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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 5 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
ICML
2009
IEEE
16 years 5 months ago
Bayesian clustering for email campaign detection
We discuss the problem of clustering elements according to the sources that have generated them. For elements that are characterized by independent binary attributes, a closedform...
Peter Haider, Tobias Scheffer
ICASSP
2009
IEEE
15 years 11 months ago
Bandwidth adaptive hardware architecture of K-Means clustering for intelligent video processing
K-Means is a clustering algorithm that is widely applied in many elds, including pattern classi cation and multimedia analysis. Due to real-time requirements and computational-cos...
Tse-Wei Chen, Shao-Yi Chien
CSB
2005
IEEE
136views Bioinformatics» more  CSB 2005»
15 years 10 months ago
Whole Genome Phylogeny Based on Clustered Signature String Composition
Peptide compositions constructed out of whole sets of protein sequences can be used as species signatures for phylogenetic analysis. To account for point mutations, an amino acid ...
Xiaomeng Wu, Guohui Lin, Xiu-Feng Wan, Dong Xu
ICAPR
2001
Springer
15 years 9 months ago
Image Retrieval Using a Hierarchy of Clusters
The goal of this paper is to describe an efficient procedure for color-based image retrieval. The proposed procedure consists of two stages. First, the image data set is hierarchi...
Daniela Stan, Ishwar K. Sethi