Name
Abstract | ||
|---|---|---|
QoS prediction for Web services is a hot research problem in the field of services computing. As one of the most important methods for QoS prediction, Collaborative Filtering (CF) makes prediction based on the historical QoS data contributed by similar users and services. The key issue in this process is to detect the unreliable data offered by untrustworthy users, which has attracted limited attentions so far. The utilization of unreliable data decreases the prediction accuracy greatly. In this paper, we propose a novel credibility-aware QoS prediction method (named CAP) to address this problem. Our method first employs two-phase K-means clustering to identify the untrustworthy users, which clusters QoS values for untrustworthy index calculation in the first phase and clusters users according to their index in the second phase, and then predicts the missing QoS value based on the credible clustering information. The evaluation results demonstrate that CAP provides considerable improvement on the prediction accuracy compared with other approaches and is robust against various percentages of untrustworthy users. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICWS.2015.31 | International Conference on Web Services |
Keywords | Field | DocType |
QoS prediction, K-means clustering, collaborative filtering, Web services | Services computing,Data mining,k-means clustering,Collaborative filtering,Computer science,Quality of service,Prediction algorithms,Cluster analysis,Web service,Database | Conference |
ISBN | Citations | PageRank |
978-1-4673-7271-8 | 23 | 0.76 |
References | Authors | |
17 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Wu | 1 | 27 | 1.16 |
| Weiwei Qiu | 2 | 85 | 4.50 |
| Zibin Zheng | 3 | 3731 | 199.37 |
| xinyu | 4 | 590 | 30.19 |
| Xiaohu Yang | 5 | 125 | 8.71 |