Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
A Context Search algorithm used for lexical knowledge acquisition is presented. Knowledge representation based on psycholinguistic theories of cognitive processes allows for implementation of a computational model of semantic memory in the form of semantic network. Knowledge acquisition using supervised dialog templates have been performed in a word game designed to guess the concept a human user is thinking about. The game that has been implemented on a web server, demonstrates elementary linguistic competencies based on lexical knowledge stored in semantic memory, enabling at the same time acquisition and validation of knowledge. Possible applications of the algorithm in domains of medical diagnosis and information retrieval are sketched.
Czasopismo
Rocznik
Tom
Strony
81--96
Opis fizyczny
Bibliogr. 32 poz., wykr.
Twórcy
autor
autor
- Department of Computer Systems Architecture Gdańsk University of Technology, Poland, julian.szymanski@eti.pg.gda.pl
Bibliografia
- Burke, D., MacKay, D.,Worthley, J. and Wade, E. (1991) On the tip of the tongue: What causes word finding failures in young and older adults. Journal of Memory and Language 30 (5), 542-579.
- Calzolari, N. (1984) Machine-readable dictionaries, lexical data bases and the lexical system. In: Proceedings of 10th International Conference on Computational Linguistics. Association for Computational Linguistics, 460-460.
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- Coren, S. and Ward, L.M. (1994) Sensation and Perception. Harcourt Brace, Toronto, 4th edition.
- Cullen, J., Bryman, A. (1988) The knowledge acquisition bottleneck: time for reassessment? Expert Systems 5 (3), 216-225.
- Davis,R., Shrobe,H. and Szolovits,P. (1993) What Is a Knowledge Representation? AI Magazine 14 (1), 17-33.
- DSM (1994) Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association.
- Duch,W., Matykiewicz,P. and Pestian, J. (2008) Neurolinguistic approach to natural language processing with applications to medical text analysis. Neural Networks 21 (10), 1500-1510.
- Duch,W. and Naud,A. (1996) Multidimensional scaling and Kohonen’s selforganizing maps. In: Proc. of the 2nd Conference „Neural Networks and their Applications”. Szczyrk, Poland, I, 138-143.
- Duch, W. and Szymański, J. (2008) Semantic web: Asking the right questions. In: Proceedings of the 7 International Conference on Information and Management Sciences. California Polytechnic State University Press.
- Gleason, J.B. and Ratner,N. B. (1997) Psycholinguistics. Wadsworth Publishing, 2nd edition.
- Goldberg, D. (1989) Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA.
- Guarino, N. and Poli, R. (1995) Formal ontology, conceptual analysis and knowledge representation. International Journal of Human Computer Studies 43 (5), 625-640.
- Hunston, S. (2001) Word frequencies in written and spoken English: Based on the British national corpus. Language Awareness 11 (2), 152-157.
- Liu, H. and Singh, P. (2004) ConceptNet. A Practical Commonsense Reasoning Tool-Kit. BT Technology Journal 22 (4), 211-226.
- Ripps, L.J. and Shoben, E.J. (1973) Semantic distance and the verification of semantic relations. Journal of Verbal Learning and Verbal Behavior 12, 1-20.
- Majewski, P. and Szymański, J. (2008) Text categorisation with semantic common sense knowledge: first results. In: Proceedings of 14th International Conference on Neural Information Processing. Springer, LNCS, 285-294.
- Manning,C. and Schutze,H. (1999) Foundations of Statistical Natural Language Processing. Massachusetts Institute of Technology Press.
- Martin, A. and Chao, L. (2001) Semantic memory and the brain: structure and processes. Current Opinion in Neurobiology 11 (2), 194-201.
- McClelland, J. and Rogers, T. (2003) The parallel distributed processing approach to semantic cognition. Nature Reviews Neuroscience 4 (4), 310-322.
- Miller,G.A., Beckitch,R., Fellbaum,C., Gross,D. and Miller,K. (1993) Introduction to WordNet: An On-line Lexical Database. Cognitive Science Laboratory, Princeton University Press.
- Pulvermüller, F. (2003) The Neuroscience of Language. On Brain Circuits of Words and Serial Order. Cambridge University Press.
- Quinlan, J. (1986) Induction of decision trees. Machine Learning 1 (1), 81-106.
- Ritter, H. and Kohonen, T. (1989) Self-organizing semantic maps. Biological Cybernetics 61 (1), 241-254.
- Sowa, J. (1991) Principles of Semantic Networks: Explorations in the Representation of Knowledge. Morgan Kaufmann, Series in Representation and Reasoning. San Mateo, CA.
- Staab, S. and Studer, R. (2004) Handbook on Ontologies. Springer Verlag.
- Szymański, J. and Duch, W. (2011) Induction of the common-sense hierarchie in lexical data. In: Proc. of 17th Int. Conf. on Neural Information Processing. LNCS 7063. Springer, 726-734.
- Szymański, J., Sarnatowicz,T. and Duch,W. (2008) Towards avatars with artificial minds: Role of semantic memory. Journal of Ubiquitous Computing and Intelligence 2, 1-11.
- Tulving,E., Bower,G. and Donaldson,W. (1972) Organization of Memory. New York: Academic Press.
- Vanderwende, L., Kacmarcik,G., Suzuki,H., Menezes,A. (2005) Mind-Net: an automatically created lexical resource. In: Proceedings of HLT/EMNLP on Interactive Demonstrations. ACL, Morristown, NJ, USA, 8-19.
- Voss, P. (2007) Essentials of General Intelligence: The Direct Path to Artificial General Intelligence. In: B. Goertzel and C. Pennachin, eds., Artificial General Intelligence. Series Cognitive Technologies. Springer, Berlin-Heidelberg, 131-157.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATC-0009-0038