@inproceedings{112bbfe1c35a4e54836c1b6eccb4025f,
title = "An adaptive affinity propagation document clustering",
abstract = "The standard affinity propagation clustering algorithm suffers from one limitation that it is hard to know the value of the parameter {"}preference{"} which can yield an optimal clustering solution. To overcome this limitation, in this paper we proposes an adaptive affinity propagation method. The method first finds out the range of {"} preference{"}, then searches the space of {"}preference{"} to find a good value which can optimize the clustering result. We apply the method to document clustering and compare it with the standard affinity propagation and K-Means clustering method in real data sets. Experimental results show that our proposed method can get better clustering result.",
keywords = "Adaptive clustering, Affinity propagation, Document clustering, Vector space model",
author = "Yancheng He and Qingcai Chen and Xiaolong Wang and Ruifeng Xu and Xiaohua Bai and Xianjun Meng",
year = "2010",
language = "英语",
isbn = "9789774033964",
series = "INFOS2010 - 2010 7th International Conference on Informatics and Systems",
booktitle = "INFOS2010 - 2010 7th International Conference on Informatics and Systems",
note = "2010 7th International Conference on Informatics and Systems, INFOS2010 ; Conference date: 28-03-2010 Through 30-03-2010",
}