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» Mining evolving data streams for frequent patterns
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SDM
2009
SIAM
170views Data Mining» more  SDM 2009»
15 years 6 months ago
Mining Complex Spatio-Temporal Sequence Patterns.
Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often...
Florian Verhein
83
Voted
AUSDM
2008
Springer
221views Data Mining» more  AUSDM 2008»
14 years 11 months ago
Mining Medical Specialist Billing Patterns for Health Service Management
This paper presents an application of association rule mining in compliance in the context of health service management. There are approximately 500 million transactions processed...
Yin Shan, David Jeacocke, D. Wayne Murray, Alison ...
GIS
2004
ACM
15 years 10 months ago
A partial join approach for mining co-location patterns
Spatial co-location patterns represent the subsets of events whose instances are frequently located together in geographic space. We identified the computational bottleneck in the...
Jin Soung Yoo, Shashi Shekhar
ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
15 years 4 months ago
Zonal Co-location Pattern Discovery with Dynamic Parameters
Zonal co-location patterns represent subsets of featuretypes that are frequently located in a subset of space (i.e., zone). Discovering zonal spatial co-location patterns is an im...
Mete Celik, James M. Kang, Shashi Shekhar
IS
2008
14 years 9 months ago
Continuous subspace clustering in streaming time series
Performing data mining tasks in streaming data is considered a challenging research direction, due to the continuous data evolution. In this work, we focus on the problem of clust...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...