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» Techniques of Cluster Algorithms in Data Mining
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EDBT
2004
ACM
142views Database» more  EDBT 2004»
16 years 6 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
IPPS
2000
IEEE
15 years 11 months ago
PaDDMAS: Parallel and Distributed Data Mining Application Suite
Discovering complex associations, anomalies and patterns in distributed data sets is gaining popularity in a range of scientific, medical and business applications. Various algor...
Omer F. Rana, David W. Walker, Maozhen Li, Steven ...
ICML
2006
IEEE
16 years 7 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade
IDEAL
2007
Springer
16 years 19 days ago
A Tool for Web Usage Mining
This paper presents a tool for web usage mining. The aim is centered on providing a tool that facilitates the mining process rather than implement elaborated algorithms and techniq...
José M. Domenech, Javier Lorenzo
ICDM
2005
IEEE
109views Data Mining» more  ICDM 2005»
16 years 3 days ago
Triple Jump Acceleration for the EM Algorithm
This paper presents the triple jump framework for accelerating the EM algorithm and other bound optimization methods. The idea is to extrapolate the third search point based on th...
Han-Shen Huang, Bou-Ho Yang, Chun-Nan Hsu