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Mining Actionable Patterns by Role Models

12 years 1 months ago
Mining Actionable Patterns by Role Models
Data mining promises to discover valid and potentially useful patterns in data. Often, discovered patterns are not useful to the user. "Actionability" addresses this problem in that a pattern is deemed actionable if the user can act upon it in her favor. We introduce the notion of "action" as a domain-independent way to model the domain knowledge. Given a data set about actionable features and an utility measure, a pattern is actionable if it summarizes a population that can be acted upon towards a more promising population observed with a higher utility. We present several pruning strategies taking into account the actionability requirement to reduce the search space, and algorithms for mining all actionable patterns as well as mining the top k actionable patterns. We evaluate the usefulness of patterns and the focus of search on a real-world application domain.
Ke Wang, Yuelong Jiang, Alexander Tuzhilin
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2006
Where ICDE
Authors Ke Wang, Yuelong Jiang, Alexander Tuzhilin
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