NDLI: Reputation-Aware QoS Value Prediction of Web Services

Content Provider	IEEE Xplore Digital Library
Author	Weiwei Qiu Zibin Zheng Xinyu Wang Xiaohu Yang Lyu, M.R.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Hong Kong, China (Zibin Zheng; Lyu, M.R.) \|\| Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China (Weiwei Qiu; Xinyu Wang; Xiaohu Yang)
Abstract	QoS value prediction of Web services is an important research issue for service recommendation, selection and composition. Collaborative Filtering (CF) is one of the most widely used methods which employs QoS values contributed by similar users to make predictions. Therefore, historical QoS values contributed by different users can have great impacts on prediction results. However, existing Web service QoS value prediction approaches did not take data credibility into consideration, which may impact the prediction accuracy. To address this problem, we propose a reputation-aware QoS value prediction approach, which first calculates the reputation of each user based on their contributed values, and then takes advantage of reputation-based ranking to exclude the values contributed by untrustworthy users. CF QoS prediction approach is finally used to predict the missing QoS values based on the purified dataset. Experimental results show that our approach has higher prediction accuracy than other approaches.
Starting Page	41
Ending Page	48
File Size	250136
Page Count	8
File Format	PDF
e-ISBN	9780769550268
DOI	10.1109/SCC.2013.43
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Quality of service Web services Accuracy Collaboration Prediction algorithms Equations Mathematical model Web service QoS value prediction reputation-based ranking collaborative filtering
Content Type	Text
Resource Type	Article

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