@inproceedings{6ec5334d35c645d3bf12551af8dc2c3e,
title = "A new effective collaborative filtering algorithm based on user's interest partition",
abstract = "Traditional collaborative filtering algorithms all suffer from inaccurate recommendation and bad scalability. In this paper, we propose a new collaborative filtering algorithm based on user's interest partition. We divides user's whole interest into pieces. Each piece of interest is called interest unit. And the similarity between users on interest unit is named local similarity. The similarity between users on whole interest is named holistic similarity which is similar with the traditional similarity. Our approach searches the nearest neighbors of active user according to the linear combination of local similarity and holistic similarity. Through experiments, thealgorithm can solve the problem of high sparsity on user-item matrix. Our algorithm also has a better quality on recommendation according to experiments.",
keywords = "Collaborative filtering, Interest model, Interest partition, Local interest, Recommender system",
author = "He Keqin and He Liang and Xia Weiwei",
year = "2008",
doi = "10.1109/ISCSCT.2008.37",
language = "英语",
isbn = "9780769534985",
series = "Proceedings - International Symposium on Computer Science and Computational Technology, ISCSCT 2008",
pages = "727--731",
booktitle = "Proceedings - International Symposium on Computer Science and Computational Technology, ISCSCT 2008",
note = "International Symposium on Computer Science and Computational Technology, ISCSCT 2008 ; Conference date: 20-12-2008 Through 22-12-2008",
}