A clustering algorithm based on Bayesian network learning system

Construction of Student Model for Bayesian network-based Intelligent Tutoring System belongs to one of the major content for individualized teaching strategies, which plays crucial role during the whole process of research. Only after the reasonable student model is established, can analysis of the learning characteristics be carried out accordingly so that learning strategy can be made for individualized learning. This paper presents an algorithm to obtain students' feature information using data mining technique. Researchers who are interested in different teaching strategy are referred to this piece of work.

[1]  Zheng Rong Yang,et al.  A biology inspired neural learning algorithm for analysing protein sequences , 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

[2]  William H. Hsu,et al.  A Survey of Algorithms for Real-Time Bayesian Network Inference , 2002 .

[3]  Godfried T. Toussaint,et al.  An algorithm for computing the restriction scaffold assignment problem in computational biology , 2005, Inf. Process. Lett..

[4]  Ya-Dong Wang,et al.  The research and application of the self-learning expert system based on BP network , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[5]  Gonzalo Guillén-Gosálbez,et al.  Outer approximation-based algorithm for biotechnology studies in systems biology , 2010, Comput. Chem. Eng..

[6]  Yang Liu,et al.  A new Q-learning algorithm based on the metropolis criterion , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).