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Weak Ratio Rules: A Generalized Boolean Association Rules

Weak Ratio Rules: A Generalized Boolean Association Rules

Baoqing Jiang, Xiaohua Hu, Qing Wei, Jingjing Song, Chong Han, Meng Liang
Copyright: © 2011 |Volume: 7 |Issue: 3 |Pages: 38
ISSN: 1548-3924|EISSN: 1548-3932|EISBN13: 9781613506356|DOI: 10.4018/jdwm.2011070103
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MLA

Jiang, Baoqing, et al. "Weak Ratio Rules: A Generalized Boolean Association Rules." IJDWM vol.7, no.3 2011: pp.50-87. http://doi.org/10.4018/jdwm.2011070103

APA

Jiang, B., Hu, X., Wei, Q., Song, J., Han, C., & Liang, M. (2011). Weak Ratio Rules: A Generalized Boolean Association Rules. International Journal of Data Warehousing and Mining (IJDWM), 7(3), 50-87. http://doi.org/10.4018/jdwm.2011070103

Chicago

Jiang, Baoqing, et al. "Weak Ratio Rules: A Generalized Boolean Association Rules," International Journal of Data Warehousing and Mining (IJDWM) 7, no.3: 50-87. http://doi.org/10.4018/jdwm.2011070103

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Abstract

This paper examines the problem of weak ratio rules between nonnegative real-valued data in a transactional database. The weak ratio rule is a weaker form than Flip Korn’s ratio rule. After analyzing the mathematical model of weak ratio rules problem, the authors conclude that it is a generalization of Boolean association rules problem and every weak ratio rule is supported by a Boolean association rule. Following the properties of weak ratio rules, the authors propose an algorithm for mining an important subset of weak ratio rules and construct a weak ratio rule uncertainty reasoning method. An example is given to show how to apply weak ratio rules to reconstruct lost data, and forecast and detect outliers.

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