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- W1872877 abstract "A drawback of traditional data mining methods is that they do not leverage prior knowledge of users. In many business settings, managers and analysts have significant intuition based on several years of experience. In prior work we proposed a method that could discover unexpected patterns in data by using this domain knowledge in a systematic manner. In this paper we continue our focus on discovering unexpected patterns and propose new methods for discovering a minimal set of unexpected patterns that discover orders of magnitude fewer patterns and yet retain most of the truly unexpected ones. We demonstrate the strengths of this approach experimentally using a case study application in a marketing domain." @default.
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- W1872877 date "2003-01-01" @default.
- W1872877 modified "2023-09-22" @default.
- W1872877 title "On Characterization and Discovery of Minimal Unexpected Patterns in Data Mining Applications" @default.
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