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» Data Clustering: A Review
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SDM
2007
SIAM
139views Data Mining» more  SDM 2007»
13 years 9 months ago
Dynamic Algorithm for Graph Clustering Using Minimum Cut Tree
We present an efficient dynamic algorithm for clustering undirected graphs, whose edge property is changing continuously. The algorithm maintains clusters of high quality in pres...
Barna Saha, Pabitra Mitra
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
14 years 1 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
SAC
2009
ACM
14 years 2 months ago
Parameterless outlier detection in data streams
Outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). Clustering-based outlier detection is a field that aims to cluster data and to detect...
Alice Marascu, Florent Masseglia
USENIX
2008
13 years 10 months ago
Free Factories: Unified Infrastructure for Data Intensive Web Services
We introduce the Free Factory, a platform for deploying data-intensive web services using small clusters of commodity hardware and free software. Independently administered virtua...
Alexander Wait Zaranek, Tom Clegg, Ward Vandewege,...
BMCBI
2008
121views more  BMCBI 2008»
13 years 8 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...