Sequential Patterns for Maintaining Ontologies Over Time

Abstract : Ontologies are known as a quality and functional model, allowing meta data representation and reasoning. However, their maintenance plays a crucial role as ontologies may be misleading if they are not up to date. Currently, this work is done manually, and raises the problem of expert subjectivity. Therefore, some works have developed maintenance tools but none has allowed a precise identification of the relations that could link concepts. In this paper, we propose a new fully generic approach combining sequential patterns extraction and equivalence classes. Our method allows to identify terms from textual documents and to define labelized association rules from sequential patterns according to relevance and neighborhood measures. Moreover, this process proposes the placement of the found elements refined by the use of equivalence classes. Results of various experiments on real data highlight the relevance of our proposal.
Type de document :
Communication dans un congrès
OTM/ODBASE'08: Ontologies, DataBases, and Applications of Semantics, Nov 2008, Monterrey, Mexico. Springer Verlag, pp.1385-1403, 2008, LNCS. 〈http://www.cs.rmit.edu.au/fedconf/index.html?page=odbase2008cfp〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00324469
Contributeur : Lisa Di Jorio <>
Soumis le : jeudi 25 septembre 2008 - 10:17:12
Dernière modification le : jeudi 24 mai 2018 - 15:59:22

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  • HAL Id : lirmm-00324469, version 1

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Lisa Di Jorio, Sandra Bringay, Céline Fiot, Anne Laurent, Maguelonne Teisseire. Sequential Patterns for Maintaining Ontologies Over Time. OTM/ODBASE'08: Ontologies, DataBases, and Applications of Semantics, Nov 2008, Monterrey, Mexico. Springer Verlag, pp.1385-1403, 2008, LNCS. 〈http://www.cs.rmit.edu.au/fedconf/index.html?page=odbase2008cfp〉. 〈lirmm-00324469〉

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