Discovery of Temporal Association Rules in Multivariate Time Series

Abstract

This paper presents a method for discovering association rules in multivariable time series, proposes two efficient algorithms based on the basic ideas of the Apriori algorithm to discover the frequent patterns from single time series and multivariate time series. The advantage of the two algorithms is that it avoids multiple scans on the time series and can be extended to any number of time series.