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Formation of categories in document classification systems

  • Sanjiv K. Bhatia
  • Jitender S. Deogun
  • Vijay V. Raghavan
Track 2: Artificial Intelligence
Part of the Lecture Notes in Computer Science book series (LNCS, volume 507)

Abstract

Information retrieval systems employ the classification of documents into various categories to facilitate retrieval. The problem of categorization depends on the successful solution to three subproblems: creation of categories, determining the relationship between categories, and maintenance of the categorization system. In existing document categorization systems, the categories are formed by using hit and trial methods. This increases the initial setup period for the system. The initial setup time is further affected by an empirical assignment of relationships between categories.

In this paper, we propose a solution to the problem of developing categories by the application of techniques originating in knowledge acquisition. The approach is based on capturing the knowledge of a user to ensure continuity with the existing categorization system. The use of Personal Construct Theory for knowledge elicitation helps in making explicit the subconscious hierarchical relationships between various categories as perceived by the user.

Keywords

Knowledge Acquisition Information Retrieval System Dependence Tree Repertory Grid Maximum Span Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    J. H. Boose. Expertise Transfer for Expert System Design. Elsevier-Science Publishers, New York, 1986.Google Scholar
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    Carnegie Group, Pittsburgh, PA. Text Categorization Shell: Technical Brief, 1989. 13 p.Google Scholar
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    A. Hart. Knowledge Acquisition for Expert Systems. McGraw-Hill, New York, NY, 1986.Google Scholar
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    G. A. Kelly. The Psychology of Personal Constructs. Norton Publishers, 1955.Google Scholar
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    C. J. van Rijsbergen. Information Retrieval. Butterworth Publishers, Boston, MA, 2 edition, 1980.Google Scholar
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    C. J. van Rijsbergen, D. J. Harper, and M. F. Porter. The selection of good search terms. Information Processing and Management, 17:77–91, 1981.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Sanjiv K. Bhatia
    • 1
  • Jitender S. Deogun
    • 1
  • Vijay V. Raghavan
    • 2
  1. 1.Department of Computer Science and EngineeringUniversity of NebraskaLincoln
  2. 2.Center for Advanced Computer StudiesUniversity of SW LouisianaLafayette

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