Function Labeling for Unparsed Chinese Text

DOI Web Site Web Site 被引用文献1件 参考文献36件
  • 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

この論文をさがす

説明

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

被引用文献 (1)*注記

もっと見る

参考文献 (36)*注記

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ