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SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
14 years 5 months ago
Constraint-Based Subspace Clustering.
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
Élisa Fromont, Adriana Prado, Céline...
VLDB
1994
ACM
140views Database» more  VLDB 1994»
14 years 3 days ago
Efficient and Effective Clustering Methods for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering ...
Raymond T. Ng, Jiawei Han
AI
2005
Springer
14 years 1 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
ICML
2005
IEEE
14 years 8 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
CLUSTER
2007
IEEE
14 years 2 months ago
Sequential and parallel implementation of a constraint-based algorithm for searching protein structures
— Data mining in biological structure libraries can be a powerful tool to better understand biochemical processes. This article introduces the LISA algorithm which enables the re...
Sascha Hunold, Thomas Rauber, Georg Wille