C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
Weighing and Integrating Evidence for Stochastic Simulation in Bayesian Networks
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
On detecting differences between groups
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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In analysis of the market, detecting not only differences in consumer groups or changes but also their causal factors observed in consumer behavior is expected because it enables the marketer to take marketing actions. Although rule-discovery approaches can efficiently identify differences in groups or changes, it is still difficult to explain the causes of them. In this paper we propose an algorithm to detect causal differences in two bayesian networks by search and probability inference. We perform some experimental studies to analyze consumer behavior in purchasing personal computer.