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Title page for etd-0803105-231243


URN etd-0803105-231243 Statistics This thesis had been viewed 2954 times. Download 1722 times.
Author Yi-Chun Chen
Author's Email Address d8806005@mail.ttu.edu.tw
Department Computer Science and Enginerring
Year 2004 Semester 2
Degree Ph.D. Type of Document Doctoral Dissertation
Language English Page Count 126
Title Chinese Zero Anaphora Resolution and Its Applications
Keyword
  • zero anaphora resolution
  • Chinese shallow parsing
  • Chinese natural language process
  • Chinese natural language process
  • Chinese shallow parsing
  • zero anaphora resolution
  • Abstract Anaphora resolution is the task of determining the antecedent of an anaphor which can be zero, pronominal and nominal forms. It plays an increasingly important role in a number of natural language processing applications including machine translation, information retrieval, text summarization, etc. In this thesis, we aim to investigate computational resolution of zero anaphora in Chinese text and apply the resolution method on NLP applications for examining its performance. The work of zero anaphora resolution is divided into two steps: First, we investigate linguistic behavior of Chinese zero anaphora and computational approaches to anaphora resolution for developing the method of Chinese zero anaphora resolution. Second, the zero anaphora resolution system is implemented according to results of the first step. On completing the implementation, an evaluation of the system is performed on real news articles. Because zero anaphors are not expressed on the surface text, our resolution method is first to detect zero anaphors in each utterance, and then identify their antecedents in the preceding utterance.
    After the method of zero anaphora resolution is carried out, we adopt the resolution method as a basis for improving the accuracy of NLP applications. A text categorization system integrates the zero anaphora resolution process to recover the omissions of anaphors in query text. An information retrieval system employs a topic identification method to resolve the omissions of topics of documents in the text collection for creating better indices. The topic identification method is developed by employing the notion of the centering model and the zero anaphora resolution method and is further used to create the metadata of XML Topic Maps. The experiments of these applications demonstrate on text collection taken from several newspapers, such as China Times Express and Central Daily News.
    Advisor Committee
  • Ching-Long Yeh - advisor
  • Huei-Huang Chen - co-chair
  • Jason S. Chang - co-chair
  • Tai-Wen Yue - co-chair
  • Ting Liang - co-chair
  • Yuh-Jyh Hu - co-chair
  • Files indicate access worldwide
    Date of Defense 2005-07-21 Date of Submission 2005-08-03


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