Combined Pattern Mining: from Learned Rules to Actionable Knowledge

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Conference Proceeding
AI 2008: Advances in Artificial Intelligence: Lecture Notes in Artificial Intelligence 5360, 2008, pp. 393 - 403
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Association mining often produces large collections of association rules that are difficult to understand and put into action. In this paper, we have designed a novel notion of combined patterns to extract useful and actionable knowledge from a large amount of learned rules. We also present definitions of combined patterns, design novel metrics to measure their interestingness and analyze the redundancy in combined patterns. Experimental results on real-life social security data demonstrate the effectiveness and potential of the proposed approach in extracting actionable knowledge from complex data.
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