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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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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00130778
Contributor : Joël Quinqueton <>
Submitted on : Tuesday, February 13, 2007 - 5:58:18 PM
Last modification on : Wednesday, June 24, 2020 - 4:18:07 PM
Long-term archiving on: : Tuesday, April 6, 2010 - 8:59:11 PM

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Joël Quinqueton, Pierre-Michel Riccio, Reena Shetty. Hybrid Model for Knowledge Representation. ICHIT: International Conference on Hybrid Information Technology, Nov 2006, Jeju Island, South Korea. pp.355-361, ⟨10.1109/ICHIT.2006.147⟩. ⟨lirmm-00130778⟩

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