AN IMPROVED ALGORITHM FOR IDENTIFYING NEGATIVE ASSOCIATION RULES
Yuming Ou · Journal of Guangxi Normal University · 2004
Negative association rules (NAR) catch mutually-exclusive correlations among items.They play important roles just as traditional association rules (TAR) do.For example,in stock market surveillance based on alert-logs,NARs detect which alerts are false.There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets.This paper presents a new algorithm for mining horn-clause-based negative association rules.To evaluate this algorithm,the authors have illustrated the efficiency by a group of experiments.