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Extracting Structured Subject Information from Digital Document Archives

  • Jyi-Shane Liu
  • Ching-Ying Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4312)

Abstract

Information extraction (IE) techniques are capable of decoding targeted subject information in documents, and reducing text data into a set of structured core information. The implication for digital libraries is that IE potentially serves as an enabling tool to extend the value of digital document archives. We present an approach, called sandwich extraction pattern, to address the closely coupled template relation tasks. The approach provides interactive capabilities for task specification, domain knowledge acquisition, and output evaluation. This allows users (e.g. librarians) to have direct control on the design of value-added content products and the performance of IE tools. We conducted empirical validation by implementing an IE system, called SEP, and field testing it in a practical document archive. Encouraged by successful test runs, NCCU library has formally initiated a project to develop a value-added content product of government personnel gazettes, including document images, electronic texts, and personnel changes database.

Keywords

information extraction digital document archives value-added services 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jyi-Shane Liu
    • 1
    • 2
  • Ching-Ying Lee
    • 3
  1. 1.Department of Computer ScienceNational Chengchi UniversityTaiwan, R.O.C.
  2. 2.University LibraryNational Chengchi UniversityTaiwan, R.O.C.
  3. 3.Department of EnglishNational Taiwan Normal UniversityTaiwan, R.O.C.

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