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Lecture Notes in Computer Science
Recommendation systems (RS) play an important role in directing customers to their favorite items. Data sparsity, which usually leads to overfitting, is a major bottleneck for making precise recommendations. Several cross-domain RSs have been proposed in the past decade in order to reduce the sparsity issues via transferring knowledge. However, existing works only focus on either nearest neighbor model or latent factor model for cross domain scenario. In this paper, we introduce a Multifaceteddoi:10.1007/978-3-319-63558-3_27 fatcat:kzlfi5iz5fc57hmri44z6d22ci