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A trust-based recommender system for collaborative networks

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4 Author(s)
Zanette, L. ; Fed. Univ. of Rio de Janeiro, Rio de Janeiro ; Motta, C.L.R. ; Santoro, F.M. ; Elia, M.

Collaborative networks are composed by people from all over and all kind of background that meet to exchange common experience. The great challenge lies in finding significant, reliable information in view of the swelling volume of information output. Recommender systems emerged as a solution to reduce the problem of information overload. Collaborative filtering (CF) technique in particular automates the recommendation process by building on users' opinions of items in a community. However CF has limitations named cold start and first rater. The goal of this paper is to present a model using trust to minimize those problems.

Published in:

Computer Supported Cooperative Work in Design, 2009. CSCWD 2009. 13th International Conference on

Date of Conference:

22-24 April 2009

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