Power of Human Curation in Recommendation System
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This paper introduces human curation signals and demonstrates incorporating human curation signals improves the relevance of state-of-art recommendation system models by up to 30% by experiments on a large-scale Pinterest dataset.
[1] John Riedl,et al. Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.
[2] Taghi M. Khoshgoftaar,et al. A Survey of Collaborative Filtering Techniques , 2009, Adv. Artif. Intell..
[3] Yifan Hu,et al. Collaborative Filtering for Implicit Feedback Datasets , 2008, 2008 Eighth IEEE International Conference on Data Mining.
[4] John Riedl,et al. GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.