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» Detection of Spatial Changes using Spatial Data Mining
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ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
14 years 2 months ago
Spatial Multidimensional Sequence Clustering
Measurements at different time points and positions in large temporal or spatial databases requires effective and efficient data mining techniques. For several parallel measureme...
Ira Assent, Ralph Krieger, Boris Glavic, Thomas Se...
EUROPAR
2001
Springer
14 years 17 days ago
Experiments in Parallel Clustering with DBSCAN
We present a new result concerning the parallelisation of DBSCAN, a Data Mining algorithm for density-based spatial clustering. The overall structure of DBSCAN has been mapped to a...
Domenica Arlia, Massimo Coppola
SBIA
1995
Springer
13 years 11 months ago
Modeling the Influence of Non-Changing Quantities
ion Framework for Compositional Modeling 36 Diane Chi and Yumi Iwasaki Model Decomposition and Simulation 45 Daniel J. Clancy and Benjamin Kuipers A Distance Measure for Attention ...
Bert Bredeweg, Kees de Koning, Cis Schut
JIDM
2010
145views more  JIDM 2010»
13 years 6 months ago
Mining Relevant and Extreme Patterns on Climate Time Series with CLIPSMiner
One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensification of na...
Luciana A. S. Romani, Ana Maria Heuminski de &Aacu...
CIKM
2009
Springer
13 years 11 months ago
Mining data streams with periodically changing distributions
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
Yingying Tao, M. Tamer Özsu