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BMCBI
2010
139views more  BMCBI 2010»
13 years 6 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
AI
2005
Springer
13 years 11 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
AUSDM
2007
Springer
222views Data Mining» more  AUSDM 2007»
14 years 10 days ago
CURIO: A Fast Outlier and Outlier Cluster Detection Algorithm for Large Datasets
Aaron Ceglar, John F. Roddick, David M. W. Powers
SDM
2003
SIAM
125views Data Mining» more  SDM 2003»
13 years 7 months ago
Scalable, Balanced Model-based Clustering
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
Shi Zhong, Joydeep Ghosh
ICDE
1999
IEEE
139views Database» more  ICDE 1999»
14 years 7 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...