@inproceedings{c2e5bb74ed0a42908e3e6b224dd9df95,
title = "Feature Weighting Information-Theoretic Co-clustering for document clustering",
abstract = "This paper presents a feature weighting schema to improve the performance of Information-Theoretic Co-clustering (ITCC). The new algorithm, named as Feature Weighting Information-Theoretic Co-clustering (FWITCC), weights each feature with the mutual information shared by the features and the documents. The weighting schema makes informative features more important and noisy features less important, so that it can improve the qualities of resulted clusters. Experimental results on both synthetic data sets and 20Newsgroup data sets have demonstrated that our new approach has better clustering performance than (ITCC).",
keywords = "Co-clustering, Feature weighting, Text clustering",
author = "Yunming Ye and Xutao Li and Biao Wu and Yan Li",
year = "2009",
doi = "10.1109/CSA.2009.5404286",
language = "英语",
isbn = "9781424449460",
series = "Proceedings of the 2009 2nd International Conference on Computer Science and Its Applications, CSA 2009",
booktitle = "Proceedings of the 2009 2nd International Conference on Computer Science and Its Applications, CSA 2009",
note = "2009 2nd International Conference on Computer Science and Its Applications, CSA 2009 ; Conference date: 10-12-2009 Through 12-12-2009",
}