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Automatic Extraction of Structurally Coherent Mini-Taxonomies

Khalid Saleem 1 Zohra Bellahsene 2
2 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
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.
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Khalid Saleem, Zohra Bellahsene. Automatic Extraction of Structurally Coherent Mini-Taxonomies. ER: Conceptual Modeling, Oct 2008, Barcelona, Spain. pp.341-354, ⟨10.1007/978-3-540-87877-3_25⟩. ⟨lirmm-00325285⟩



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