Similarity search in time series databases using moments

Similarity search in time series data is an area of active interest in the data mining community. In this paper we introduce a simple and novel approach for performing similarity search over time series data using moments. This technique is based on the observation that similar time sequences will have their centroids close to each other. The proposed technique is capable of handling variable length queries and works irrespective of global scaling and shrinking of time series data. It can also handle vertical shifts.