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Automatic Taxonomy Generation: Issues and Possibilities

  • Raghu Krishnapuram
  • Krishna Kummamuru
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2715)

Abstract

Automatic taxonomy generation deals with organizing text documents in terms of an unknown labeled hierarchy. The main issues here are (i) how to identify documents that have similar content, (ii) how to discover the hierarchical structure of the topics and subtopics, and (iii) how to find appropriate labels for each of the topics and subtopics. In this paper, we review several approaches to automatic taxonomy generation to provide an insight into the issues involved. We also describe how fuzzy hierarchies can overcome some of the problems associated with traditional crisp taxonomies.

Keywords

Marginal Likelihood Document Cluster Concept Hierarchy Vocabulary Term Meta Search Engine 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Raghu Krishnapuram
    • 1
  • Krishna Kummamuru
    • 1
  1. 1.Block I, IITIBM India Research LabNew DelhiIndia

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