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WIREs Data Mining Knowl Discov
Impact Factor: 2.541

Contrast and change mining

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Abstract Because the world with its markets, innovations, and customers is changing faster than ever before, the key to survival for businesses is the ability to detect, assess, and respond to changing conditions timely and intelligently. Understanding changes and reacting to or acting upon them therefore become a strategic issue not only for companies but also in many other domains. The corresponding need for knowledge has been answered by data mining research by proposing a multitude of methods for analyzing different aspects of change. This article provides an overview of recent works on methods for change analysis, thereby focusing on contrast mining and change mining, the two emerging subfields of contemporary data mining research. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 215–230 DOI: 10.1002/widm.27 This article is categorized under: Algorithmic Development > Spatial and Temporal Data Mining Technologies > Association Rules Technologies > Structure Discovery and Clustering

Stock market example: price history from July 17, 2008 to July 17, 2009.

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The support histories of two item sets X and Z taken from real‐world data.

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Pattern histories of support and confidence.

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The ‘same attribute and same cut’ method for comparing decision trees.

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The ‘new decision tree’ method for comparing decision trees.

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Two decision trees, each one learned from data of a different time period.

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Technologies > Structure Discovery and Clustering
Algorithmic Development > Spatial and Temporal Data Mining
Technologies > Association Rules

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