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1. Matrix Factorization Methods for Recommender Systems
Magister-uppsats, Institutionen för datavetenskapSammanfattning : This thesis is a comprehensive study of matrix factorization methods used in recommender systems. We study and analyze the existing models, specifically probabilistic models used in conjunction with matrix factorization methods, for recommender systems from a machine learning perspective. LÄS MER
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