Mining Sequence Pattern from Time Series Based on Inter-relevant Successive Trees Model

摘要

In this paper, a novel method is proposed to discover frequent pattern from time series. It first segments time series based on perceptually important points, then converted it into meaningful symbol sequences by the relative scope, finally used a new mining model to find frequent patterns. Compared with the previous methods, the method is simpler and more efficient.