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» The Method of Quantum Clustering
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RECOMB
2009
Springer
16 years 7 months ago
Finding Biologically Accurate Clusterings in Hierarchical Tree Decompositions Using the Variation of Information
Abstract. Hierarchical clustering is a popular method for grouping together similar elements based on a distance measure between them. In many cases, annotation information for som...
Saket Navlakha, James Robert White, Niranjan Nagar...
KDD
2001
ACM
166views Data Mining» more  KDD 2001»
16 years 6 months ago
Generalized clustering, supervised learning, and data assignment
Clustering algorithms have become increasingly important in handling and analyzing data. Considerable work has been done in devising effective but increasingly specific clustering...
Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoo...
ICDE
2010
IEEE
173views Database» more  ICDE 2010»
16 years 1 months ago
Progressive clustering of networks using Structure-Connected Order of Traversal
— Network clustering enables us to view a complex network at the macro level, by grouping its nodes into units whose characteristics and interrelationships are easier to analyze ...
Dustin Bortner, Jiawei Han
ICPR
2008
IEEE
16 years 27 days ago
Adaptive selection of non-target cluster centers for K-means tracker
Hua et al. have proposed a stable and efficient tracking algorithm called “K-means tracker”[2, 3, 5]. This paper describes an adaptive non-target cluster center selection met...
Hiroshi Oike, Haiyuan Wu, Toshikazu Wada
PR
2006
116views more  PR 2006»
15 years 6 months ago
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
Stefano Rovetta, Francesco Masulli