Abstract:Singular Value Decomposition (SVD) is trust-based matrix factorization technique for recommendations is proposed. Trust SVD integrates multiple information sources into the recommendation model to reduce the data sparsity and cold start problems and their deterioration of recommendation performance. An analysis of social trust data from four real-world data sets suggests that both the explicit and the implicit influence of both ratings and trust should be taken into consideration in a recommendation model. Tru… Show more
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