Stephan Günnemann

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: Post-Doctoral Researcher
: Carnegie Mellon University
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Research Interest

Uncertain Data High Dimensional Data Interactive Exploration Data Mining Network Analysis EDIT INTEREST

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Expertise:: Random graph / Independence number (3); Data mining (2); Wireless Networks / Cellular Systems (1); Face recognition / Image analysis (1); Object Recognition / Two-View Motion Estimation (1); XML Data (1)
Conference:: ICDM (6)ICDM Workshops (3)CIKM (3)KDD (3)SSDBM (3)BTW (2)

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Publications

ALL (31) RECENT 2013 2012 2011 2010 2009

31
Subspace Clustering for Complex Data
Stephan Günnemann
BTW - 2013
PDF BIBTEX
30
Effective and Robust Mining of Temporal Subspace Clusters
Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl
ICDM - 2012
PDF BIBTEX
29
A Subspace Clustering Extension for the KNIME Data Mining Framework
Stephan Günnemann, Hardy Kremer, Richard Musiol, Roman Haag, Thomas Seidl
ICDM Workshops - 2012
PDF BIBTEX
28
Assessing the Significance of Data Mining Results on Graphs with Feature Vectors
Stephan Günnemann, Phuong Dao, Mohsen Jamali, Martin Ester
ICDM - 2012
PDF BIBTEX
27
Tracing clusters in evolving graphs with node attributes
Brigitte Boden, Stephan Günnemann, Thomas Seidl
CIKM - 2012
PDF BIBTEX
26
Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data
Stephan Günnemann, Ines Färber, Kittipat Virochsiri, Thomas Seidl
KDD - 2012
CitedBy 1 PDF BIBTEX
25
Mining coherent subgraphs in multi-layer graphs with edge labels
Brigitte Boden, Stephan Günnemann, Holger Hoffmann, Thomas Seidl
KDD - 2012
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24
Multi-view clustering using mixture models in subspace projections
Stephan Günnemann, Ines Färber, Thomas Seidl
KDD - 2012
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23
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl
ICDE - 2012
CitedBy 8 PDF BIBTEX
22
Finding density-based subspace clusters in graphs with feature vectors
Stephan Günnemann, Brigitte Boden, Thomas Seidl
Data Min. Knowl. Discov. - 2012
CitedBy 1 PDF BIBTEX
21
Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data Types
Stephan Günnemann, Brigitte Boden, Thomas Seidl
SSDBM - 2012
PDF BIBTEX
20
Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases
Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl
PAKDD (1) - 2012
CitedBy 1 PDF BIBTEX
19
Tracing Evolving Subspace Clusters in Temporal Climate Data
Stephan Günnemann, Hardy Kremer, Charlotte Laufkötter, Thomas Seidl
Data Min. Knowl. Discov. - 2012
CitedBy 3 PDF BIBTEX
18
External evaluation measures for subspace clustering
Stephan Günnemann, Ines Färber, Emmanuel Müller, Ira Assent, Thomas Seidl
CIKM - 2011
CitedBy 10 PDF BIBTEX
17
Flexible Fault Tolerant Subspace Clustering for Data with Missing Values
Stephan Günnemann, Emmanuel Müller, Sebastian Raubach, Thomas Seidl
ICDM - 2011
PDF BIBTEX
16
Scalable density-based subspace clustering
Emmanuel Müller, Ira Assent, Stephan Günnemann, Thomas Seidl
CIKM - 2011
CitedBy 2 PDF BIBTEX
15
Efficient Processing of Multiple DTW Queries in Time Series Databases
Hardy Kremer, Stephan Günnemann, Anca Maria Ivanescu, Ira Assent, Thomas Seidl
SSDBM - 2011
CitedBy 1 PDF BIBTEX
14
DB-CSC: A Density-Based Approach for Subspace Clustering in Graphs with Feature Vectors
Stephan Günnemann, Brigitte Boden, Thomas Seidl
ECML/PKDD (1) - 2011
CitedBy 9 PDF BIBTEX
13
Tracing Evolving Clusters by Subspace and Value Similarity
Stephan Günnemann, Hardy Kremer, Charlotte Laufkötter, Thomas Seidl
PAKDD (2) - 2011
CitedBy 2 PDF BIBTEX
12
Subspace clustering for indexing high dimensional data: a main memory index based on local reductions and individual multi-representations
Stephan Günnemann, Hardy Kremer, Dominik Lenhard, Thomas Seidl
EDBT - 2011
CitedBy 4 PDF BIBTEX

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