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GIS
2002
ACM
13 years 7 months ago
Opening the black box: interactive hierarchical clustering for multivariate spatial patterns
Clustering is one of the most important tasks for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial c...
Diansheng Guo, Donna Peuquet, Mark Gahegan
VLDB
1998
ACM
112views Database» more  VLDB 1998»
13 years 11 months ago
Incremental Clustering for Mining in a Data Warehousing Environment
Data warehouses provide a great deal of opportunities for performing data mining tasks such as classification and clustering. Typically, updates are collected and applied to the d...
Martin Ester, Hans-Peter Kriegel, Jörg Sander...
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
14 years 8 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
PVLDB
2010
86views more  PVLDB 2010»
13 years 6 months ago
Swarm: Mining Relaxed Temporal Moving Object Clusters
Recent improvements in positioning technology make massive moving object data widely available. One important analysis is to find the moving objects that travel together. Existin...
Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays
CINQ
2004
Springer
225views Database» more  CINQ 2004»
14 years 28 days ago
A Data Mining Query Language for Knowledge Discovery in a Geographical Information System
Spatial data mining is a process used to discover interesting but not explicitly available, highly usable patterns embedded in both spatial and nonspatial data, which are possibly ...
Donato Malerba, Annalisa Appice, Michelangelo Ceci