ITM Web Conf.
Volume 7, 20163rd Annual International Conference on Information Technology and Applications (ITA 2016)
|Number of page(s)||5|
|Section||Session 5: Algorithms and Simulation|
|Published online||21 November 2016|
Improved Collaborative Filtering Algorithm using Topic Model
School of Information Science & Engineering, Dalian Polytechnic University, China
a Corresponding author: email@example.com
Collaborative filtering algorithms make use of interactions rates between users and items for generating recommendations. Similarity among users or items is calculated based on rating mostly, without considering explicit properties of users or items involved. In this paper, we proposed collaborative filtering algorithm using topic model. We describe user-item matrix as document-word matrix and user are represented as random mixtures over item, each item is characterized by a distribution over users. The experiments showed that the proposed algorithm achieved better performance compared the other state-of-the-art algorithms on Movie Lens data sets.
© Owned by the authors, published by EDP Sciences, 2016
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