@inproceedings{ef350cfa129742fca83f8d75415ae0e5,
title = "Improving short text clustering performance with keyword expansion",
abstract = "Most of traditional text clustering methods are based on bag of words representation, which ignore the important information on semantic relationship between key terms. To overcome this problem, researchers have recently proposed several new methods for improving short text clustering accuracy based on enriching short text representation. However, the computational costs of these methods based on expanding words appeared in short texts are usually time-consuming. In this paper, we improve previous work by enriching short text representation with keyword expansion. Empirical results show that the proposed method can greatly save time without sacrificing clustering accuracy.",
keywords = "Keyword expansion, Short text clustering, Text representation",
author = "Jun Wang and Yiming Zhou and Lin Li and Biyun Hu and Xia Hu",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2009.; 6th International Symposium of Neural Networks, ISNN 2009 ; Conference date: 26-05-2009 Through 29-05-2009",
year = "2009",
doi = "10.1007/978-3-642-01216-7\_31",
language = "英语",
series = "Advances in Intelligent and Soft Computing",
publisher = "Springer Verlag",
pages = "291--298",
editor = "Hongwei Wang and Yi Shen and Zhigang Zeng and Tingwen Huang",
booktitle = "Advances in Intelligent and Soft Computing",
address = "德国",
}