Title page for etd-0730100-014038


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URN etd-0730100-014038
Author Yen-Hsien Lee
Author's Email Address roso@mis.nsysu.edu.tw
Statistics This thesis had been viewed 5335 times. Download 9658 times.
Department Information Management
Year 1999
Semester 2
Degree Master
Type of Document
Language English
Title Development of Information Extraction-based Event Detection Technique
Date of Defense 2000-07-26
Page Count 73
Keyword
  • environmental scanning
  • text categorization
  • information extraction
  • event detection
  • Abstract Environmental scanning is an important process, which acquires and uses the information about events, trends, and relationships in an organization's external environment. It permits an organization to adapt to its environment and to develop effective responses to secure or improve their position in the future. Event detection technique that identifies the onset of new events from streams of news stories would facilitate the process of organization's environmental scanning. However, traditional feature-based event detection techniques, which identify whether a news story contains an unseen event by comparing the similarity of words between the news story and past news stories, incur some limitations (e.g., the features shown in news document cannot actually represent the event described in it.). Thus, in this study, we developed an information extraction-based event detection (NEED) technique that combines information extraction and text categorization techniques to address the problems inherent to traditional feature-based event detection techniques. The empirical evaluation results showed that the NEED technique outperformed the traditional feature-based event detection techniques in miss rate and false alarm rate and achieved comparable event association accuracy rate to its counterpart.
    Advisory Committee
  • Fu-Ren Lin - chair
  • San-Yih Hwang - co-chair
  • Chih-Ping Wei - advisor
  • Files
  • 8742617.pdf
  • indicate access worldwide
    Date of Submission 2000-07-30

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