Personalized Web Service Recommendation via Normal Recovery Collaborative Filtering
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AbstractWith the increasing amount of web services on the Internet, personalized web service selection and recommendation are becoming more and more important. In this paper, we present a new similarity measure for web service similarity computation and propose a novel collaborative filtering approach, called normal recovery collaborative filtering, for personalized web service recommendation. To evaluate the web service recommendation performance of our approach, we conduct large-scale real-world experiments, involving 5,825 real-world web services in 73 countries and 339 service users in 30 countries. To the best of our knowledge, our experiment is the largest scale experiment in the field of service computing, improving over the previous record by a factor of 100. The experimental results show that our approach achieves better accuracy than other competing approaches.
All Author(s) ListSun HF, Zheng ZB, Chen JL, Lyu MR
Journal nameIEEE Transactions on Services Computing
Year2013
Month10
Day1
Volume Number6
Issue Number4
PublisherIEEE COMPUTER SOC
Pages573 - 579
ISSN1939-1374
LanguagesEnglish-United Kingdom
Keywordscollaborative filtering; QoS; recommender system; Service recommendation
Web of Science Subject CategoriesComputer Science; Computer Science, Information Systems; Computer Science, Software Engineering

Last updated on 2020-27-10 at 00:54