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UIP: estimating true rating scores of services through online user communities
conference contribution
posted on 2023-05-23, 11:37 authored by Huang, X, Huang, W, Lai, WAs many online systems rely on user ratings for making decisions such as recommendations, the quality of such rating scores are increasingly important. On the other hand, users interact with each other via online communities. How such interactions affect the trueness of their ratings? Can we obtain the true rating scores that exclude the influences among users? This paper presents a conceptual framework that characterizes the influences on quality of services among users, and an algorithm that estimates the true rating scores by minimizing the influence among users. In other words, the influence on users' ratings due to their interactions is minimized so as to obtain the more accurate rating scores. The proposed approach has been validated by experimenting on real data sets. The results of the experiments have demonstrated that our approach is capable of estimating true ratings.
History
Publication title
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence (SSCI 2016)Pagination
1-7ISBN
978-1-5090-4240-1Department/School
School of Information and Communication TechnologyPublisher
Institute of Electrical and Electronics EngineersPlace of publication
United States of AmericaEvent title
2016 IEEE Symposium Series on Computational Intelligence (SSCI 2016)Event Venue
Athens, GreeceDate of Event (Start Date)
2016-12-06Date of Event (End Date)
2016-12-09Rights statement
Copyright 2016 IEEERepository Status
- Restricted