Presented by Michalis Vlachos and Spiros Papadimitriou at ICDM 2006, Hong-Kong
|9 Nov 2009||Helen Chen||
"Time-series are probably the most prevalent form of data storage and representation in most scientific fields. Examples include industrial or environmental measurements, medical monitoring, stock market analysis, etc. However, in order to efficiently search and explore the ever-increasing amount of collected data, one needs to deploy intelligent techniques for data compression/representation, data organization/pruning and similarity characterization. This tutorial will provide a unified, geometric view of data representation techniques. Furthermore, it will demonstrate how the above tasks can be performed within the environment of the Matlab programming language and software tool, which is easily accessible in many academic institutions.