Finding Similarity in Time Series Data by Method of Time Weighted Moments

Similarity search in time series data is an active area of research in data mining. In this paper we introduce a new approach for performing similarity search over time series data using second moments denoted by us as time weighted 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. It works irrespective of global scaling and shrinking of time series data and can also handle different baselines.

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