Name
Title | ||
|---|---|---|
Collaborative filtering by sequential extraction of user-item clusters based on structural balancing approach |
Abstract | ||
|---|---|---|
This paper considers a new approach to user-item clustering for collaborative filtering problems that achieves personalized recommendation. When user-item relations are given by an alternative process, personalized recommendation is performed by finding user-item neighborhoods (co-clusters) from a rectangular relational data matrix, in which users and items have mutually positive relations. In the proposed approach, user-item clusters are extracted one by one in a sequential manner via a structural balancing technique, used in conjunction with the sequential fuzzy cluster extraction method. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/FUZZY.2009.5277251 | Jeju Island |
Keywords | Field | DocType |
fuzzy set theory,groupware,information filtering,pattern clustering,collaborative filtering,mutually positive relations,personalized recommendation,rectangular relational data matrix,sequential extraction,sequential fuzzy cluster extraction method,structural balancing,user-item clustering,user-item neighborhood,user-item relation | Data mining,Cluster (physics),Collaborative filtering,Relational database,Collaborative software,Alternative process,Computer science,Fuzzy logic,Fuzzy set,Artificial intelligence,Cluster analysis,Machine learning | Conference |
ISSN | ISBN | Citations |
1098-7584 E-ISBN : 978-1-4244-3597-5 | 978-1-4244-3597-5 | 9 |
PageRank | References | Authors |
0.72 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Katsuhiro Honda | 1 | 289 | 63.11 |
| Akira Notsu | 2 | 146 | 42.93 |
| Hidetomo Ichihashi | 3 | 370 | 72.85 |