Name
Abstract | ||
|---|---|---|
Collaborative filtering approach based on rating is one of the most broadly used service recommendation approach. However, rating data is very sparse in most service recommender systems, which seriously impacts the precision of service recommendation. In view of this problem, a usage-based service recommendation approach is proposed in this paper. What is special about this approach is that usage information instead of rating data is recruited to infer user interest. Some experiments are implemented to verify the efficient of this approach. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICWS.2016.101 | 2016 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS) |
Keywords | Field | DocType |
usage information, logistic function, interest decay rate, collaborative filtering | Recommender system,Data mining,World Wide Web,Collaborative filtering,Information retrieval,Computer science,Logistic function | Conference |
Citations | PageRank | References |
1 | 0.38 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rong Hu | 1 | 1 | 0.38 |
| Jianxun Liu | 2 | 640 | 67.12 |
| Yiping Wen | 3 | 25 | 8.59 |
| Yiyu Mao | 4 | 1 | 0.38 |