Name
Abstract | ||
|---|---|---|
With the rapid development of witkey website, the amount of witkeys and tasks on the witkey sites is increasing far more quickly than our ability to process it. It is a critical problem needs to be solved for us to accomplish witkeys and tasks rapid matching. To resolve this problem, an available way is the recommender system. This paper analyzes the witkey behaviors on the websites and constructs the witkey preference model. Then the collaborative filtering technique is used to recommend online tasks. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IFITA.2009.117 | IFITA (3) |
Keywords | Field | DocType |
helium,construction industry,data mining,application software,internet,prediction algorithms,recommender system,predictive models,collaborative filtering,information technology,collaboration,recommender systems | Recommender system,World Wide Web,Collaborative filtering,Information retrieval,Computer science,Construction industry,Prediction algorithms | Conference |
Volume | Issue | Citations |
3 | null | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Songhe Jin | 1 | 0 | 0.34 |
| Song Bao-wei | 2 | 16 | 5.95 |
| Lei He | 3 | 0 | 0.68 |