Statistical Dependency Analysis with Support Vector Machines (2003)
by
Hiroyasu Yamada
,
Yuji Matsumoto
| Venue: | In Proceedings of IWPT |
| Citations: | 83 - 0 self |
BibTeX
@INPROCEEDINGS{Yamada03statisticaldependency,
author = {Hiroyasu Yamada and Yuji Matsumoto},
title = {Statistical Dependency Analysis with Support Vector Machines},
booktitle = {In Proceedings of IWPT},
year = {2003},
pages = {195--206}
}
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Abstract
In this paper, we propose a method for analyzing word-word dependencies using deterministic bottom-up manner using Support Vector machines. We experimented with dependency trees converted from Penn treebank data, and achieved over 90 % accuracy of word-word dependency. Though the result is little worse than the most up-to-date phrase structure based parsers, it looks satisfactorily accurate considering that our parser uses no information from phrase structures. 1
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