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
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