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14

ICDM
2006
IEEE

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Spatial Multidimensional Sequence Clustering

14 years 9 days ago

Spatial Multidimensional Sequence Clustering

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Measurements at different time points and positions in large temporal or spatial databases requires effective and efﬁcient data mining techniques. For several parallel measurements, ﬁnding clusters of arbitrary length and number of attributes, poses additional challenges. We present a novel algorithm capable of ﬁnding parallel clusters in different structural quality parameter values for river sequences used by hydrologists to develop measures for river quality improvements.

Ira Assent, Ralph Krieger, Boris Glavic, Thomas Se

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Data Mining | ICDM 2006 | Parallel Clusters | Parallel Measurements | River Quality Improvements |

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Added	11 Jun 2010
Updated	11 Jun 2010
Type	Conference
Year	2006
Where	ICDM
Authors	Ira Assent, Ralph Krieger, Boris Glavic, Thomas Seidl

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