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» Data Clustering: A Review
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CEC
2005
IEEE
14 years 1 months ago
Improvements to the scalability of multiobjective clustering
In previous work, we have proposed a novel approach to data clustering based on the explicit optimization of a partitioning with respect to two complementary clustering objectives ...
Julia Handl, Joshua D. Knowles
ICDE
1999
IEEE
183views Database» more  ICDE 1999»
14 years 9 months ago
ROCK: A Robust Clustering Algorithm for Categorical Attributes
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim
KDD
2009
ACM
208views Data Mining» more  KDD 2009»
14 years 8 months ago
A principled and flexible framework for finding alternative clusterings
The aim of data mining is to find novel and actionable insights in data. However, most algorithms typically just find a single (possibly non-novel/actionable) interpretation of th...
Zijie Qi, Ian Davidson
KDD
2006
ACM
173views Data Mining» more  KDD 2006»
14 years 8 months ago
Robust information-theoretic clustering
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...
Christian Böhm, Christos Faloutsos, Claudia P...
CIDM
2009
IEEE
14 years 2 months ago
Density-based clustering of polygons
– Clustering is an important task in spatial data mining and spatial analysis. We propose a clustering algorithm P-DBSCAN to cluster polygons in space. PDBSCAN is based on the we...
Deepti Joshi, Ashok Samal, Leen-Kiat Soh