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AI
2005
Springer
10 years 6 months ago
A Comparative Study of Two Density-Based Spatial Clustering Algorithms for Very Large Datasets
Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we ...
Xin Wang, Howard J. Hamilton
ICTAI
2006
IEEE
10 years 7 months ago
On the Relationships between Clustering and Spatial Co-location Pattern Mining
The goal of spatial co-location pattern mining is to find subsets of spatial features frequently located together in spatial proximity. Example co-location patterns include servi...
Yan Huang, Pusheng Zhang
ICDE
1999
IEEE
139views Database» more  ICDE 1999»
11 years 2 months ago
Clustering Large Datasets in Arbitrary Metric Spaces
Clustering partitions a collection of objects into groups called clusters, such that similar objects fall into the same group. Similarity between objects is defined by a distance ...
Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehr...
ISBRA
2007
Springer
10 years 7 months ago
Clustering Algorithms Optimizer: A Framework for Large Datasets
Clustering algorithms are employed in many bioinformatics tasks, including categorization of protein sequences and analysis of gene-expression data. Although these algorithms are r...
Roy Varshavsky, David Horn, Michal Linial
VLDB
2008
ACM
147views Database» more  VLDB 2008»
11 years 1 months ago
Tree-based partition querying: a methodology for computing medoids in large spatial datasets
Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous e...
Kyriakos Mouratidis, Dimitris Papadias, Spiros Pap...
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