Abstract
Cross-domain collaborative filtering (CF) is an emerging research topic in recommender systems. It aims to alleviate the sparsity problem in individual CF domains by transferring knowledge among related domains. In this paper, we will give a brief survey of the pilot studies in this research line in two dimensions: Collaborative Filtering Domains and Knowledge Transfer Styles. Some possible extensions for cross-domain CF will be discussed in the end.
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