Graph-based word clustering using web search engine (2006)
| Venue: | IN PROC. OF EMNLP 2006 |
| Citations: | 7 - 0 self |
BibTeX
@INPROCEEDINGS{Matsuo06graph-basedword,
author = {Yutaka Matsuo and Kôki Uchiyama and et al.},
title = { Graph-based word clustering using web search engine},
booktitle = {IN PROC. OF EMNLP 2006},
year = {2006},
publisher = {}
}
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Abstract
Word clustering is important for automatic thesaurus construction, text classification, and word sense disambiguation. Recently, several studies have reported using the web as a corpus. This paper proposes an unsupervised algorithm for word clustering based on a word similarity measure by web counts. Each pair of words is queried to a search engine, which produces a co-occurrence matrix. By calculating the similarity of words, a word cooccurrence graph is obtained. A new kind of graph clustering algorithm called Newman clustering is applied for efficiently identifying word clusters. Evaluations are made on two sets of word groups derived from a web directory and WordNet.
