Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering Hans-Peter Kriegel Peer Kroger - Cluster reduction - Document - PDFSEARCH.IO

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	Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering Hans-Peter Kriegel Peer Kroger Add to Reading List Document Date: 2008-10-23 08:00:13 Open Document File Size: 152,75 KB Share Result on Facebook City Auckland / Munchen / / Company Princeton University Press / ACM Inc. / / Country Germany / / / / IndustryTerm search strategies / data mining applications / projected clustering algorithms / prior specific publisher / prominent solutions / data mining / infinite search space / Prominent algorithms / search space / ad hoc solution / / Organization VLDB Endowment / Base Endowment / Very Large Data Endowment / Universitat / Princeton University / / Person Arthur Zimek / Hans-Peter Kriegel Peer / / / Position tackle / REPRESENTATIVE / / Technology corresponding algorithms / DNA Chip / Example algorithms / clustering algorithm / data mining / Biclustering algorithms / projected clustering algorithms / / URL http / SocialTag Clustering high-dimensional data Biclustering Dimension reduction Data mining Feature selection Consensus clustering Statistics Cluster analysis Correlation clustering

Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering Hans-Peter Kriegel Peer KrogerAdd to Reading List