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Title:
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INFERRING TRUST BASED ON HIGHLY TRUSTED USERS IN A RECOMMENDER SYSTEM |
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Author(s):
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Yussuf Abu-shaaban |
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ISBN:
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978-972-8924-68-3 |
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Editors:
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Pedro Isaías, Miguel Baptista Nunes and Dirk Ifenthaler |
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Year:
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2008 |
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Edition:
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Single |
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Keywords:
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Trust, Trust propagation, Trust Inference, Recommender Systems |
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Type:
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Full Paper |
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First Page:
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306 |
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Last Page:
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313 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Trust information is becoming essential to support users making decisions when using e-commerce services and social
networks. Such trust information is usually represented by a directed network of nodes (users) connected by trust edges.
Trust propagation and aggregation techniques are usually used to infer the trust value between two users with no direct
trust link. In this paper, we propose and investigate a new approach to infer trust by using recommender system
information. To determine the trust value of a user, ratings assigned by the highest trusted users to recommendations
issued by that user are aggregated to infer trust. It was found that basing trust decisions on recommendation ratings made
by the highest trusted users can achieve high accuracy outperforming less trusted users. In addition, trust value inference
based on recommendation ratings of the highest trusted users tend to give a trust value greater than the mean of the direct
trust values in a network of trust. This tendency can also be noticed, with a smaller degree, when trust is predicted based
on recommendation ratings made by less trusted users. The work presented in this paper is the first to use recommender
systems to predict trust and to analyze the accuracy and tendencies of their use in the trust inference process. |
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