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Machine Learning: The Automation of Knowledge Acquition Using Kohonen Self-Organising Map Neural Network

Hani Mohamed Khalil, and Mohd. Nor Sulaiman, and Hussein Sheikh, and Elfadil Nazar, (2001) Machine Learning: The Automation of Knowledge Acquition Using Kohonen Self-Organising Map Neural Network. Malaysian Journal of Computer Science, 14 (1). pp. 68-82. ISSN 0127-9084

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Official URL: http://mjcs.fsktm.um.edu.my/detail.asp?AID=115

Affiliations

Universiti Teknologi Malaysia

Abstract

In machine learning, a key aspect is the acquisition of knowledge. As problems become more complex, and experts become scarce, the manual extraction of knowledge becomes very difficult. Hence, it is important that the task of knowledge acquisition be automated. This paper proposes a novel method that integrates neural network and expert system paradigms to produce an automated knowledge acquisition system. A rule-generation algorithm is proposed, whereby symbolic rules are generated from a neural network that has been trained by an unsupervised Kohonen self-organising map (KSOM) learning algorithm. The generated rules are evaluated and verified using an expert system inference engine. To demonstrate the applicability of the proposed method to real-world problems, a case study in medical diagnosis is presented.

Item Type:Journal
Keywords:Kohonen self-organising maps, Machine learning, Knowledge acquisition, Expert system, Rule extraction
Subjects:Q Science
ID Code:268

M. Ishikawa, “Neural Networks Approach to Rule Extraction”. IEEE Expert, 1995, pp. 6-9.

M. S. Kurzyn, “Expert Systems and Neural Networks: A Comparison”. IEEE Expert, 1993, pp. 222-223.

N. DeClaris, M. Su, “A Neural Network Based Approach to Knowledge Acquisition and Expert Systems”. IEEE Expert, 1993, pp. 645-650.

Carl G. Looney, Pattern Recognition Using Neural Network. Oxford University Press, New York. USA 1997.

A. Ultsch, D. Korus, Kleine, and T. O., “Integration of Neural Networks and Knowledge-Based Systems in Medicine”, in 5th. Conf. Artificial Intelligence in Medicine Europe AIME'95, Pavia, Italy, June 1995, in Barahona, P., Stefanelli, M., Wyatt, J.: Artificial Intelligence in Medicine, Lectures in Artificial Intelligence 934, Springer 1995, pp. 425-426.

A. Ultsch, S. Farsch, H. Li, “Automatic Acquisition of Medical Knowledge from Data Sets with Neural Networks”, in Proc. KI'95, Bielefeld/Germany, Advances in Artificial Intelligence, Springer 1995, pp. 258- 260.

A. Ultsch, “Knowledge Extraction from Self-organizing Neural Networks”, in O. Opitz, B. Lausen and R. Klar (Eds.): Information and Classification, Berlin, Springer Verlag, pp. 301-306.

A. Ultsch, “The Integration of Connectionist Models with Knowledge-based Systems: Hybrid Systems”, in Proceedings of the IEEE SMC 98 International Conference, San Diego, 11. - 14. October 1998, pp. 1530- 1535.

Teuvo Kohonen, Self-Organizing Maps. Springer, 1995, USA.

Juha Vesanto, “Data Mining Techniques Based on the Self Organizing Maps”. Helsinki University of Technology. Thesis M. Sc., 1997.

Sabrina Sestito, Automated Knowledge Acquisition. Prentice Hall, 1994, Australia.

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