Personalized Context-A ware QoS Prediction for Web Services Based on Collaborative Filtering

摘要：

Abstract The emergence of abundant Web Services has enforced rapid evolvement of the Service Oriented Architecture (SOA). To help user selecting and recommending the services appropriate to their needs, both functional and nonfunctional quality of service (QoS) attributes should be taken into account Before selecting, user should predict the quality of Web Services. A Collaborative Filtering (CF)-based recommendation system is introduced to attack this problem. However, existing CF approaches generally do not consider context, which is an important factor in both recommender system and QoS prediction. Motivated by this, the paper proposes a personalized contextaware QoS prediction method for Web Services recommendations based on the SLOPE ONE approach. Experimental results demonstrate that the suggested approach provides better QoS prediction.

关键词： Context QoS Prediction Collaborative Filtering Web Service

作者: Qi Xie Kaigui Wu Jie Xu Pan He Min Chen

作者单位: College of Computer Science,Chongqing University,Chongqing 400044, China

会议类型: 国际会议

会议名称: 6th International Conference on Advanced Data Mining and Applications(第六届先进数据挖掘及应用国际会议 ADMA 2010)

会议地点: 重庆

会议语种:英文

页码: 368-375

在线出版日期: 2010-11-19（万方平台首次上网日期，不代表论文的发表时间）