Data mining experiments on hop processing data

This paper presents results on research conducted on three hop processing data sets using two data mining methods: rule induction and belief network generation. We briefly describe the hop processing and reasons for inconsistency in the corresponding data sets. Then we discuss the significance of knowledge in the form of rules acquired by both applied data mining methods. Finally, we present validation results for both methods.