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» Techniques of Cluster Algorithms in Data Mining
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139
Voted
GIS
2002
ACM
15 years 1 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
130
Voted
PAKDD
1998
ACM
103views Data Mining» more  PAKDD 1998»
15 years 6 months ago
Discovering Case Knowledge Using Data Mining
The use of Data Mining in removing current bottlenecks within Case-based Reasoning (CBR) systems is investigated along with the possible role of CBR in providing a knowledge manag...
Sarabjot S. Anand, David W. Patterson, John G. Hug...
GIS
2007
ACM
16 years 2 months ago
Using fuzzy clustering methods for delineating urban housing submarkets
This study investigates whether a fuzzy clustering method is of any practical value in delineating urban housing submarkets relative to clustering methods based on classic (or cri...
Sungsoon Hwang, Jean-Claude Thill
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
15 years 11 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
KDD
2005
ACM
112views Data Mining» more  KDD 2005»
16 years 2 months ago
Model-based overlapping clustering
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh,...