Predicting Category Additions in a Topic Hierarchy

  • Janez Brank
  • Marko Grobelnik
  • Dunja Mladenić
Conference paper

DOI: 10.1007/978-3-540-89704-0_22

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5367)
Cite this paper as:
Brank J., Grobelnik M., Mladenić D. (2008) Predicting Category Additions in a Topic Hierarchy. In: Domingue J., Anutariya C. (eds) The Semantic Web. ASWC 2008. Lecture Notes in Computer Science, vol 5367. Springer, Berlin, Heidelberg

Abstract

This paper discusses the problem of predicting the structural changes in an ontology. It addresses ontologies that contain instances in addition to concepts. The focus is on an ontology where the instances are textual documents, but the approach presented in this document is general enough to also work with other kinds of instances, as long as a similarity measure can be defined over them. We examine the changes in the Open Directory Project ontology of Web pages over a period of several years and analyze the most common types of structural changes that took place during that time. We then present an approach for predicting one of the more common types of structural changes, namely the addition of a new concept that becomes the subconcept of an existing parent concept and adopts a few instances of this existing parent concept. We describe how this task can be formulated as a machine-learning problem and present an experimental evaluation of this approach that shows promising results of the proposed approach.

Keywords

Ontologies taxonomies knowledge organization semantic web modeling human expertise machine learning text mining support vector machine 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Janez Brank
    • 1
  • Marko Grobelnik
    • 1
  • Dunja Mladenić
    • 1
  1. 1.Jožef Stefan InstituteLjubljanaSlovenia

Personalised recommendations