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Data Mining In Time Series Databases
Posted on 2010-04-15
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More edited by Mark Last, Abraham Kandel, Horst Bunke Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed. Download: Password: & 119;& 119;& 119;& 46;& 65;& 118;& 97;& 120;& 72;& 111;& 109;& 101;& 46;& 114;& 117;
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