Feature extraction from time series data

Abstract

Many scientific and business domains require the collection and analysis of time series data. Feature extraction is an important component of time series data mining. In this paper, we introduce simple and novel techniques for feature extraction from time series data based on moments and slopes. The proposed techniques are capable of handling vertical and horizontal shifts existing between time sequences. They can also handle global scaling and shrinking of the time sequences.