Relational distance-based collaborative filtering
暂无分享,去创建一个
In this paper, we present a novel hybrid recommender system called RelationalCF, which integrate content and demographic information into a collaborative filtering framework by using relational distance computation approaches without the effort of form transformation and feature construction. Our experiments suggest that the effective combination of various kinds of information based on relational distance approaches provides improved accurate recommendations than other approaches.
[1] Sean M. McNee,et al. Improving recommendation lists through topic diversification , 2005, WWW '05.
[2] John Riedl,et al. Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.
[3] William W. Cohen,et al. Recommendation as Classification: Using Social and Content-Based Information in Recommendation , 1998, AAAI/IAAI.
[4] M. Hilario,et al. Distance-based learning over extended relational algebra structures , 2022 .