Function Labeling for Unparsed Chinese Text

• Yuan Caixia

  Faculty of Engineering, The University of Tokushima School of Computer, Beijing University of Posts and Telecommunications

• Ren Fuji

  Faculty of Engineering, The University of Tokushima School of Computer, Beijing University of Posts and Telecommunications

• Wang Xiaojie

  School of Computer, Beijing University of Posts and Telecommunications

• Zhong Yixin

  School of Computer, Beijing University of Posts and Telecommunications

抄録

This paper presents a work of function labeling for unparsed Chinese text. Unlike other attempts that utilize the full parse trees, we propose an effective way to recognize function labels directly based on lexical information, which is easily scalable for languages that lack sufficient parsing resources. Furthermore, we investigate a general method to iteratively simplify a sentence, thus transferring complicated sentence into structurally simple pieces. By means of a sequence learning model with hidden Markov support vector machine, we achieve the best F-measure of 87.40 on the text from Penn Chinese Treebank resources - a statistically significant improvement over the existing Chinese function labeling systems.

収録刊行物

• 電気学会論文誌Ｃ（電子・情報・システム部門誌）

  電気学会論文誌Ｃ（電子・情報・システム部門誌） 129 (8), 1593-1600, 2009

  一般社団法人 電気学会

キーワード

• function labeling
• lexical features
• sequence learning
• Chinese language processing

詳細情報

• CRID: 1390282679580530944
• NII論文ID: 10025101803
• NII書誌ID: AN10065950
• DOI: 10.1541/ieejeiss.129.1593
• ISSN: 13488155
• ISSN: 03854221
• NDL書誌ID: 10396202
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I10396202
• Web Site: http://www.jstage.jst.go.jp/article/ieejeiss/129/8/129_8_1593/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可