An Online Algorithm for Segmenting Time Series Export

@inproceedings{citeulike:915953, abstract = {In recent years, there has been an explosion of interest in mining time series databases. As with most computer science problems, representation of the data is the key to efficient and effective solutions. One of the most commonly used representations is piecewise linear approximation. This representation has been used by various researchers to support clustering, classification, indexing and association rule mining of time series data. A variety of algorithms have been proposed to obtain this...}, author = {Keogh, Eamonn J. and Chu, Selina and Hart, David and Pazzani, Michael J.}, booktitle = {ICDM}, citeulike-article-id = {915953}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.6570}, keywords = {approximation, segmentation, time-series}, pages = {289--296}, posted-at = {2007-11-20 15:35:15}, priority = {0}, title = {An Online Algorithm for Segmenting Time Series}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.6570}, year = {2001} }

TY - CONF ID - citeulike:915953 L3 - citeulike-article-id:915953 N2 - In recent years, there has been an explosion of interest in mining time series databases. As with most computer science problems, representation of the data is the key to efficient and effective solutions. One of the most commonly used representations is piecewise linear approximation. This representation has been used by various researchers to support clustering, classification, indexing and association rule mining of time series data. A variety of algorithms have been proposed to obtain this... EP - 296 TI - An Online Algorithm for Segmenting Time Series T2 - ICDM SP - 289 KW - approximation KW - segmentation KW - time-series AU - Keogh, Eamonn AU - Chu, Selina AU - Hart, David AU - Pazzani, Michael PY - 2001/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.6570 ER -