@inproceedings{e994ca9b503b4c2d96c76fa5003b07b6,
title = "User's latent interest-based collaborative filtering",
abstract = "Memory-based collaborative filtering is one of the most popular methods used in recommendation systems. It predicts a user's preference based on his or her similarity to other users. Traditionally, the Pearson correlation coefficient is often used to compute the similarity between users. In this paper we develop novel memory-based approach that incorporates user's latent interest. The interest level of a user is first estimated from his/her ratings for items through a latent trait model, and then used for computing the similarity between users. Experimental results show that the proposed method outperforms the traditional memory-based one.",
keywords = "Latent Interest, Latent Trait Models, Memory-based Collaborative Filtering, Sparsity",
author = "Biyun Hu and Zhoujun Li and Jun Wang",
year = "2010",
doi = "10.1007/978-3-642-12275-0\_61",
language = "英语",
isbn = "3642122744",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "619--622",
booktitle = "Advances in Information Retrieval - 32nd European Conference on IR Research, ECIR 2010, Proceedings",
address = "德国",
note = "32nd European Conference on Information Retrieval, ECIR 2010 ; Conference date: 28-03-2010 Through 31-03-2010",
}