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Semi-automatic Construction of Topic Ontologies

  • Blaž Fortuna
  • Dunja Mladenič
  • Marko Grobelnik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4289)

Abstract

In this paper, we review two techniques for topic discovery in collections of text documents (Latent Semantic Indexing and K-Means clustering) and present how we integrated them into a system for semi-automatic topic ontology construction. The OntoGen system offers support to the user during the construction process by suggesting topics and analyzing them in real time. It suggests names for the topics in two alternative ways both based on extracting keywords from a set of documents inside the topic. The first set of descriptive keyword is extracted using document centroid vectors, while the second set of distinctive keyword is extracted from the SVM classification model dividing documents in the topic from the neighboring documents.

Keywords

Support Vector Machine Text Document Latent Semantic Indexing Keyword Extraction Ontology Learn 
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 2006

Authors and Affiliations

  • Blaž Fortuna
    • 1
  • Dunja Mladenič
    • 1
  • Marko Grobelnik
    • 1
  1. 1.Jožef Stefan InstituteLjubljanaSlovenia

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