BriefGPT.xyz
Oct, 2012
响应感知基于模型的协同过滤
Response Aware Model-Based Collaborative Filtering
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Guang Ling, Haiqin Yang, Michael R. Lyu, Irwin King
TL;DR
本文提出了 Response Aware Probabilistic Matrix Factorization (RAPMF) 方法，它可以更好地建模用户的反应模式，从而提高推荐系统的准确性和可解释性。
Abstract
Previous work on
recommender systems
mainly focus on fitting the ratings provided by users. However, the
response patterns
, i.e., some items are rated while others not, are generally ignored. We argue that failin
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