DocumentCode :
3127494
Title :
Personalized QoS Prediction forWeb Services via Collaborative Filtering
Author :
Shao, Lingshuang ; Zhang, Jing ; Wei, Yong ; Zhao, Junfeng ; Xie, Bing ; Mei, Hong
Author_Institution :
Peking Univ., Beijing
fYear :
2007
fDate :
9-13 July 2007
Firstpage :
439
Lastpage :
446
Abstract :
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.
Keywords :
Web services; data mining; groupware; quality of service; Web services; collaborative filtering; personalized QoS prediction; quality of service; similarity mining; Availability; Collaboration; Collaborative software; Delay; Information filtering; Information filters; Quality of service; Software quality; Web and internet services; Web services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Services, 2007. ICWS 2007. IEEE International Conference on
Conference_Location :
Salt Lake City, UT
Print_ISBN :
0-7695-2924-0
Type :
conf
DOI :
10.1109/ICWS.2007.140
Filename :
4279629
Link To Document :
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