Abstract
Social Networks have dominated growth and popularity of the Web to an extent which has never been witnessed before. Such popularity puts forward issue of trust to the participants of Social Networks. Collaborative Filtering Recommenders have been among many systems which have begun taking full advantage of Social Trust phenomena for generating more accurate predictions. For analyzing the evolution of constructed networks of trust, we utilize Collaborative Filtering enhanced with T-index as an estimate of a user’s trustworthiness to identify and select neighbors in an effective manner. Our empirical evaluation demonstrates how T-index improves the Trust Network structure by generating connections to more trustworthy users. We also show that exploiting T-index results in better prediction accuracy and coverage of recommendations collected along few edges that connect users on a network.
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Fazeli, S., Zarghami, A., Dokoohaki, N., Matskin, M. (2010). Mechanizing Social Trust-Aware Recommenders with T-Index Augmented Trustworthiness. In: Katsikas, S., Lopez, J., Soriano, M. (eds) Trust, Privacy and Security in Digital Business. TrustBus 2010. Lecture Notes in Computer Science, vol 6264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15152-1_18
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DOI: https://doi.org/10.1007/978-3-642-15152-1_18
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