Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...
Several algorithms have been proposed for finding the “best,” “optimal,” or “most interesting” rule(s) in a database according to a variety of metrics including confid...
In recent years, the concept of temporal association rule (TAR) has been introduced in order to solve the problem on handling time series by including time expressions into associ...
Vincent T. Y. Ng, Stephen Chi-fai Chan, Derek Lau,...
Abstract. Frequent itemsets and association rules are generally accepted concepts in analyzing item-based databases. The Apriori-framework was developed for analyzing categorical d...