Title page for etd-0802101-100356


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URN etd-0802101-100356
Author Chih-Jen Pen
Author's Email Address dreamtrue@livemail.tw
Statistics This thesis had been viewed 5331 times. Download 3418 times.
Department Information Management
Year 2000
Semester 2
Degree Master
Type of Document
Language English
Title LIEF: An Algorithm for Learning Information Extraction Rules from Unstructured Documents
Date of Defense 2001-07-23
Page Count 49
Keyword
  • Information Extraction Rules
  • Positive Searching Path
  • Regular Expression
  • Unstructured Documents
  • Negative Searching Path
  • Information Extraction
  • Abstract In the past, information was stored more or less well-structured in database. Nowadays, a lot of information is presented in unstructured format. The management of and retrieval from such large vast of textual information has been a challenging issue for organizations or individuals. Information extraction is the process of extracting relevant data from semi-structured or unstructured documents and transforming them into structured representations. Many information extraction learning techniques have been proposed. However, they are ineffectiveness on unstructured documents. Thus, in the research, we proposed a new information extraction learning algorithm, called LIEF, that enhancing existing information extraction learning techniques. According to the empirical evaluations on news documents that are unstructured format, the LIEF algorithm proposed showed its capabilities in accuracy rate.
    Advisory Committee
  • Fu-Ren Lin - chair
  • Sheng-Tun Li - co-chair
  • Chih-Ping Wei - advisor
  • Files
  • etd-0802101-100356.pdf
  • indicate access worldwide
    Date of Submission 2001-08-02

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