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ICPR
2002
IEEE
15 years 9 months ago
A Large Scale Clustering Scheme for Kernel K-Means
Kernel functions can be viewed as a non-linear transformation that increases the separability of the input data by mapping them to a new high dimensional space. The incorporation ...
Rong Zhang, Alexander I. Rudnicky
ICASSP
2009
IEEE
15 years 10 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
ISMIS
2005
Springer
15 years 9 months ago
Model-Based Cluster Analysis for Web Users Sessions
One of the main issues inWeb usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of users’sessions and di...
George Pallis, Lefteris Angelis, Athena Vakali
CINQ
2004
Springer
133views Database» more  CINQ 2004»
15 years 7 months ago
Inductive Querying for Discovering Subgroups and Clusters
We introduce the problem of cluster-grouping and show that it integrates several important data mining tasks, i.e. subgroup discovery, mining correlated patterns and aspects from c...
Albrecht Zimmermann, Luc De Raedt
ISNN
2010
Springer
15 years 2 months ago
Pruning Training Samples Using a Supervised Clustering Algorithm
As practical pattern classification tasks are often very-large scale and serious imbalance such as patent classification, using traditional pattern classification techniques in ...
Minzhang Huang, Hai Zhao, Bao-Liang Lu