Weak Ratio Rules: A Generalized Boolean Association Rules

Baoqing Jiang, Xiaohua Hu, Qing Wei, Jingjing Song, Chong Han and Meng Liang
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Baoqing Jiang: Henan University, China
Xiaohua Hu: Henan University China, and Drexel Univeristy, USA
Qing Wei: Henan University of Economics and Law, China
Jingjing Song: Qingyuan Polytechnic, China
Chong Han: Henan University, China
Meng Liang: Henan University, China

International Journal of Data Warehousing and Mining (IJDWM), 2011, vol. 7, issue 3, 50-87

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.

Date: 2011
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