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WEBI
2007
Springer
16 years 21 days ago
K-SVMeans: A Hybrid Clustering Algorithm for Multi-Type Interrelated Datasets
Identification of distinct clusters of documents in text collections has traditionally been addressed by making the assumption that the data instances can only be represented by ...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...
MCS
2004
Springer
15 years 12 months ago
A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
Hanan Ayad, Otman A. Basir, Mohamed Kamel
ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
15 years 12 months ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
PAMI
2011
15 years 1 months ago
Parallel Spectral Clustering in Distributed Systems
Spectral clustering algorithms have been shown to be more effective in finding clusters than some traditional algorithms such as k-means. However, spectral clustering suffers fro...
Wen-Yen Chen, Yangqiu Song, Hongjie Bai, Chih-Jen ...
KDD
2012
ACM
281views Data Mining» more  KDD 2012»
13 years 9 months ago
Active spectral clustering via iterative uncertainty reduction
Spectral clustering is a widely used method for organizing data that only relies on pairwise similarity measurements. This makes its application to non-vectorial data straightforw...
Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jord...