Abstract
The proposition Extended Semantic Network is an innovative tool for Knowledge Representation and Ontology construction, which not only infers meanings but looks for sets of associations between nodes as opposed to the present method of keyword association. The objective here is to achieve semi-supervised knowledge representation technique with good accuracy and minimum human intervention. This is realized by obtaining a technical co-operation between mathematical and mind models to harvest their collective intelligence.
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Naiaiya F. Noy and Deborah L. McGuinness, Ontology Development 101: A Guide to Creating Your First Ontology, Stanford University, Stanford, CA.
T.R. Gruber, “Toward Principle for the design of ontologies used for Knowledge Sharing”, in Proc. Of International Workshop on Formal Ontology, March 1993.
Briekley, D. and Guha, R.V. Resource Description Framework (RDF) Schema Specification. Proposed Recommendation: World Wide Web Consortium, 1999.
Helder, J. and McGuinness, D.L., The DARPA Agent Markup Language. IEEE Intelligent Systems. 2000.
Natalya F. Noy, Michel Sintek, Stefan Decker, onica Crubézy. Kay W. Fergerson and Mark A. Musen, Creating Semantic web Contents With protégé 2000, Stanford University, IEEE Intelligent Systems. 2001.
J.F Sowa, Knowledge Representation: Logical, Philosophical, and Computational Foundations, Brooks Cole Publishing Co., Pacific Grove, CA, 2000.
J Voss, P Danowski, B Chapter-citebase.eprinls.org, 2005.
M.R Quillian, Semantic memory. M Minsky, Ed, Semantic Information Processing. pp.216–270. Cambridge, Massachusetts: MIT Press, 1968.
J.F Sowa, Conceptual structures: information processing in mind and machine, Addison-Wesley Longman Publishing Co., Inc. Boston. MA. 1984.
J Brachman. L Deborah. McGuinness. F Patel-Sehneider, A Resnick Living with CLASSIC: When and How to Use a KL-ONE-Like Language, 1991.
Rational Corporation: UML Notation Guide 2, 2000.
M.E Winston, R Chaffin and D Hernnann, A taxonomy of part — Whole Relations Cognitive Science 11, 1987.
S.A. Mané, P.M. Riccio et S. Vailliès: des elements pour un modèle: la lutte des classes! Revue Génie Logiciel, n°58, Paris, septembre 2001.
M Ménager, Programme Toxicologie Nucléairc Environnementale: Comment fédérer et créer une communauté scientifique autour d’un enjue de société, Intelligence Collective Partage et Redistribution des Savoirs, Nimes, France, septembre, 2004.
J Aberg & N Shahmehri, User Modelling an Aid for Human Web Assistants. User Modeling 2001: 8th International Conference, UM 2001, Southaven, Germany, July 13–17, 2001.
E Reingold, J Nightingale, “Artificial Intelligence”.
Alexander maedche & Steffen Staab. “Ontology Learning for the Semantic Web”.
J Link-Pezet, P Glize, C Régis, A cognitive approach to intelligent databases, On line, London: Learned Information, 1992.
N.J Befkin, W.B Croft, Information Filtering and Information Retrieval: Two Sides of the Same Coin?, Communications of the ACM Vol. 35 no12, 1992
R Davis, B.G Buchanann, Meta-Level knowledge: Overview and applications, IJCAI, ACM SIGIR, no 5, Cambridge, 1984.
A Maedche, S Staab, Representation & Learning, IEEE Intelligent Systems, 2001.
E Rosen and B. Mervis, Family Resemblances: Studies in the Internal Structure of Categories, University of California. Berkeley, 1989
E Rosch Cognitive Representation of Semantic Categories, University of California, Berkeley, 1978
E Rosch “Cognitive Reference Points”, University of California, Berkeley, 1978.
N. Cuarino, C. Masoio, and G. Vetere, “Ontoseek: Content-based Access to the Web,” IEEE Intelligent Systems, Volume 14, no. 3. pp. 70–80, 1999
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Shetty, R.T.N., Riccio, PM., Quinqueton, J. (2006). Extended Semantic Network for Knowledge Representation. In: Shi, Z., Shimohara, K., Feng, D. (eds) Intelligent Information Processing III. IIP 2006. IFIP International Federation for Information Processing, vol 228. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-44641-7_14
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DOI: https://doi.org/10.1007/978-0-387-44641-7_14
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