Abstract
The increasing of the knowledge of mankind benefits from the concept learning. Based on the analysis of the common procedure of children’s actions during recognizing the world, a cognitive model of concept learning is set up. A general multi-concept learning algorithm, a method of knowledge representation based on general rules, a logical structure in the forest shape, and a uniform data structure for storage are accordingly presented. Thus, a complete and more scientific knowledge acquisition and application case used for building knowledge base of many kinds of AI system based on knowledge is provided. Further more, with this method, a large scale knowledge base containing more extensive domains can be build. At last, comparing with some ontology knowledge bases, such as CYC, WordNet, NKI and so on, three different characteristics of this learning method are identified and the good application prospects are discussed.
This work is supported by NSF Grant #50811120111 and #40971275.
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References
Wang, S., Wang, A.: Cognitive Psychology, pp. 240–264. Beijing University Press, Beijing (1992)
Kong, F.: Principle of Knowledge Base System, pp. 4–6. Zhejang University Press, Hangzhou (2000)
Cai, Z., Xu, G.: Artificial intelligence and applications, pp. 200–204. TsingHua University Press, Beijing (1996)
Guarino, N.: Understanding, Building and using Ontologies. Human-Computer Studies  46(1), 293–310 (1997)
Gu, F., Cao, C.: Ontology research and existing problems in knowledge engineering. Computer Science 31(10), 1–10 (2004)
Navigi, R., Velardi, P., Gangemi, A.: Ontology learning and its application to automated terminology Translation. IEEE Intelligent System 18(1), 22–31 (2003)
Lenat, D., Guha, P.: Building large knowledge based systems: Representation and Inference in the CYC project. Addision-Wesley (1990)
Lenat, D.: CYC: a large scale investment in knowledge infrastructure. Communication of ACM 38(11), 33–38 (1995)
Miier, G.: WordNet: An on-line lexical database. International Journal of Lexicograph 3(4), 234–244 (1990)
Vetulani, Z., Walkowska, J., Obrębski, T., Marciniak, J., Konieczka, P., Rzepecki, P.: An Algorithm for Building Lexical Semantic Network and Its Application to PolNet - Polish WordNet Project. In: Vetulani, Z., Uszkoreit, H. (eds.) LTC 2007. LNCS, vol. 5603, pp. 369–381. Springer, Heidelberg (2009)
Cao, C., Feng, Q., Gao, Y.: Progress in the development of National Knowledge Infrastructure. Journal of Computer Science and Technology 17(5), 523–534 (2002)
Sui, Y., Gao, Y., Cao, C.: Ontologies, Frames and logical theories in NKI. Journal of Software 16(12), 2046–2053 (2005)
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Zhu, S., Wang, Y., Huang, X. (2012). A Method of General Multi-Concept Learning Based on Cognitive Model. In: Wu, Y. (eds) Software Engineering and Knowledge Engineering: Theory and Practice. Advances in Intelligent and Soft Computing, vol 114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03718-4_43
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DOI: https://doi.org/10.1007/978-3-642-03718-4_43
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