When applying association mining to real datasets, a major obstacle is that often a huge number of rules are generated even with very reasonable support and confidence. Among thes...
Ping Chen, Rakesh M. Verma, Janet C. Meininger, We...
We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
Abstract-Mining generalized association rules between items in the presence of taxonomy has been recognized as an important model in data mining. Earlier work on mining generalized...
Efficient discover of association rules in large databases is a we 1 studied problem and several ap-1y proaches have been proposed. However, it is non trivial to maintain the asso...
This paper presents an active learning approach to the problem of systematic noise inference and noise elimination, specifically the inference of Associated Corruption (AC) rules...