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Local Ensemble across Multiple Sources for Collaborative Filtering
2017
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management - CIKM '17
Recently, Transfer Collaborative Filtering (TCF) methods across multiple source domains, which employ knowledge from different source domains to improve the recommendation performance in the target domain, have been applied in recommender systems. The existing multi-source TCF methods either require overlapping objects in different domains or simply re-weight domains to merge them together. In this paper, we propose a novel LOcal EN semble framework across multiple source domains for
doi:10.1145/3132847.3133099
dblp:conf/cikm/ZhengZS17
fatcat:w7xmo4xhzzbivphhq3astxt7su