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IEEE International Conference on Web Services (ICWS 2007)
Personalized QoS Prediction forWeb Services via Collaborative Filtering
Salt Lake City, Utah, USA
July 09-July 13
ISBN: 0-7695-2924-0
Lingshuang Shao, Peking University, P.R.China
Jing Zhang, Peking University, P.R.China
Yong Wei, Peking University, P.R.China
Junfeng Zhao, Peking University, P.R.China
Bing Xie, Key Laboratory of High Confidence Software Technologies, Ministry of Education of P.R.China
Hong Mei, Peking University, P.R.China
Many researchers propose that, not only functional but also non-functional properties, also known as quality of service (QoS), should be taken into consideration when consumers select services. Consumers need to make prediction on quality of unused web services before selecting. Usually, this prediction is based on other consumers? experiences. Being aware of different QoS experiences of consumers, this paper proposes a collaborative filtering based approach to making similarity mining and prediction from consumers? experiences. Experimental results demonstrate that this approach can make significant improvement on the effectiveness of QoS prediction for web services.
Citation:
Lingshuang Shao, Jing Zhang, Yong Wei, Junfeng Zhao, Bing Xie, Hong Mei, "Personalized QoS Prediction forWeb Services via Collaborative Filtering," icws, pp.439-446, IEEE International Conference on Web Services (ICWS 2007), 2007
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