Hybrid Model for Knowledge Representation

Abstract : In this paper the fundamental idea is to develop and explore an innovative approach of completing human designed networks with that of machine built word networks. This network forms a hybrid method which combines human precision with that of machine computation to form a knowledge representation model. This model in turn encourages faster and efficient construction of automatic ontology. Our objective is to tackle the problem faced in the field of information retrieval and classification in the current era of information over flow
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Communication dans un congrès
G. Lee and D. Slezak and T. kim and P. Sloot and H. Kim and M. Szczuka. ICHIT'06: International Conference on Hybrid Information Technology, Nov 2006, France. IEEE Computer Society, pp.355-361, 2006, 〈10.1109/ICHIT.2006.147〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00130778
Contributeur : Joël Quinqueton <>
Soumis le : mardi 13 février 2007 - 17:58:18
Dernière modification le : vendredi 9 février 2018 - 16:58:06
Document(s) archivé(s) le : mardi 6 avril 2010 - 20:59:11

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Joël Quinqueton, Pierre-Michel Riccio, Reena Shetty. Hybrid Model for Knowledge Representation. G. Lee and D. Slezak and T. kim and P. Sloot and H. Kim and M. Szczuka. ICHIT'06: International Conference on Hybrid Information Technology, Nov 2006, France. IEEE Computer Society, pp.355-361, 2006, 〈10.1109/ICHIT.2006.147〉. 〈lirmm-00130778〉

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