A note on morphological analysis methods based on statistical decision theory

Yasunari Maeda*, Naoya Ikeda, Hideki Yoshida, Yoshitaka Fujiwara, Toshiyasu Matsushima

*この研究の対応する著者

研究成果: Conference contribution

抄録

Morphological analysis is one of important topics in the field of NLP(Natural Language Processing). In many previous research a HMM(Hidden Markov Model) with unknown parameters has been used as a language model. In this research we also use the HMM as the language model. And we assume that sate transitions in the HMM are dominated by a second order Markov chain. At first we propose two types of morphological analysis methods which minimize the error rate with reference to a Bayes criterion. But the computational complexity of the proposed Bayes optimal morphological analysis methods are exponential order. So we also propose approximate methods.

本文言語English
ホスト出版物のタイトルSICE Annual Conference, SICE 2007
ページ1563-1568
ページ数6
DOI
出版ステータスPublished - 2007 12 1
イベントSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
継続期間: 2007 9 172007 9 20

出版物シリーズ

名前Proceedings of the SICE Annual Conference

Conference

ConferenceSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
国/地域Japan
CityTakamatsu
Period07/9/1707/9/20

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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