SLIM: Sparse Linear Methods for Top-N Recommender Systems

Abstract

This paper focuses on developing effective and efficient algorithms for top-N recommender systems. A novel Sparse Linear Method (SLIM) is proposed, which generates top-N recommendations by aggregating from user purchase/rating profiles. A sparse aggregation coefficient matrix W is learned from SLIM by solving an `1-norm and `2-norm regularized optimization… (More)
DOI: 10.1109/ICDM.2011.134
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