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Quality of web service prediction by collective matrix factorization

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper studies the quality of web service prediction problem. We formalize the QoS prediction problem by incorporating multiple contextual characteristics via collective matrix factorization that simultaneously factor the user-service quality matrix and contextual information matrices. Using the service category and location context, we develop three context-aware QoS prediction models and algorithms to demonstrate the advantages of this modeling technique. The advantages of our proposed models are demonstrated via experiments on real-life data sets.

源语言英语
主期刊名Proceedings - 2014 IEEE International Conference on Services Computing, SCC 2014
编辑Elena Ferrari, Ravindran Kaliappa, Patrick C.K. Hung
出版商Institute of Electrical and Electronics Engineers Inc.
432-439
页数8
ISBN(电子版)9781479950669
DOI
出版状态已出版 - 17 10月 2014
活动11th IEEE International Conference on Services Computing, SCC 2014 - Anchorage, 美国
期限: 27 6月 20142 7月 2014

出版系列

姓名Proceedings - 2014 IEEE International Conference on Services Computing, SCC 2014

会议

会议11th IEEE International Conference on Services Computing, SCC 2014
国家/地区美国
Anchorage
时期27/06/142/07/14

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