Mining Association and Correlation Patterns Simultaneously in Database

Data mining aims to discover useful patterns (rules) in large datasets. In order to enhance the interestingness of the patterns produced, we propose an algorithm to mine both association and correlation patterns among items. In the mining process the all-confidence and correlation-confidence measures are adopted simultaneously. The effectiveness of the proposed approach is demonstrated with the experiment results on some real data sets.