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» Approximation algorithms for clustering uncertain data
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ICALP
2010
Springer
14 years 13 days ago
Clustering with Diversity
Abstract. We consider the clustering with diversity problem: given a set of colored points in a metric space, partition them into clusters such that each cluster has at least point...
Jian Li, Ke Yi, Qin Zhang
DASFAA
2003
IEEE
151views Database» more  DASFAA 2003»
14 years 29 days ago
Approximate String Matching in DNA Sequences
Approximate string matching on large DNA sequences data is very important in bioinformatics. Some studies have shown that suffix tree is an efficient data structure for approxim...
Lok-Lam Cheng, David Wai-Lok Cheung, Siu-Ming Yiu
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
14 years 8 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
SSD
2005
Springer
173views Database» more  SSD 2005»
14 years 1 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
CSDA
2006
82views more  CSDA 2006»
13 years 7 months ago
Nearest neighbours in least-squares data imputation algorithms with different missing patterns
Methods for imputation of missing data in the so-called least-squares approximation approach, a non-parametric computationally efficient multidimensional technique, are experiment...
Ito Wasito, Boris Mirkin