Commenced in January 2007
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Model for Knowledge Representation using Sample Problems and Designing a Program for Automatically Solving Algebraic Problems

Authors: Nhon Do, Hien Nguyen


Nowadays there are many methods for representing knowledge such as semantic network, neural network, and conceptual graphs. Nonetheless, these methods are not sufficiently efficient when applied to perform and deduce on knowledge domains about supporting in general education such as algebra, analysis or plane geometry. This leads to the introduction of computational network which is a useful tool for representation knowledge base, especially for computational knowledge, especially knowledge domain about general education. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. Besides that, when finding related problems, we have to determine whether the result of them can be used to solve the practical problem or not. In this paper, the extension model of computational network has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking, and give the good solution for the practical problem faster and more effectively. This extension model is applied to construct an automatic system for solving algebraic problems in middle school.

Keywords: Artificial Intelligence, Knowledge Representation, Educational Software, Knowledge base system

Digital Object Identifier (DOI):

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[1] Stuart Russell & Peter Norvig, Artificial Intelligence - A modern approach (second edition), Prentice Hall (2003).
[2] John F. Sowa. Knowledge Representation: Logical, Philosophical and Computational Foundations, Brooks/Cole (2000).
[3] Do Van Nhon, Constructing intelligent systems for computation - Research and development of knowledge representation models to design systems for automated solving problems, PhD. thesis, National University of Ho Chi Minh City (2001-2002).
[4] Hoang Kiem & Do Van Nhon, Extension and development of the knowledge models of computational objects, Proceedings of National Conference of some selective problems of Information Technology, Publisher of Science and Technology (2005).
[5] Do Van Nhon, The architecture of a system for solving problems for learners and design techniques, Scientific magazine of Education and Technology, Technical teachers- college of Ho Chi Minh City, No 2(4) 2007.
[6] Nhon Do, An ontology for knowledge representation and Applications, Proceeding of World Academy of science, engineer and technology, vol. 32, August 2008, ISSN: 2070-370.
[7] Nhon Van Do &Tam Pham Huu, Extensive Computational Networks And Applying in an Educational Software, Proceedings of 2009 International Conference on Artificial Intelligence and Education (ICAIE 2009), Wuhan, China, 2009.
[8] Nhon Van Do, Computational Networks for Knowledge Representation, World Academy of Science, Engineering and Technology, Volume 56, August 2009, ISSN 2070 - 3724 (ICCSISE 2009), Singapore, 2009.
[9] Vietnam Ministry of Education and Training, Textbook and workbook of algebra in middle school, Publisher of Education (2006-2007).
[10] George F. Luger & William A Stubblefield, Artificial Intelligence, Addison Wesley Longman, Inc (1998).
[11] G. Polya. How to solve it, Publisher of Education (1997).
[12] Lakemeyer, G. & Nebel, B. (1994), Foundations of Knowledge representation and Reasoning. Berlin Heidelberg: Springer-Verlag (1994).
[13] ToshinoriMunakata, Fundamentals of the New Artificial Intelligence: Neural, Evolutionary, Fuzzy and More, Springer-Verlag London Limited (2008).
[14] Frank van Harmelem & Vladimir & Bruce, Handbook of Knowledge Representation, Elsevier (2008).