• DocumentCode
    3301576
  • Title

    An ungreedy Chinese deterministic dependency parser considering long-distance dependency

  • Author

    Yao, Wenlin ; Wang, Lei ; Gao, Lingling

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Ocean Univ. of China, Qingdao
  • fYear
    2008
  • fDate
    19-22 Oct. 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a two-step dependency parser to parse Chinese deterministically. By dividing a sentence into two parts and parsing them separately, the error accumulation can be avoided effectively. Previous works on shift-reduce dependency parser may guarantee the greedy characteristic of deterministic parsing less. This paper improves on a kind of deterministic dependency parsing method to weaken the greedy characteristic of it. During parsing, both forward and backward parsing directions are chosen to decrease the unparsed rate. Support vector machines are utilized to determine the word dependency relations and in order to solve the problem of long distance dependency, a group of combined global features are presented in this paper. The proposed parser achieved significant improvement on dependency accuracy and root accuracy.
  • Keywords
    grammars; natural language processing; support vector machines; text analysis; long-distance dependency; support vector machine; ungreedy Chinese deterministic dependency parser; word dependency; Computer errors; Computer science; Greedy algorithms; Machine learning; Marine technology; Natural language processing; Natural languages; Oceans; Performance analysis; Support vector machines; Chinese Dependency Parser; Combined Global Features; Deterministic; Ungreedy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing and Knowledge Engineering, 2008. NLP-KE '08. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4515-8
  • Electronic_ISBN
    978-1-4244-2780-2
  • Type

    conf

  • DOI
    10.1109/NLPKE.2008.4906818
  • Filename
    4906818