural diagram, are server another kind structure chart described in the present embodiment, such as Fig. 8 institute Show, the server includes processor 502, storage medium 504 and at least one external communication interface 501；The processor 502, storage medium 504 and external communication interface 501 are connected by bus 503.The processor 502 can be micro process Device, central processing unit, digital signal processor or programmable logic array etc. have the electronic component of processing function.

The external communication interface 501 is used to carry out information exchange with other electronic equipments, such as is led to client Letter, is communicated with other network servers.The bus 503 is the connecting component of server internal.

The processor 502 controls the external communication interface, storage medium and total by running executable instruction The information processing inside information exchange and the processor 502 between line, realizes the function of above-mentioned each unit.

Server example three:

Based on the application scenarios of above-mentioned server example two, Fig. 9 is the server block diagram for friend recommendation, server 601 include:

Obtain module 6011, similarity computing module 6012, friend recommendation module 6013, in which:

Module 6011 is obtained, for the user-generated content according to social networks, obtains and update the spatio-temporal activity of user Information；

Similarity computing module 6012 calculates the spatio-temporal activity phase between user for the spatio-temporal activity information according to user Like sex index；

Friend recommendation module 6013, for according to the spatio-temporal activity index of similarity between user, according to index of similarity Just, recommend the good friend with similar active space and similar habit to target user；

The spatio-temporal activity information of user is obtained by acquisition module 6011 and updated according to the user-generated content of social networks, Spatio-temporal activity index of similarity between user is calculated by similarity computing module 6012, user is based on by friend recommendation module 6013 Main activities range, Density Distribution and space-time track sets, to user's main activities range have overlapping candidate user, meter The index of similarity for calculating candidate user and target user's spatial distribution and/or space-time trajectory sequence, according to the height of index of similarity It is low, recommend the good friend with similar active space and similar habit to target user.Through the embodiment of the present invention, good friend can be improved The accuracy rate and user's acceptance of recommendation are conducive to improve and recommend efficiency.

In one preferred embodiment of the embodiment of the present invention, still as shown in figure 9, to module 6011, Similarity measures is obtained Internal module in module 6012, friend recommendation module 6013 is described as follows:

Module 6011 is obtained to specifically include:

Submodule 60111 is searched, the spatio-temporal activity letter of user is searched for the user generated content (UGC) in social networks Breath；

Acquisition submodule 60112 obtains the spatio-temporal activity letter of user for the user generated content (UGC) in social networks Breath.

Wherein, the lookup submodule 60111 specifically includes:

Parsing subunit 601111: for believing the implicit space such as place name, POI, IP address, the address WIF, base station location Breath resolves to explicit spatial information, i.e. latitude and longitude coordinates；

Generate subelement 601112: for generating and updating the spatio-temporal activity information of user, the moving position new to user Geographic grid space reflection is carried out, and frequency update and Annual distribution frequency are carried out more to the geographic grid of user's history behaviour area Newly；

Wherein, the similarity computing module 6012 specifically includes:

Screening submodule 60121: for the spatio-temporal activity information according to social network user, the main space of user is calculated Scope of activities, Density Distribution and space-time track sets obtain the time for having plyability with target user's main space scope of activities Select family collection；

First similarity computational submodule 60122: for calculating candidate user and mesh in target user's candidate user collection Mark User Activity spatial distribution index of similarity；And/or

Second similarity computational submodule 60123: for calculating candidate user and mesh in target user's candidate user collection Mark user's space-time trajectory index of similarity；

Wherein, the friend recommendation module 6013 specifically includes:

First recommends submodule 60131: being used in target user's candidate user collection, according to candidate user and target user The activity space distribution similarity index sequence low from height, to target user's commending friends；And/or

Second recommends submodule 60132: being used in target user's candidate user collection, according to candidate user and target user The activity space-time trajectory index of similarity sequence low from height, to target user's commending friends.

It is to be herein pointed out obtaining module 6011 according to the user generated content (UGC) of social networks, when obtaining user Empty action message logs in and exits the spatio-temporal activity letter of server info generation including searching user in user-generated content Breath, the spatio-temporal activity information of the information of user and server communication, the related spatio-temporal activity information registered of user, user's upload Spatio-temporal activity information in relation to track of going on a journey, resolving to explicit spatial information to user concealed spatial information, (longitude and latitude is sat Mark), and geographic grid space reflection is carried out according to user coordinates, the frequency that counting user historical act map in geographic grid with Annual distribution frequency distribution.The activity space range and Spatial Density Distribution that user is calculated by similarity computing module 6012, are obtained The candidate user collection that there is plyability with target user's main space scope of activities is taken, according to the Spatial Density Distribution of User Activity And space-time track sets, it calculates candidate user and target user's activity space is distributed and/or space-time trajectory sequence similarity index. By friend recommendation module 6013, according to candidate user and target user's activity space is distributed and/or space-time trajectory sequence similarity Index height, recommends the good friend with similar active space and/or similar habit to target user.Use can be caught through the invention Known strange human psychological is found at family, chance height is met under the good friend's acceptance and line of recommendation, when the friend relation of formation is maintained Between it is long, can be improved the accuracy rate and user's acceptance of friend recommendation, further extension friend relation circle and improve friend relation net Network structure.

In several embodiments provided herein, it should be understood that disclosed device and method can pass through it Its mode is realized.Apparatus embodiments described above are merely indicative, for example, the division of the unit, only A kind of logical function partition, there may be another division manner in actual implementation, such as: multiple units or components can combine, or It is desirably integrated into another system, or some features can be ignored or not executed.In addition, shown or discussed each composition portion Mutual coupling or direct-coupling or communication connection is divided to can be through some interfaces, the INDIRECT COUPLING of equipment or unit Or communication connection, it can be electrical, mechanical or other forms.

Above-mentioned unit as illustrated by the separation member, which can be or may not be, to be physically separated, aobvious as unit The component shown can be or may not be physical unit, it can and it is in one place, it may be distributed over multiple network lists In member；Some or all of units can be selected to achieve the purpose of the solution of this embodiment according to the actual needs.

In addition, each functional unit in various embodiments of the present invention can be fully integrated in one processing unit, it can also To be each unit individually as a unit, can also be integrated in one unit with two or more units；It is above-mentioned Integrated unit both can take the form of hardware realization, can also realize in the form of hardware adds SFU software functional unit.

Those of ordinary skill in the art will appreciate that: realize that all or part of the steps of above method embodiment can pass through The relevant hardware of program instruction is completed, and program above-mentioned can be stored in a computer readable storage medium, the program When being executed, step including the steps of the foregoing method embodiments is executed；And storage medium above-mentioned include: movable storage device, it is read-only Memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or The various media that can store program code such as person's CD.

If alternatively, the above-mentioned integrated unit of the present invention is realized in the form of software function module and as independent product When selling or using, it also can store in a computer readable storage medium.Based on this understanding, the present invention is implemented Substantially the part that contributes to existing technology can be embodied in the form of software products the technical solution of example in other words, The computer software product is stored in a storage medium, including some instructions are used so that computer equipment (can be with It is personal computer, server or network equipment etc.) execute all or part of each embodiment the method for the present invention. And storage medium above-mentioned includes: that movable storage device, ROM, RAM, magnetic or disk etc. are various can store program code Medium.

The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain Lid is within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.

Claims

1. a kind of information processing method, which is characterized in that the described method includes:

The first information is determined according to user's spatio-temporal activity information, and the first screening parameter is determined according to the first information；Institute The first information is stated for characterizing user in the variation of Spatial Dimension；

The second information is determined according to user's spatio-temporal activity information, and the second screening parameter is determined according to second information；Institute The second information is stated for characterizing user in the variation of time dimension；

It is concentrated according to preset strategy from screening parameter and chooses first screening parameter and/or second screening parameter, according to First screening parameter and/or second screening parameter are from the corresponding candidate user group of the first user in the group Filter out with the most matched target user of first user, the target user includes potential good friend；

Wherein, the first information is the spatial dimension and Density Distribution of User Activity in social networks, corresponding first obtained Screening parameter is User Activity spatial distribution index of similarity；Second information is the space-time trajectory sequence of user in social networks Column, corresponding the second obtained screening parameter are user's space-time trajectory index of similarity；

The spatio-temporal activity point of gridding in the space-time trajectory sequence is < L_x,p_x,f_x(t) >, L_xFor x-th point of coordinate, p_xFor The accumulative access frequency of x-th of grid points, f_xIt (t) is frequency distribution of the xth point on time dimension.

2. the method according to claim 1, wherein the method also includes:

The screening parameter is written in the third screening parameter to concentrate, further according to first screening parameter and/or institute The second screening parameter and/or the third screening parameter is stated to sieve from the corresponding candidate user group of the first user in the group It selects and the most matched target user of first user.

3. according to the method described in claim 2, it is characterized in that, described obtain each user in group according to user-generated content User's spatio-temporal activity information, including the one or more of following manner:

Mode one: user is searched in the user-generated content and logs in and exit spatio-temporal activity information caused by server；

Mode four: user is searched in the user-generated content and uploads spatio-temporal activity information caused by related trip track.

4. according to the method described in claim 3, it is characterized in that, the lookup user in the user-generated content logs in With exit spatio-temporal activity information caused by server, comprising:

The spatio-temporal activity information includes at least: user's history logs in and exits the temporal information and/or Internet protocol using APP IP address information and/or cellular base station information and/or GPS information and/or information of place names and/or WIFI information.

5. according to the method described in claim 3, it is characterized in that, described search user and clothes in the user-generated content Business device communicates generated spatio-temporal activity information

The information sent in handshaking procedures is kept to look into according to assigned frequency and server during using APP by record user Find the spatio-temporal activity information；

The spatio-temporal activity information includes at least: user and server actively and the time of passive communication and/or IP address and/or Cellular base station information and/or GPS information and/or place name and/or WIFI information.

6. according to the method described in claim 3, it is characterized in that, the lookup user in the user-generated content is related Spatio-temporal activity information caused by registering；

The spatio-temporal activity information is obtained using the information searching of registering of APP active upload to server by record user；

The spatio-temporal activity information includes at least: user register point of interest POI information and/or temporal information and/or geographical position Confidence breath and/or text information and/or pictorial information.

7. according to the method described in claim 3, it is characterized in that, described search user's upload in the user-generated content Spatio-temporal activity information caused by related trip track includes:

It searches to obtain the spatio-temporal activity information using the trace information of APP active upload to server by recording user；

8. according to the method described in claim 2, it is characterized in that, described determine first according to user's spatio-temporal activity information Information, comprising:

The extraction of spatial information of Spatial Dimension involved in user's spatio-temporal activity information is come out, and isolates explicit space Information and implicit spatial information；

After converting explicit spatial information for the implicit spatial information, adopted using the explicit spatial information as first Sampling point simultaneously obtains the second sampled point of gridding by mesh mapping resampling；

By second sampled point according to the coordinate of user access point and the frequency of access point, generated by preset interpolation strategies The spatial dimension and Density Distribution of User Activity, and using the spatial dimension of the User Activity and Density Distribution as described first Information.

9. according to the method described in claim 8, it is characterized in that, described determine that the first screening is joined according to the first information Number, comprising:

Judge first user scope of activities whether with the scope of activities of at least one alternative candidate user group there are Chong Die, Obtain judging result；

The judging result is that when there is overlapping, the candidate user group of overlapping will be present as time corresponding with first user Select user group；

Obtain all users in candidate user group corresponding with first user；

According to all users described in the spatial dimension of the User Activity and Density Distribution operation respectively with first user it Between User Activity spatial distribution index of similarity, and using the User Activity spatial distribution index of similarity as described first Screening parameter.

10. according to the method described in claim 2, it is characterized in that, described determine according to user's spatio-temporal activity information Two information, comprising:

The extraction of spatial information of time dimension involved in user's spatio-temporal activity information is come out, to the spatial information extracted In all access points of user carry out access point set from high to Low sequence, after being sorted according to its access frequency；

Each point that access point after successively traversing the sequence is concentrated, obtains the accumulated probability of each point, when each point Accumulated probability be greater than a threshold value when, will be greater than the threshold value point be denoted as user reside access point；

The space-time trajectory sequence that access point generates user's common activities is resided by the user after traversal, and by the user The space-time trajectory sequence of common activities is as second information.

11. according to the method described in claim 10, it is characterized in that, described determine that the second screening is joined according to second information Number, comprising:

Obtain all users in candidate user group corresponding with first user；

According to all users described in the space-time trajectory Sequence Operation Theory of user's common activities respectively between first user User's space-time trajectory index of similarity, and using user's space-time trajectory index of similarity as second screening parameter.

12. a kind of server, which is characterized in that the server includes:

First determining module, it is true according to the first information for determining the first information according to user's spatio-temporal activity information Fixed first screening parameter；The first information is for characterizing user in the variation of Spatial Dimension；

Second determining module, it is true according to second information for determining the second information according to user's spatio-temporal activity information Fixed second screening parameter；Second information is for characterizing user in the variation of time dimension；

Processing module chooses first screening parameter and/or described second for concentrating according to preset strategy from screening parameter Screening parameter, it is corresponding from the first user in the group according to first screening parameter and/or second screening parameter Candidate user group in filter out with the most matched target user of first user, the target user includes potential good friend；

13. server according to claim 12, which is characterized in that the server further include:

Third determining module, for determining third screening parameter according to first screening parameter and second screening parameter；

Processing module is further used for that the screening parameter concentration is written the third screening parameter into, further according to First screening parameter and/or second screening parameter and/or the third screening parameter are from the first user in the group It is filtered out in corresponding candidate user group and the most matched target user of first user.

14. server according to claim 13, which is characterized in that the acquisition module is further used for using including User's spatio-temporal activity information of each user in one or more acquisition groups of following manner:

15. server according to claim 14, which is characterized in that the acquisition module further include:

First searches submodule, when searching to obtain described using the log information of APP for logging in and exiting by record user Empty action message；

16. server according to claim 14, which is characterized in that the acquisition module further include:

Second searches submodule, for keeping connecting according to assigned frequency and server during using APP by record user The information searching sent during logical obtains the spatio-temporal activity information；

17. server according to claim 14, which is characterized in that the acquisition module further include:

Third searches submodule, lives for the related generated space-time of registering of user of searching in the user-generated content Dynamic information；

18. server according to claim 14, which is characterized in that the acquisition module further include:

4th searches submodule, for searching to obtain using the trace information of APP active upload to server by record user The spatio-temporal activity information；

19. server according to claim 13, which is characterized in that first determining module further include:

First extracting sub-module, for going out the extraction of spatial information of Spatial Dimension involved in user's spatio-temporal activity information Come, and isolates explicit spatial information and implicit spatial information；

Mapping submodule, after converting explicit spatial information for the implicit spatial information, by the explicit sky Between information as the first sampled point and by mesh mapping resampling obtain the second sampled point of gridding；

The first information generate submodule, for by second sampled point according to the coordinate of user access point and the frequency of access point Rate generates the spatial dimension and Density Distribution of User Activity by preset interpolation strategies, and by the space of the User Activity Range and Density Distribution are as the first information.

20. server according to claim 19, which is characterized in that first determining module further include:

First judging submodule, for judge first user scope of activities whether at least one alternative candidate user group Scope of activities exist overlapping, obtain judging result；The judging result is that when there is overlapping, the candidate user of overlapping will be present Group is as candidate user group corresponding with first user；

First similarity exponent arithmetic submodule, for according to the spatial dimension of the User Activity and Density Distribution operation All users User Activity spatial distribution index of similarity between first user respectively, and the User Activity is empty Between distribution similarity index as first screening parameter.

21. server according to claim 13, which is characterized in that second determining module further include:

Second extracting sub-module, for going out the extraction of spatial information of time dimension involved in user's spatio-temporal activity information Come, all access points of user in the spatial information extracted obtain from high to Low sequence according to its access frequency Access point set after sequence；

Traversal searches submodule, and each point concentrated for successively traversing the access point after the sequence obtains the tired of each point Probability is counted, when the accumulated probability of each point is greater than a threshold value, the point that will be greater than the threshold value is denoted as the resident access of user Point；

Second information generate submodule, for traverse after by the user reside access point generation user's common activities when Empty track sets, and using the space-time trajectory sequence of user's common activities as second information.

22. server according to claim 21, which is characterized in that second determining module further include:

Second judgment submodule, for judge first user scope of activities whether at least one alternative candidate user group Scope of activities exist overlapping, obtain judging result；The judging result is that when there is overlapping, the candidate user of overlapping will be present Group is as candidate user group corresponding with first user；

Second similarity exponent arithmetic submodule, for the institute according to the space-time trajectory Sequence Operation Theory of user's common activities There is user space-time trajectory index of similarity of the user respectively between first user, and user's space-time trajectory is similar Sex index is as second screening parameter.