CN102135983A - Group dividing method and device based on network user behavior - Google Patents
Group dividing method and device based on network user behavior Download PDFInfo
- Publication number
- CN102135983A CN102135983A CN2011100091670A CN201110009167A CN102135983A CN 102135983 A CN102135983 A CN 102135983A CN 2011100091670 A CN2011100091670 A CN 2011100091670A CN 201110009167 A CN201110009167 A CN 201110009167A CN 102135983 A CN102135983 A CN 102135983A
- Authority
- CN
- China
- Prior art keywords
- user
- scope
- point
- control number
- space
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The invention discloses a group dividing method and a device based on network user behavior. The method comprises the following steps: determining a behavior characteristic parameter set according to user requirement; constructing a user type space according to the determined behavior characteristic parameter set; reading data from a user behavior server, normalizing various parameters of each user, forming a user constellation diagram in the user type space, initializing each point in the constellation diagram, and determining a searching range; calculating a moving distance vector according to the distance from points in the searching range of the point to the point, and updating the searching range according to the moving distance vector; repeating the performed steps until all points are fixed; and forming a user group by adjacent points according to the initial searching range.
Description
Technical field
The present invention relates to the Network Users'Behaviors Analysis field, particularly a kind of method and apparatus of realizing analysis user business conduct characteristic and rule.
Background technology
At present, along with Internet user's increase rapidly, Internet service is also abundant thereupon, different professional corresponding different crowds.Therefore, allow a business be fit to more its respective user just needs carry out colony's division to using this professional user, improve existing business targetedly according to different customer groups then.The customer group partitioning technology is a gordian technique of following user behavior analysis.
Customer group division methods of the prior art, mainly be based on the division methods of the logic-based link of LM (Link Mining links excavation), this method is unfavorable for that the multi-service intersection is used in communication network, make analysis under internet and the multiple user's of non-internet the situation, simultaneously, excessive program complexity makes that also this method range of application is limited.
Summary of the invention
The embodiment of the invention provides the colony's division methods and the device of user behavior Network Based, customer group is divided more meet communication network monitoring situation and satisfy user's specific (special) requirements, has enlarged usable range simultaneously.
The embodiment of the invention discloses a kind of colony's division methods of user behavior Network Based, comprising: determine the cybernetics control number collection; Make up the user type space according to determined cybernetics control number collection again, from the user behavior server, read in data, after the multiple parameter normalization of each user, in the user type space, form user's planisphere, each point in the planisphere is carried out initialization and determines the scope of detecting,, upgrade the scope of detecting according to the displacement vector simultaneously according to detect point in the scope and the distance calculation displacement vector of itself at this point, repeat above step, up to have a few and not move; According to initially detecting scope, contiguous point is constituted a customer group.
The embodiment of the invention also discloses a kind of device of colony's division of user behavior Network Based, it is characterized in that, comprising:
The parameter set determining unit is used for determining the cybernetics control number collection;
The space determining unit is used for determining the user type space according to the cybernetics control number collection;
Cluster cell, from the user behavior server, read in data, after the multiple parameter values normalization of each user, in the user type space, form user's planisphere and determine the scope of detecting, according to detect point in the scope and the distance calculation displacement vector of itself at this point, upgrade simultaneously and detect scope, repeat above step, have a few mobile up to institute according to the displacement vector
Group's division unit is used for according to initially detecting scope contiguous point being constituted a customer group.
From the embodiment of the invention described above as can be seen, the user behavior space of the embodiment of the invention can change has satisfied the request for utilization of communication network multi-service intersection, introduce the corresponding relation of user's requirement as the cybernetics control number collection, therefore importance degree between the expression parameter has considered user's specific (special) requirements.Clustering method of the present invention is not confined to colony's division of the network user simultaneously, has enlarged the scope of application.
Description of drawings
Fig. 1 realizes an embodiment process flow diagram of customer group division methods for the present invention;
Fig. 2 realizes another embodiment process flow diagram of the method for network selecting for the present invention;
Fig. 3 is the process flow diagram of distance vector clustering method of the present invention;
Fig. 4 realizes an example structure figure of customer group classification apparatus for the present invention.
Embodiment
Below in conjunction with accompanying drawing the embodiment of the invention is described in detail.
See also Fig. 1, realize an embodiment process flow diagram of the method for network selecting for the present invention, may further comprise the steps:
Step 101: determine the cybernetics control number collection;
Step 102:, make up the user type space according to fixed cybernetics control number collection;
Step 103: from the user behavior server, read in data, after the multiple parameter normalization of each user, in the user type space, form user's planisphere, each point in the planisphere is carried out initialization and determines the scope of detecting, according to detect point in the scope and the distance calculation displacement vector of itself at this point, upgrade simultaneously and detect scope, repeat above step, have a few mobile up to institute according to the displacement vector;
Step 104:, contiguous point is constituted a customer group according to initially detecting scope;
The foregoing description reads in data from the user behavior server in customer group is divided, after the multiple parameter values normalization of each user, in the user type space, form user's planisphere and determine the scope of detecting, according to detect point in the scope and the distance calculation displacement vector of itself at this point, upgrade the scope of detecting according to the displacement vector simultaneously, repeat above step, up to have a few and not move, thereby reach the user clustering effect.Wherein, the user behavior space of the embodiment of the invention can change the requirement of having satisfied finite data, introduces the corresponding relation of user's requirement as the cybernetics control number collection, and therefore the importance degree between the expression parameter has considered the service developer requirement.Clustering method of the present invention is not confined to colony's division of the network user simultaneously, has enlarged the scope of application.
See also Fig. 2, realize another embodiment process flow diagram of the method that customer group is divided for the present invention.In the present embodiment,, obtain the information that the user pays close attention to by user interface.In the present embodiment, cybernetics control number is stored in UBAS, such as user's static types and the dynamic topic of user, has also made dividing region at the IP address, is may further comprise the steps when the user need divide customer group:
Step 201: customer group classification apparatus UGDD (User Group Diving Device) obtains with the user from current UBAS (User Behavior analysis Server) and requires and each cybernetics control number, according to the corresponding relation between user's requirement and the cybernetics control number collection, determine corresponding cybernetics control number collection.
Wherein UGDD is the ingredient of current UBAS, has a UGDD among each UBAS at least.
In order to determine the corresponding relation between cybernetics control number collection and the user requirement, before dividing, customer group reads in user's much-talked-about topic and attention rate in advance: " Diaoyu Island; 1.0 ", " Japan; 0.6 ", " China; 0.8 " user's static types and attention rate: " blog, 0.5 ", " news, 0.9 ", the region is: " Henan ", the time is: 20100712 require the various actions characteristic parameter that disposed among data and the UBAS as the user.
So the cybernetics control number collection of choosing in the present embodiment is:
Table one requires resulting cybernetics control number collection according to the user
Step 202:UGDD according to the cybernetics control number collection, makes up the user type theorem in Euclid space, determines the normalization standard simultaneously.
Above-mentioned structure user type theorem in Euclid space is to concentrate at the behavior characteristic parameter, removes " time " and " region " two parameters, also has 5 parameters, so make up 5 dimension coordinate theorem in Euclid space this moment, 5 coordinate axis are respectively: Diaoyu Island axle, Japan's axle, China's axle, blog axle and news axle.
Above-mentioned definite normalization standard S=(1.0,0.6,0.8,0.5,0.9).
Step 203:UGDD is reading of data from UBAS, by normalization standard normalization user data, forms planisphere in the user type space, with distance vector clustering algorithm cluster, similar users is concentrated
Above-mentioned UGDD reading of data from UBAS by normalization standard normalization user data is:
UGDD reads the data in 20100712 Henan in UBAS result is total T user, and each user of this T user has separately numerical value for 5 coordinate axis in 202, and user i can be expressed as at this moment
According to normalization standard S=(1.0,0.6,0.8,0.5,0.9), by formula
With the normalization per family of this T usefulness, obtaining user i is IP
i=(p
I1, p
I2..., p
In), at this moment this T user to be clicked and entered in the user type space and form planisphere, each is put according to formula,
Calculate it and initially detect scope w
0, scope w is detected in order
i=w
0, minimum is detected scope w
Min=w
0/ 4.
Above-mentioned distance vector clustering algorithm cluster, the specific implementation that similar users is concentrated sees also Fig. 3, may further comprise the steps:
Step 301: determine that L represents vector length, d in this n dimension theorem in Euclid space
IjThe distance of expression point i and j;
In the present embodiment, this n dimension theorem in Euclid space is exactly the user type space
Step 302: calculate mobile route;
If the some i with the some j apart from d
Ij＜w claims that then neighbor point or the some i of some j for some i is the neighbor point of j, the mobile route d of some i
iPass through formula
Calculate and get;
Step 303: cluster moves;
Make L
DiBe mobile route d
iLength, make ID
iBe ID
i+ d
iMove, upgrade simultaneously and detect scope, make w
i=L
DiEach point in the space is carried out once above-mentioned moving;
Step 304: mobile end judgement;
When have a few when not mobile, cluster finishes, and finishes the back similar users and has just concentrated.
Step 203:UGDD constitutes a customer group according to initially detecting scope with contiguous point. simultaneously the result is fed back to UBAS;
Initially the scope of detecting is w
0, each some i searches neighbor point according to initially detecting scope, will put i and neighbor point thereof and be made as a group, repeats above-mentioned probe procedure, if this point has been included into a group and has not then detected, all nodes all are included into the group back to be finished; The network user group who obtains dividing.
Each customer group that UGDD will divide deposits among the UBAS.
Can find out that from the foregoing description user behavior of the present invention space can change, the space that the cybernetics control number data are generated more after a little while in UBAS also can be less, satisfied the requirement of finite data, introduce the corresponding relation of user's requirement as the cybernetics control number collection, therefore importance degree between the expression parameter has considered the service developer requirement.Clustering method of the present invention is not confined to colony's division of the network user simultaneously, has enlarged the scope of application.
Above embodiment is the source of behavioural characteristic data with current user behavior analysis server UBAS, but the invention is not restricted to this two analytical models, when not being network behavior feature but other behavioural characteristics when behavioural characteristic, its customer group division methods and the foregoing description are similar, repeat no more herein.See also Fig. 4, for the present invention realizes an example structure figure of the device that customer group is divided, this device comprises parameter set determining unit 401, space determining unit 402, cluster cell 403, group's division unit 404
Parameter set determining unit 401 is used for according to customer requirements, determines the cybernetics control number collection;
This device also comprises:
Group's division unit 404 is used for the result according to cluster cell 403 gained, utilizes the scope of initially detecting, and contiguous point is constituted a customer group.
In the present embodiment, does not limit to and internet behavioural characteristic requirement in the user behavior space, introduce the corresponding relation of user's requirement as the cybernetics control number collection, importance degree between the expression parameter, satisfy user's specific (special) requirements, considered the situation that communication network multi-service intersection is used simultaneously.Clustering method of the present invention is not confined to colony's division of the network user simultaneously, has enlarged the scope of application.
One of ordinary skill in the art will appreciate that all or part of step that realizes in the foregoing description method, be to instruct relevant hardware to finish by program, described program can be stored in the computer read/write memory medium, this program comprises the steps: the requirement according to the user, determines the cybernetics control number collection; According to fixed cybernetics control number collection, make up the user type space; From the user behavior server, read in data, after the multiple parameter normalization of each user, in the user type space, form user's planisphere, each point in the planisphere is carried out initialization and determines the scope of detecting, according to detect point in the scope and the distance calculation displacement vector of itself at this point, upgrade simultaneously and detect scope, repeat above step, have a few mobile up to institute according to the displacement vector; According to initially detecting scope, contiguous point is constituted a customer group.Described storage medium, as: ROM/RAM, magnetic disc, CD etc.
The above only is a preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (9)
1. colony's division methods of a user behavior Network Based is characterized in that, comprises
Determine the cybernetics control number collection;
According to fixed cybernetics control number collection, make up the user type space;
From the user behavior server, read in data, after the multiple parameter normalization of each user, in the user type space, form user's planisphere, each point in the planisphere is carried out initialization and determines the scope of detecting, according to detect point in the scope and the distance calculation displacement vector of itself at this point, upgrade simultaneously and detect scope, repeat above step, have a few mobile up to institute according to the displacement vector;
According to initially detecting scope, contiguous point is constituted a customer group.
2. method according to claim 1 is characterized in that, also comprises before described definite cybernetics control number:
In predetermined cybernetics control number scope, according to user's the needs setting and the corresponding relation of current behavior characteristic parameter collection;
Then described definite current behavior characteristic parameter collection is for obtaining the dynamic topic of user, user's static types and IP address from user behavior analysis server UBAS (User Behavior Analysis Server), according to user's the needs and the corresponding relation of current behavior characteristic parameter collection, determine the corresponding cybernetics control number collection of needs with the user;
3. method according to claim 2 is characterized in that, described cybernetics control number scope comprises:
The dynamic topic of user is by being used the determined keyword of Network by the user in a period of time in the user behavior server, this keyword can since the user who is analyzed for geographic position and time of use business different and different;
User's static types is meant the professional type of using, and comprising: news, physical culture, amusement, science and technology, finance and economics, automobile, number, mobile phone, house property, recreation, tourism, education, 13 classes of blog; These classifications are to add up by the historical data of user behavior server to draw.
4. method according to claim 2 is characterized in that, the user requires to comprise:
To degree of concern some or the dynamic topic of several users or user's static types, the selection of time period, the selection of geographic area scope.
5. method according to claim 1 is characterized in that, described definite cybernetics control number collection comprises:
Obtain with the user from UBAS and to require corresponding behavioural analysis parameter set.
6. according to claim 1,2 or 5 any described methods, it is characterized in that,, make up the user type space and comprise according to fixed cybernetics control number collection:
This user type space is a theorem in Euclid space;
With the orthogonal axis in the dynamic topic structure of user's static types and user in the parameter set space;
User's static types and the dynamic topic quantity of user sum n are called range parameter;
With the attention rate of each user's static types and the dynamic topic of user in the parameter set as data normalization standard S=(s
1, s
2..., s
n);
7. according to claim 1,2 or 5 any described methods, it is characterized in that, describedly from the user behavior server, read in data, after the multiple parameter values normalization of each user, form user's planisphere and determine the scope of detecting in the user type space, according to the point and the distance calculation displacement vector of itself detected at this point in the scope, scope is detected in renewal according to the displacement vector simultaneously, repeat above step, up to have a few not move and comprise:
To from the user behavior server, reading in data, after the multiple parameter values normalization of each user, in the user type space, form user's planisphere and determine the scope of detecting according to:
From the user behavior server, read each user i data and indicate this user, obtain data set with the IP address
According to number
According to normalization standard S=(s
1, s
2..., s
n), by formula
Normalization,
Each parameter of user i obtains IP
i=(p
I1, p
I2..., p
In) simultaneously, click and enter in the user type space,
Form planisphere, each is put according to formula,
Calculate its initial spy
Look into scope w
0, scope w is detected in order
i=w
0, minimum is detected scope w
Min=w
0/ 4.
To according to point and the distance calculation displacement vector of itself detected at this point in the scope, upgrade according to the displacement vector simultaneously and detect scope, repeat above step, up to have a few mobilely according to the distance vector clustering algorithm, carry out mobile cluster;
The vector clustering algorithm of adjusting the distance carries out according to following steps:
A) in this n dimension theorem in Euclid space, L represents vector length, d
IjThe distance of expression point i and j;
B) if the some i with the some j apart from d
Ij＜w claims that then neighbor point or the some i of some j for some i is j
Neighbor point, the some i mobile route d
iBy
Calculate and get, simultaneously, make L
DiBe mobile route d
iLength, make ID
iBe ID
i+ d
iMove, upgrade simultaneously and detect scope, make w
i=L
DiEach point in the space is carried out once above-mentioned moving;
C) repeat b), when institute has a few when not mobile the cluster end;
8. according to claim 1,2,5,6 or 7 any described methods, it is characterized in that described basis is initially detected scope, contiguous point constituted a customer group comprise:
Initially the scope of detecting is w
0, each some i searches neighbor point according to initially detecting scope, will put i and neighbor point thereof and be made as a group, repeats above-mentioned probe procedure, if this point has been included into a group and has not then detected, all nodes all are included into the group back to be finished; The network user group who obtains dividing.
9. the colony's division methods and the device of a user behavior Network Based is characterized in that, comprising:
The parameter set determining unit is used for determining the cybernetics control number collection;
The space determining unit is used for determining the user type space according to the cybernetics control number collection;
Cluster cell, from the user behavior server, read in data, after the multiple parameter values normalization of each user, in the user type space, form user's planisphere and determine the scope of detecting, according to detect point in the scope and the distance calculation displacement vector of itself at this point, upgrade simultaneously and detect scope, repeat above step, have a few mobile up to institute according to the displacement vector
Group's division unit is used for according to initially detecting scope contiguous point being constituted a customer group.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011100091670A CN102135983A (en) | 2011-01-17 | 2011-01-17 | Group dividing method and device based on network user behavior |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011100091670A CN102135983A (en) | 2011-01-17 | 2011-01-17 | Group dividing method and device based on network user behavior |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102135983A true CN102135983A (en) | 2011-07-27 |
Family
ID=44295770
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011100091670A Pending CN102135983A (en) | 2011-01-17 | 2011-01-17 | Group dividing method and device based on network user behavior |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102135983A (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102438035A (en) * | 2011-09-29 | 2012-05-02 | 惠州市德赛西威汽车电子有限公司 | Automatic microblog interconnection accessing method suitable for automobile user |
| CN102509248A (en) * | 2011-11-22 | 2012-06-20 | 昆明理工大学 | Multi-objective categorization method for travel grouping and system adopting same |
| CN102937951A (en) * | 2011-08-15 | 2013-02-20 | 北京百度网讯科技有限公司 | Method for building internet protocol (IP) address classification model, user classifying method and device |
| CN103514167A (en) * | 2012-06-15 | 2014-01-15 | 富士通株式会社 | Data processing method and device |
| CN104573034A (en) * | 2015-01-15 | 2015-04-29 | 中国联合网络通信集团有限公司 | CDR call ticket based user group division method and system |
| CN105224681A (en) * | 2015-10-23 | 2016-01-06 | 武汉大学 | Based on the customer requirement retrieval method and system of family's place of working context environmental |
| WO2016000562A1 (en) * | 2014-06-30 | 2016-01-07 | Tencent Technology (Shenzhen) Company Limited | Method and apparatus for grouping network service users |
| CN105763631A (en) * | 2016-04-13 | 2016-07-13 | 北京网康科技有限公司 | Peer group identification method and device |
| CN107623715A (en) * | 2017-08-08 | 2018-01-23 | 阿里巴巴集团控股有限公司 | A kind of identity information acquisition methods and device |
| CN109145934A (en) * | 2017-12-22 | 2019-01-04 | 北京数安鑫云信息技术有限公司 | User behavior data processing method, medium, equipment and device based on log |
| CN109522815A (en) * | 2018-10-26 | 2019-03-26 | 深圳博为教育科技有限公司 | A kind of focus appraisal procedure, device and electronic equipment |
| CN110737848A (en) * | 2018-07-03 | 2020-01-31 | 百度在线网络技术（北京）有限公司 | Mining processing method and device for user work unit and electronic equipment |
-
2011
- 2011-01-17 CN CN2011100091670A patent/CN102135983A/en active Pending
Cited By (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102937951B (en) * | 2011-08-15 | 2016-11-02 | 北京百度网讯科技有限公司 | Set up the method for IP address sort model, the method and device to user's classification |
| CN102937951A (en) * | 2011-08-15 | 2013-02-20 | 北京百度网讯科技有限公司 | Method for building internet protocol (IP) address classification model, user classifying method and device |
| CN102438035B (en) * | 2011-09-29 | 2014-10-29 | 惠州市德赛西威汽车电子有限公司 | Automatic microblog interconnection accessing method suitable for automobile user |
| CN102438035A (en) * | 2011-09-29 | 2012-05-02 | 惠州市德赛西威汽车电子有限公司 | Automatic microblog interconnection accessing method suitable for automobile user |
| CN102509248B (en) * | 2011-11-22 | 2016-03-30 | 昆明理工大学 | A kind ofly be applied to the travel Multi-Target Classification Method of forming a team and system |
| CN102509248A (en) * | 2011-11-22 | 2012-06-20 | 昆明理工大学 | Multi-objective categorization method for travel grouping and system adopting same |
| CN103514167A (en) * | 2012-06-15 | 2014-01-15 | 富士通株式会社 | Data processing method and device |
| CN103514167B (en) * | 2012-06-15 | 2017-03-01 | 富士通株式会社 | Data processing method and equipment |
| WO2016000562A1 (en) * | 2014-06-30 | 2016-01-07 | Tencent Technology (Shenzhen) Company Limited | Method and apparatus for grouping network service users |
| CN105281925A (en) * | 2014-06-30 | 2016-01-27 | 腾讯科技（深圳）有限公司 | Network service user group dividing method and device |
| CN105281925B (en) * | 2014-06-30 | 2019-05-14 | 腾讯科技（深圳）有限公司 | The method and apparatus that network service groups of users divides |
| US9817885B2 (en) | 2014-06-30 | 2017-11-14 | Tencent Technology (Shenzhen) Company Limited | Method and apparatus for grouping network service users |
| CN104573034A (en) * | 2015-01-15 | 2015-04-29 | 中国联合网络通信集团有限公司 | CDR call ticket based user group division method and system |
| CN104573034B (en) * | 2015-01-15 | 2018-03-23 | 中国联合网络通信集团有限公司 | User group's division method and system based on CDR tickets |
| CN105224681A (en) * | 2015-10-23 | 2016-01-06 | 武汉大学 | Based on the customer requirement retrieval method and system of family's place of working context environmental |
| CN105224681B (en) * | 2015-10-23 | 2018-07-27 | 武汉大学 | Customer requirement retrieval method and system based on family's place of working context environmental |
| CN105763631B (en) * | 2016-04-13 | 2019-03-29 | 北京网康科技有限公司 | A kind of peer group recognition methods and device |
| CN105763631A (en) * | 2016-04-13 | 2016-07-13 | 北京网康科技有限公司 | Peer group identification method and device |
| CN107623715A (en) * | 2017-08-08 | 2018-01-23 | 阿里巴巴集团控股有限公司 | A kind of identity information acquisition methods and device |
| CN107623715B (en) * | 2017-08-08 | 2020-06-09 | 阿里巴巴集团控股有限公司 | Identity information acquisition method and device |
| CN109145934A (en) * | 2017-12-22 | 2019-01-04 | 北京数安鑫云信息技术有限公司 | User behavior data processing method, medium, equipment and device based on log |
| CN109145934B (en) * | 2017-12-22 | 2019-05-21 | 北京数安鑫云信息技术有限公司 | User behavior data processing method, medium, equipment and device based on log |
| CN110737848A (en) * | 2018-07-03 | 2020-01-31 | 百度在线网络技术（北京）有限公司 | Mining processing method and device for user work unit and electronic equipment |
| CN109522815A (en) * | 2018-10-26 | 2019-03-26 | 深圳博为教育科技有限公司 | A kind of focus appraisal procedure, device and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102135983A (en) | Group dividing method and device based on network user behavior | |
| AU2019275615B2 (en) | Classifying user behavior as anomalous | |
| CN105431844B (en) | Third party for search system searches for application | |
| US8782051B2 (en) | System and method for text categorization based on ontologies | |
| US20170228445A1 (en) | Systems and Methods for Presenting a Topic-Centric Visualization of Collaboration Data | |
| CN105719191B (en) | The social groups that behavior semanteme is not known under multiscale space find method | |
| CN104750798B (en) | Recommendation method and device for application program | |
| CN105335519A (en) | Model generation method and device as well as recommendation method and device | |
| CN104077723B (en) | A kind of social networks commending system and method | |
| CN107480158A (en) | The method and system of the matching of content item and image is assessed based on similarity score | |
| KR20150135196A (en) | Tailoring user experience for unrecognized and new users | |
| WO2008016495A2 (en) | Determination of graph connectivity metrics using bit-vectors | |
| Mo et al. | Event recommendation in social networks based on reverse random walk and participant scale control | |
| CN108701155A (en) | Expert's detection in social networks | |
| TWI525460B (en) | Electronic calculating apparatus, personalized information recommending method thereof, and computer program product thereof | |
| CN109903086A (en) | A kind of similar crowd's extended method, device and electronic equipment | |
| US9767204B1 (en) | Category predictions identifying a search frequency | |
| CN109241403A (en) | Item recommendation method, device, machinery equipment and computer readable storage medium | |
| Gao et al. | SeCo-LDA: Mining service co-occurrence topics for recommendation | |
| Cho et al. | Latent space model for multi-modal social data | |
| KR20190128246A (en) | Searching methods and apparatus and non-transitory computer-readable storage media | |
| CN105580043A (en) | Strength based modeling for recommendation system | |
| WO2020147259A1 (en) | User portait method and apparatus, readable storage medium, and terminal device | |
| US10474670B1 (en) | Category predictions with browse node probabilities | |
| CN112000763A (en) | Method, device, equipment and medium for determining competition relationship of interest points |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20110727 |