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Hardy Kremer
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2010 – 2019
- 2014
- [i1]Stephan Günnemann, Hardy Kremer, Matthias Hannen, Thomas Seidl:
KDD-SC: Subspace Clustering Extensions for Knowledge Discovery Frameworks. CoRR abs/1407.3850 (2014) - 2013
- [b1]Hardy Kremer:
Mining and similarity search in temporal databases. RWTH Aachen University, 2013, ISBN 978-3-86359-157-1 - [c20]Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl
:
An Evaluation Framework for Temporal Subspace Clustering Approaches. ICDM Workshops 2013: 1089-1092 - [c19]Hardy Kremer, Stephan Günnemann, Simon Wollwage, Thomas Seidl
Nesting the earth mover's distance for effective cluster tracing. SSDBM 2013: 34:1-34:4 - 2012
- [j3]Stephan Günnemann, Hardy Kremer, Charlotte Laufkötter
Tracing Evolving Subspace Clusters in Temporal Climate Data. Data Min. Knowl. Discov. 24(2): 387-410 (2012) - [c18]Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl
Stream Data Mining Using the MOA Framework. DASFAA (2) 2012: 309-313 - [c17]Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl
Effective and Robust Mining of Temporal Subspace Clusters. ICDM 2012: 369-378 - [c16]Stephan Günnemann, Hardy Kremer, Richard Musiol, Roman Haag, Thomas Seidl
A Subspace Clustering Extension for the KNIME Data Mining Framework. ICDM Workshops 2012: 886-889 - [c15]Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl
Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases. PAKDD (1) 2012: 444-455 - 2011
- [c14]Stephan Günnemann, Hardy Kremer, Dominik Lenhard, Thomas Seidl
Subspace clustering for indexing high dimensional data: a main memory index based on local reductions and individual multi-representations. EDBT 2011: 237-248 - [c13]Hardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl
An effective evaluation measure for clustering on evolving data streams. KDD 2011: 868-876 - [c12]Stephan Günnemann, Hardy Kremer, Charlotte Laufkötter
Tracing Evolving Clusters by Subspace and Value Similarity. PAKDD (2) 2011: 444-456 - [c11]Albert Bifet
MOA: A Real-Time Analytics Open Source Framework. ECML/PKDD (3) 2011: 617-620 - [c10]Hardy Kremer, Stephan Günnemann, Anca Maria Ivanescu, Ira Assent
Efficient Processing of Multiple DTW Queries in Time Series Databases. SSDBM 2011: 150-167 - 2010
- [j2]Stephan Günnemann, Ines Färber, Hardy Kremer, Thomas Seidl
CoDA: Interactive Cluster Based Concept Discovery. Proc. VLDB Endow. 3(2): 1633-1636 (2010) - [c9]Ira Assent, Hardy Kremer, Thomas Seidl
Speeding Up Complex Video Copy Detection Queries. DASFAA (1) 2010: 307-321 - [c8]Ira Assent, Hardy Kremer, Stephan Günnemann, Thomas Seidl
Pattern detector: fast detection of suspicious stream patterns for immediate reaction. EDBT 2010: 709-712 - [c7]Hardy Kremer, Stephan Günnemann, Thomas Seidl
Detecting Climate Change in Multivariate Time Series Data by Novel Clustering and Cluster Tracing Techniques. ICDM Workshops 2010: 96-97 - [c6]Stephan Günnemann, Hardy Kremer, Ines Färber, Thomas Seidl
MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering Solutions. ICDM Workshops 2010: 1387-1390 - [c5]Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl
Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA. ICDM Workshops 2010: 1400-1403 - [c4]Stephan Günnemann, Hardy Kremer, Thomas Seidl
Subspace Clustering for Uncertain Data. SDM 2010: 385-396 - [c3]Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering. WAPA 2010: 44-50
2000 – 2009
- 2009
- [j1]Ira Assent, Marc Wichterich, Ralph Krieger, Hardy Kremer, Thomas Seidl
Anticipatory DTW for Efficient Similarity Search in Time Series Databases. Proc. VLDB Endow. 2(1): 826-837 (2009) - [c2]Ira Assent, Stephan Günnemann, Hardy Kremer, Thomas Seidl:
High-Dimensional Indexing for Multimedia Features. BTW 2009: 187-206 - [c1]Ira Assent, Hardy Kremer:
Robust Adaptable Video Copy Detection. SSTD 2009: 380-385
Coauthor Index
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