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This paper describes an improved intelligent student advising system. Comparing it to the initial system, the improvements include: the initial system was integrated with WEKA, both K-means algorithm and Cobweb algorithm were implemented for training and testing data sets, and course and pathway recommendations were also implemented. The recommendations given by the improved system were based on the K-means algorithm only, and the results were meaningful. However, the quality of the recommendations could be improved. For that purpose, Cobweb algorithm was also experimented. The results showed that it is hard to identify proper parameters for Cobweb algorithm to produce meaningful clusters. Furthermore, the results of the experiments suggested that Cobweb algorithm is less efficient than K-means algorithm for this system. The results of the experiments also suggested that Cobweb algorithm is more reliable than K-means algorithm for this system. Future research should focus on improving the efficiency of Cobweb algorithm.
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