Grid Representation for Efficient Similarity Search in Time Series Databases

Widespread interest in time-series similarity search has made more in need of efficient technique, which can reduce dimensionality of the data and then to index it easily using a multidimensional structure. In this paper, we introduce a new technique, which we called grid representation, based on a grid approximation of the data. We propose a lower bounding distance measure that enables a bitmap approach for fast computation and searching. We also show how grid representation can be indexed with a multidimensional index structure, and demonstrate its superiority.