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...
We have a large database consisting of sales transactions. We investigate the problem of online mining of association rules in this large database. We show how to preprocess the d...
This paper investigates a brute-force technique for mining classification rules from large data sets. We employ an association rule miner enhanced with new pruning strategies to c...
Frequent constraint violations on the data stored in a database may suggest that the semantics of the represented reality is changing. In this work we propose a methodology and a t...
In this paper, we discuss a problem of finding risk patterns in medical data. We define risk patterns by a statistical metric, relative risk, which has been widely used in epidemi...
Jiuyong Li, Ada Wai-Chee Fu, Hongxing He, Jie Chen...