An ensemble method for top-N recommendations from the SVD
作者：
Highlights：
• SVD suffers from computational limitation when delivering top-N items online.
• An ensemble algorithm for getting top-N items from the SVD results is proposed.
• The algorithm maps the items to the leaves of multiple compact trees offline.
• Users are assigned online to one leaf in each tree for obtaining their top-N items.
• The algorithm delivers faster and more accurate top-N items than the base SVD.
摘要
•SVD suffers from computational limitation when delivering top-N items online.•An ensemble algorithm for getting top-N items from the SVD results is proposed.•The algorithm maps the items to the leaves of multiple compact trees offline.•Users are assigned online to one leaf in each tree for obtaining their top-N items.•The algorithm delivers faster and more accurate top-N items than the base SVD.
论文关键词：Recommender systems,Ensemble methods,Matrix factorization,Top-N recommendations,Singular value decomposition
论文评审过程：Received 20 February 2016, Revised 1 July 2016, Accepted 19 July 2016, Available online 20 July 2016, Version of Record 27 July 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.07.028
