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Published in:
2006 | OriginalPaper | Chapter
Causal Difference Detection Using Bayesian Networks
Authors : Tomoko Murakami, Ryohei Orihara
Published in: PRICAI 2006: Trends in Artificial Intelligence
Publisher: Springer Berlin Heidelberg
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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.