A Dynamic Knowledge Representation Model based on Hybrid Approach

Abstract : Our fundamental objective is to tackle the problem faced in the field of information retrieval and classification in the current era of information overflow by proposing better and efficient knowledge representation techniques. In order to realize this we developed a model called Extended Semantic Network which explores a new dimension in combining machine designed knowledge networks with that of human reasoning. The network so built attempts in bridging human precision and machine recall to bring out a new knowledge representation model. In this paper we explore the possibility of using our model is building efficient ontologies with considerably lowered cost and time for construction.
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Article dans une revue
International Journal of Digital Content Technology and its Applications (JDCTA), Convergence Information Society (CIS), Korea, 2007, 2 (3), pp.29-38
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00370483
Contributeur : Joël Quinqueton <>
Soumis le : mardi 24 mars 2009 - 14:45:17
Dernière modification le : jeudi 24 mai 2018 - 15:59:20

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  • HAL Id : lirmm-00370483, version 1

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Reena Shetty, Joël Quinqueton, Pierre-Michel Riccio. A Dynamic Knowledge Representation Model based on Hybrid Approach. International Journal of Digital Content Technology and its Applications (JDCTA), Convergence Information Society (CIS), Korea, 2007, 2 (3), pp.29-38. 〈lirmm-00370483〉

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