Abstract
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.
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Yuan, W., Guan, D., Lee, S., Lee, YK., Lee, H. (2006). Filtering Out Unfair Recommendations for Trust Model in Ubiquitous Environments. In: Bagchi, A., Atluri, V. (eds) Information Systems Security. ICISS 2006. Lecture Notes in Computer Science, vol 4332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11961635_27
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DOI: https://doi.org/10.1007/11961635_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68962-1
Online ISBN: 978-3-540-68963-8
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