Record Extraction Based on User Feedback and Document Selection

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Abstract

In recent years, the research of record extraction from large document data is becoming popular. However there still exist some problems in record extraction. 1) when large document data is used for the target of information extraction, the process usually becomes very expensive. 2) it is also likely that extracted records may not pertain to the user's interest on the aspect of the topic. To address these problems, in this paper we propose a method to efficiently extract those records whose topics agree with the user's interest. To improve the efficiency of the information extraction system, our method identifies documents from which useful records are probably extracted. We make use of user feedback on extraction results to find topic-related documents and records. Our experiments show that our system achieves high extraction accuracy across different extraction targets.

Journal

  • Lecture Notes in Computer Science

    Lecture Notes in Computer Science, 574-585, 2007-06

    Springer

Codes

  • NII Article ID (NAID)
    120000975504
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    0302-9743
  • Data Source
    IR 
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