Choosing reputable servents in a P2P network
Proceedings of the 11th international conference on World Wide Web
An Adaptive Recommendation Trust Model in Multiagent System
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
MobiDE '07 Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access
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This paper presents a novel context-based approach to filter out unfair recommendations for trust model in ubiquitous environments. Context is used in our approach to analyze the user's activity, state and intention. Incremental learning based neural network is used to dispose the context in order to find doubtful recommendations. This approach has distinct advantages when dealing with randomly given irresponsible recommendations, individual unfair recommendations as well as unfair recommendations flooding.