Name
Abstract | ||
|---|---|---|
•We propose a regularization approach that incorporates social network information.•Biclustering algorithm is used to calculate the number of realistic friends.•The friendships are used to calculate the similarities between users.•The correlation between user and item is taken into consideration.•We examine the impacts of parameters to the experimental results. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.jss.2014.09.019 | Journal of Systems and Software |
Keywords | Field | DocType |
Recommender system,Social network,Social-based recommender system | Recommender system,Data mining,Social relationship,Social network,Collaborative filtering,Computer science,Real-time computing,Regularization (mathematics),Artificial intelligence,Biclustering,Missing data,Machine learning | Journal |
Volume | Issue | ISSN |
99 | C | 0164-1212 |
Citations | PageRank | References |
26 | 0.75 | 21 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhoubao Sun | 1 | 28 | 1.12 |
| Lixin Han | 2 | 45 | 4.50 |
| Wenliang Huang | 3 | 26 | 0.75 |
| Xueting Wang | 4 | 35 | 11.12 |
| Xiaoqin Zeng | 5 | 407 | 32.97 |
| Min Wang | 6 | 62 | 4.30 |
| Hong Yan | 7 | 3628 | 335.04 |