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Automatic Subject Classification of Scientific Literature Using Citation Metadata

  • Abdulhussain E. Mahdi
  • Arash Joorabchi
Part of the Communications in Computer and Information Science book series (CCIS, volume 194)

Abstract

This paper describes a new method for automatic classification of scientific literature archived in digital libraries and repositories according to a standard library classification scheme. The method is based on identifying all the references cited in the document to be classified and, using the subject classification metadata of extracted references as catalogued in existing conventional libraries, inferring the most probable class for the document itself with the help of a weighting mechanism. We have demonstrated the application of the proposed method and assessed its performance by developing a prototype software system for automatic classification of scientific documents according to the Dewey Decimal Classification (DDC) scheme. A dataset of one thousand research articles, papers, and reports from a well-known scientific digital library, CiteSeer, were used to evaluate the classification performance of the system. Detailed results of this experiment are presented and discussed.

Keywords

Digital library organization scientific literature classification library classification schemes Dewey Decimal Classification (DDC) library Online Public Access Catalogues (OPACs) 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Abdulhussain E. Mahdi
    • 1
  • Arash Joorabchi
    • 1
  1. 1.Department of Electronic and Computer EngineeringUniversity of LimerickIreland

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