Automatic Extraction of Structurally Coherent Mini-Taxonomies

  • Khalid Saleem
  • Zohra Bellahsene
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5231)

Abstract

Today, ontologies are being used to model a domain of knowledge in semantic web. OWL is considered to be the main language for developing such ontologies. It is based on the XML model, which inherently follows the hierarchical structure. In this paper we demonstrate an automatic approach for emergent semantics modeling of ontologies. We follow the collaborative ontology construction method without the direct interaction of domain users, engineers or developers. A very important characteristic of an ontology is its hierarchical structure of concepts. We consider large sets of domain specific hierarchical structures as trees and apply frequent sub-tree mining for extracting common hierarchical patterns. Our experiments show that these hierarchical patterns are good enough to represent and describe the concepts for the domain ontology. The technique further demonstrates the construction of the taxonomy of domain ontology. In this regard we consider the largest frequent tree or a tree created by merging the set of largest frequent sub-trees as the taxonomy. We argue in favour of the trustabilty for such a taxonomy and related concepts, since these have been extracted from the structures being used with in the specified domain.

Keywords

Ontology Learning Mini-taxonomies Collaborative Ontology Construction Tree Mining Large Scale 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Khalid Saleem
    • 1
  • Zohra Bellahsene
    • 1
  1. 1.LIRMM - UMR 5506 CNRS University Montpellier 2Montpellier

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