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Thomas Seidl
Author information
- RWTH Aachen
Other persons with the same name
- Thomas Seidl 0002 — Fraunhofer Institute for Factory Operation and Automation (IFF)
2010 – today
- 2013
[j28]Thomas Seidl: Datenmanagement und -exploration an der RWTH Aachen. Datenbank-Spektrum 13(1): 55-58 (2013)- [j27]Markus Harmsen, Benedikt Fischer, Hauke Schramm, Thomas Seidl, Thomas Martin Deserno: Support Vector Machine Classification Based on Correlation Prototypes Applied to Bone Age Assessment. IEEE J. Biomedical and Health Informatics 17(1): 190-197 (2013)
- [c150]Thomas Seidl, Sergej Fries, Brigitte Boden: MR-DSJ: Distance-Based Self-Join for Large-Scale Vector Data Analysis with MapReduce. BTW 2013: 37-56
- [c149]Christian Beecks, Merih Seran Uysal, Philip Driessen, Thomas Seidl: Content-based exploration of multimedia databases. CBMI 2013: 59-64
- [c148]Marwan Hassani, Yunsu Kim, Thomas Seidl: Subspace MOA: Subspace Stream Clustering Evaluation Using the MOA Framework. DASFAA (2) 2013: 446-449
- [c147]Ayman Tarakji, Marwan Hassani, Stefan Lankes, Thomas Seidl: Using a Multitasking GPU Environment for Content-Based Similarity Measures of Big Data. ICCSA (5) 2013: 181-196
- [c146]Christian Beecks, Steffen Kirchhoff, Thomas Seidl: Signature matching distance for content-based image retrieval. ICMR 2013: 41-48
- [c145]Stephan Günnemann, Brigitte Boden, Ines Färber, Thomas Seidl: Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors. PAKDD (1) 2013: 261-275
- [c144]Marwan Hassani, Yunsu Kim, Seungjin Choi, Thomas Seidl: Effective Evaluation Measures for Subspace Clustering of Data Streams. PAKDD Workshops 2013: 342-353
- [c143]Brigitte Boden, Stephan Günnemann, Holger Hoffmann, Thomas Seidl: RMiCS: a robust approach for mining coherent subgraphs in edge-labeled multi-layer graphs. SSDBM 2013: 23
- [c142]Hardy Kremer, Stephan Günnemann, Simon Wollwage, Thomas Seidl: Nesting the earth mover's distance for effective cluster tracing. SSDBM 2013: 34
- 2012
- [j26]Stephan Günnemann, Hardy Kremer, Charlotte Laufkötter, Thomas Seidl: Tracing Evolving Subspace Clusters in Temporal Climate Data. Data Min. Knowl. Discov. 24(2): 387-410 (2012)
- [j25]Stephan Günnemann, Brigitte Boden, Thomas Seidl: Finding density-based subspace clusters in graphs with feature vectors. Data Min. Knowl. Discov. 25(2): 243-269 (2012)
- [j24]Philipp Kranen, Ira Assent, Thomas Seidl: An Index-Inspired Algorithm for Anytime Classification on Evolving Data Streams. Datenbank-Spektrum 12(1): 43-50 (2012)
- [j23]Anca Maria Ivanescu, Marc Wichterich, Christian Beecks, Thomas Seidl: The ClasSi coefficient for the evaluation of ranking quality in the presence of class similarities. Frontiers of Computer Science 6(5): 568-580 (2012)
- [c141]Brigitte Boden, Stephan Günnemann, Thomas Seidl: Tracing clusters in evolving graphs with node attributes. CIKM 2012: 2331-2334
- [c140]Philipp Kranen, Stephan Wels, Tim Rohlfs, Sebastian Raubach, Thomas Seidl: A tool for automated evaluation of algorithms. CIKM 2012: 2692-2694
- [c139]Ira Assent, Philipp Kranen, Corinna Baldauf, Thomas Seidl: AnyOut: Anytime Outlier Detection on Streaming Data. DASFAA (1) 2012: 228-242
- [c138]Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read: Stream Data Mining Using the MOA Framework. DASFAA (2) 2012: 309-313
- [c137]Anca Maria Ivanescu, Philipp Kranen, Manfred Smieschek, Philip Driessen, Thomas Seidl: PA-Miner: Process Analysis Using Retrieval, Modeling, and Prediction. DASFAA (2) 2012: 319-322
- [c136]Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl: Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. ICDE 2012: 1207-1210
- [c135]Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl: Effective and Robust Mining of Temporal Subspace Clusters. ICDM 2012: 369-378
- [c134]Anca Maria Ivanescu, Thivaharan Albin, Dirk Abel, Thomas Seidl: Employing the Principal Hessian Direction for Building Hinging Hyperplane Models. ICDM Workshops 2012: 481-485
- [c133]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
- [c132]Andrada Tatu, Fabian Maass, Ines Färber, Enrico Bertini, Tobias Schreck, Thomas Seidl, Daniel A. Keim: Subspace search and visualization to make sense of alternative clusterings in high-dimensional data. IEEE VAST 2012: 63-72
- [c131]Stephan Günnemann, Ines Färber, Thomas Seidl: Multi-view clustering using mixture models in subspace projections. KDD 2012: 132-140
- [c130]Stephan Günnemann, Ines Färber, Kittipat Virochsiri, Thomas Seidl: Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data. KDD 2012: 352-360
- [c129]Brigitte Boden, Stephan Günnemann, Holger Hoffmann, Thomas Seidl: Mining coherent subgraphs in multi-layer graphs with edge labels. KDD 2012: 1258-1266
- [c128]Christian Beecks, Thomas Seidl: On Stability of Adaptive Similarity Measures for Content-Based Image Retrieval. MMM 2012: 346-357
- [c127]Roland Assam, Marwan Hassani, Thomas Seidl: Differential Private Trajectory Obfuscation. MobiQuitous 2012: 139-151
- [c126]Marwan Hassani, Thomas Seidl: Resource-Aware Distributed Clustering of Drifting Sensor Data Streams. NDT (1) 2012: 592-607
- [c125]Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl: Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases. PAKDD (1) 2012: 444-455
- [c124]Thomas Seidl, Brigitte Boden, Sergej Fries: CC-MR - Finding Connected Components in Huge Graphs with MapReduce. ECML/PKDD (1) 2012: 458-473
- [c123]Stephan Günnemann, Brigitte Boden, Thomas Seidl: Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data Types. SSDBM 2012: 280-297
- [c122]Philipp Kranen, Marwan Hassani, Thomas Seidl: BT* - An Advanced Algorithm for Anytime Classification. SSDBM 2012: 298-315
- [c121]Anca Maria Ivanescu, Philipp Kranen, Thomas Seidl: Hinging Hyperplane Models for Multiple Predicted Variables. SSDBM 2012: 431-448
- [c120]Marwan Hassani, Pascal Spaus, Mohamed Medhat Gaber, Thomas Seidl: Density-Based Projected Clustering of Data Streams. SUM 2012: 311-324
- [i1]Daniel A. Keim, Fabrice Rossi, Thomas Seidl, Michel Verleysen, Stefan Wrobel: Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081). Dagstuhl Reports 2(2): 58-83 (2012)
- 2011
- [j22]Christoph Busch, Ulrike Korte, Sebastian Abt, Christian Böhm, Ines Färber, Sergej Fries, Johannes Merkle, Claudia Nickel, Alexander Nouak, Alexander Opel, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther, Xuebing Zhou: Biometric Template Protection - Ein Bericht über das Projekt BioKeyS. Datenschutz und Datensicherheit 35(3): 183-191 (2011)
- [j21]Nikos Mamoulis, Thomas Seidl: Special section on spatial and temporal databases. GeoInformatica 15(4): 663-664 (2011)
- [j20]Philipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl: The ClusTree: indexing micro-clusters for anytime stream mining. Knowl. Inf. Syst. 29(2): 249-272 (2011)
- [c119]Christian Böhm, Ines Färber, Sergej Fries, Ulrike Korte, Johannes Merkle, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther: Efficient Database Techniques for Identification with Fuzzy Vault Templates. BIOSIG 2011: 115-126
- [c118]Marc Wichterich, Anca Maria Ivanescu, Thomas Seidl: Feature-Based Graph Similarity with Co-Occurrence Histograms and the Earth Mover's Distance. BTW 2011: 135-146
- [c117]Emmanuel Müller, Ira Assent, Stephan Günnemann, Patrick Gerwert, Matthias Hannen, Timm Jansen, Thomas Seidl: A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases. BTW 2011: 347-366
- [c116]Christian Böhm, Ines Färber, Sergej Fries, Ulrike Korte, Johannes Merkle, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther: Filtertechniken für geschützte biometrische Datenbanken. BTW 2011: 379-389
- [c115]Thivaharan Albin, Peter Drews, Frank J. Hesseler, Anca Maria Ivanescu, Thomas Seidl, Dirk Abel: A hybrid control approach for low temperature combustion engine control. CDC-ECE 2011: 6846-6851
- [c114]Emmanuel Müller, Ira Assent, Stephan Günnemann, Thomas Seidl: Scalable density-based subspace clustering. CIKM 2011: 1077-1086
- [c113]Stephan Günnemann, Ines Färber, Emmanuel Müller, Ira Assent, Thomas Seidl: External evaluation measures for subspace clustering. CIKM 2011: 1363-1372
- [c112]Martin Krulis, Jakub Lokoc, Christian Beecks, Tomás Skopal, Thomas Seidl: Processing the signature quadratic form distance on many-core GPU architectures. CIKM 2011: 2373-2376
- [c111]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
- [c110]Roland Assam, Thomas Seidl: Preserving privacy of moving objects via temporal clustering of spatio-temporal data streams. SPRINGL 2011: 9-16
- [c109]Christian Beecks, Anca Maria Ivanescu, Steffen Kirchhoff, Thomas Seidl: Modeling image similarity by Gaussian mixture models and the Signature Quadratic Form Distance. ICCV 2011: 1754-1761
- [c108]Emmanuel Müller, Matthias Schiffer, Thomas Seidl: Statistical selection of relevant subspace projections for outlier ranking. ICDE 2011: 434-445
- [c107]Stephan Günnemann, Emmanuel Müller, Sebastian Raubach, Thomas Seidl: Flexible Fault Tolerant Subspace Clustering for Data with Missing Values. ICDM 2011: 231-240
- [c106]Christian Beecks, Thomas Seidl: Analyzing the inner workings of the Signature Quadratic Form Distance. ICME 2011: 1-6
- [c105]Hardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer: An effective evaluation measure for clustering on evolving data streams. KDD 2011: 868-876
- [c104]Marwan Hassani, Thomas Seidl: Towards a Mobile Health Context Prediction: Sequential Pattern Mining in Multiple Streams. Mobile Data Management (2) 2011: 55-57
- [c103]Christian Beecks, Jakub Lokoc, Thomas Seidl, Tomás Skopal: Indexing the signature quadratic form distance for efficient content-based multimedia retrieval. ICMR 2011: 24
- [c102]Christian Beecks, Anca Maria Ivanescu, Steffen Kirchhoff, Thomas Seidl: Modeling multimedia contents through probabilistic feature signatures. ACM Multimedia 2011: 1433-1436
- [c101]Christian Beecks, Ira Assent, Thomas Seidl: Content-Based Multimedia Retrieval in the Presence of Unknown User Preferences. MMM (1) 2011: 140-150
- [c100]Christian Beecks, Merih Seran Uysal, Thomas Seidl: L2-Signature Quadratic Form Distance for Efficient Query Processing in Very Large Multimedia Databases. MMM (1) 2011: 381-391
- [c99]Anca Maria Ivanescu, Marc Wichterich, Thomas Seidl: ClasSi: Measuring Ranking Quality in the Presence of Object Classes with Similarity Information. PAKDD Workshops 2011: 185-196
- [c98]Stephan Günnemann, Hardy Kremer, Charlotte Laufkötter, Thomas Seidl: Tracing Evolving Clusters by Subspace and Value Similarity. PAKDD (2) 2011: 444-456
- [c97]Stephan Günnemann, Brigitte Boden, Thomas Seidl: DB-CSC: A Density-Based Approach for Subspace Clustering in Graphs with Feature Vectors. ECML/PKDD (1) 2011: 565-580
- [c96]Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl: MOA: A Real-Time Analytics Open Source Framework. ECML/PKDD (3) 2011: 617-620
- [c95]Christian Beecks, Anca Maria Ivanescu, Thomas Seidl, Diana Martin, Philipp Pischke, Reinhold Kneer: Applying similarity search for the investigation of the fuel injection process. SISAP 2011: 117-118
- [c94]Jakub Lokoc, Christian Beecks, Thomas Seidl, Tomás Skopal: Parameterized earth mover's distance for efficient metric space indexing. SISAP 2011: 121-122
- [c93]Hardy Kremer, Stephan Günnemann, Anca Maria Ivanescu, Ira Assent, Thomas Seidl: Efficient Processing of Multiple DTW Queries in Time Series Databases. SSDBM 2011: 150-167
- [c92]Philipp Kranen, Felix Reidl, Fernando Sanchez Villaamil, Thomas Seidl: Hierarchical Clustering for Real-Time Stream Data with Noise. SSDBM 2011: 405-413
- [p3]
- [e4]Emmanuel Müller, Stephan Günnemann, Ira Assent, Thomas Seidl (Eds.): Proceedings of the 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings, Athens, Greece, September 5, 2011, in conjunction with ECML/PKDD 2011. CEUR Workshop Proceedings 772, CEUR-WS.org 2011
- 2010
- [j19]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. Journal of Machine Learning Research - Proceedings Track 11: 44-50 (2010)
- [j18]Stephan Günnemann, Ines Färber, Hardy Kremer, Thomas Seidl: CoDA: Interactive Cluster Based Concept Discovery. PVLDB 3(2): 1633-1636 (2010)
- [c91]Emmanuel Müller, Matthias Schiffer, Thomas Seidl: Adaptive outlierness for subspace outlier ranking. CIKM 2010: 1629-1632
- [c90]Christian Beecks, Merih Seran Uysal, Thomas Seidl: Signature Quadratic Form Distance. CIVR 2010: 438-445
- [c89]Ira Assent, Hardy Kremer, Thomas Seidl: Speeding Up Complex Video Copy Detection Queries. DASFAA (1) 2010: 307-321
- [c88]Emmanuel Müller, Philipp Kranen, Michael Nett, Felix Reidl, Thomas Seidl: Air-Indexing on Error Prone Communication Channels. DASFAA (1) 2010: 505-519
- [c87]Ira Assent, Hardy Kremer, Stephan Günnemann, Thomas Seidl: Pattern detector: fast detection of suspicious stream patterns for immediate reaction. EDBT 2010: 709-712
- [c86]Christian Beecks, Merih Seran Uysal, Thomas Seidl: Efficient k-nearest neighbor queries with the Signature Quadratic Form Distance. ICDE Workshops 2010: 10-15
- [c85]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
- [c84]Stephan Günnemann, Ines Färber, Brigitte Boden, Thomas Seidl: Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms. ICDM 2010: 845-850
- [c83]Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl: Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. ICDM 2010: 1220
- [c82]Stephan Günnemann, Hardy Kremer, Ines Färber, Thomas Seidl: MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering Solutions. ICDM Workshops 2010: 1387-1390
- [c81]Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer: Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA. ICDM Workshops 2010: 1400-1403
- [c80]Christian Beecks, Thilo Stadelmann, Bernd Freisleben, Thomas Seidl: Visual speaker model exploration. ICME 2010: 727-728
- [c79]Christian Beecks, Merih Seran Uysal, Thomas Seidl: A comparative study of similarity measures for content-based multimedia retrieval. ICME 2010: 1552-1557
- [c78]Christian Beecks, Sascha Wiedenfeld, Thomas Seidl: Improving the Efficiency of Content-Based Multimedia Exploration. ICPR 2010: 3163-3166
- [c77]Christian Beecks, Philip Driessen, Thomas Seidl: Index support for content-based multimedia exploration. ACM Multimedia 2010: 999-1002
- [c76]Stephan Günnemann, Thomas Seidl: Subgraph Mining on Directed and Weighted Graphs. PAKDD (2) 2010: 133-146
- [c75]Philipp Kranen, Ralph Krieger, Stefan Denker, Thomas Seidl: Bulk Loading Hierarchical Mixture Models for Efficient Stream Classification. PAKDD (2) 2010: 325-334
- [c74]Emmanuel Müller, Matthias Schiffer, Patrick Gerwert, Matthias Hannen, Timm Jansen, Thomas Seidl: SOREX: Subspace Outlier Ranking Exploration Toolkit. ECML/PKDD (3) 2010: 607-610
- [c73]Stephan Günnemann, Hardy Kremer, Thomas Seidl: Subspace Clustering for Uncertain Data. SDM 2010: 385-396
- [c72]Christian Beecks, Merih Seran Uysal, Thomas Seidl: Similarity matrix compression for efficient signature quadratic form distance computation. SISAP 2010: 109-114
- [c71]Philipp Kranen, Stephan Günnemann, Sergej Fries, Thomas Seidl: MC-Tree: Improving Bayesian Anytime Classification. SSDBM 2010: 252-269
2000 – 2009
- 2009
- [j17]Philipp Kranen, Thomas Seidl: Harnessing the strengths of anytime algorithms for constant data streams. Data Min. Knowl. Discov. 19(2): 245-260 (2009)
- [j16]Matthias Schiffer, Emmanuel Müller, Thomas Seidl: SubRank: Ranking Local Outliers in Projections of High-Dimensional Spaces. Datenbank-Spektrum 29: 53-55 (2009)
- [j15]Ira Assent, Marc Wichterich, Ralph Krieger, Hardy Kremer, Thomas Seidl: Anticipatory DTW for Efficient Similarity Search in Time Series Databases. PVLDB 2(1): 826-837 (2009)
- [j14]Emmanuel Müller, Stephan Günnemann, Ira Assent, Thomas Seidl: Evaluating Clustering in Subspace Projections of High Dimensional Data. PVLDB 2(1): 1270-1281 (2009)
- [c70]Marc Wichterich, Christian Beecks, Martin Sundermeyer, Thomas Seidl: Relevance Feedback for the Earth Mover's Distance. Adaptive Multimedia Retrieval 2009: 72-86
- [c69]Ira Assent, Stephan Günnemann, Hardy Kremer, Thomas Seidl: High-Dimensional Indexing for Multimedia Features. BTW 2009: 187-206
- [c68]Christian Beecks, Marc Wichterich, Thomas Seidl: Metrische Anpassung der Earth Mover's Distanz zur Ähnlichkeitssuche in Multimedia-Datenbanken. BTW 2009: 207-216
- [c67]Stephan Günnemann, Emmanuel Müller, Ines Färber, Thomas Seidl: Detection of orthogonal concepts in subspaces of high dimensional data. CIKM 2009: 1317-1326
- [c66]Marc Wichterich, Christian Beecks, Martin Sundermeyer, Thomas Seidl: Exploring multimedia databases via optimization-based relevance feedback and the earth mover's distance. CIKM 2009: 1621-1624
- [c65]Babak Ahmadi, Marios Hadjieleftheriou, Thomas Seidl, Divesh Srivastava, Suresh Venkatasubramanian: Type-based categorization of relational attributes. EDBT 2009: 84-95
- [c64]Thomas Seidl, Ira Assent, Philipp Kranen, Ralph Krieger, Jennifer Herrmann: Indexing density models for incremental learning and anytime classification on data streams. EDBT 2009: 311-322
- [c63]Philipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl: Self-Adaptive Anytime Stream Clustering. ICDM 2009: 249-258
- [c62]Emmanuel Müller, Ira Assent, Stephan Günnemann, Ralph Krieger, Thomas Seidl: Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data. ICDM 2009: 377-386
- [c61]Marwan Hassani, Emmanuel Müller, Thomas Seidl: EDISKCO: energy efficient distributed in-sensor-network k-center clustering with outliers. KDD Workshop on Knowledge Discovery from Sensor Data 2009: 39-48
- [c60]Christian Beecks, Merih Seran Uysal, Thomas Seidl: Signature quadratic form distances for content-based similarity. ACM Multimedia 2009: 697-700
- [c59]Philipp Kranen, Thomas Seidl: Harnessing the Strengths of Anytime Algorithms for Constant Data Streams. ECML/PKDD (1) 2009: 31
- [c58]Emmanuel Müller, Ira Assent, Ralph Krieger, Stephan Günnemann, Thomas Seidl: DensEst: Density Estimation for Data Mining in High Dimensional Spaces. SDM 2009: 173-184
- [c57]Emmanuel Müller, Ira Assent, Thomas Seidl: HSM: Heterogeneous Subspace Mining in High Dimensional Data. SSDBM 2009: 497-516
- [c56]Philipp Kranen, Thomas Seidl: Using Index Structures for Anytime Stream Mining. VLDB PhD Workshop 2009
- [e3]Nikos Mamoulis, Thomas Seidl, Torben Bach Pedersen, Kristian Torp, Ira Assent (Eds.): Advances in Spatial and Temporal Databases, 11th International Symposium, SSTD 2009, Aalborg, Denmark, July 8-10, 2009, Proceedings. Lecture Notes in Computer Science 5644, Springer 2009, ISBN 978-3-642-02981-3
- [r1]
- 2008
- [j13]David Ruau, Corinna Kolárik, Heinz-Theodor Mevissen, Emmanuel Müller, Ira Assent, Ralph Krieger, Thomas Seidl, Martin Hofmann-Apitius, Martin Zenke: Public microarray repository semantic annotation with ontologies employing text mining and expression profile correlation. BMC Bioinformatics 9(S-10) (2008)
- [j12]Thomas Martin Deserno, Mark Oliver Güld, Bartosz Plodowski, Klaus Spitzer, Berthold B. Wein, Henning Schubert, Hermann Ney, Thomas Seidl: Extended Query Refinement for Medical Image Retrieval. J. Digital Imaging 21(3): 280-289 (2008)
- [j11]Ira Assent, Ralph Krieger, Boris Glavic, Thomas Seidl: Clustering multidimensional sequences in spatial and temporal databases. Knowl. Inf. Syst. 16(1): 29-51 (2008)
- [c55]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl: EDSC: efficient density-based subspace clustering. CIKM 2008: 1093-1102
- [c54]Ira Assent, Ralph Krieger, Farzad Afschari, Thomas Seidl: The TS-tree: efficient time series search and retrieval. EDBT 2008: 252-263
- [c53]Ira Assent, Marc Wichterich, Tobias Meisen, Thomas Seidl: Efficient similarity search using the Earth Mover's Distance for large multimedia databases. ICDE 2008: 307-316
- [c52]Marc Wichterich, Christian Beecks, Thomas Seidl: Ranking multimedia databases via relevance feedback with history and foresight support. ICDE Workshops 2008: 596-599
- [c51]Emmanuel Müller, Ira Assent, Uwe Steinhausen, Thomas Seidl: OutRank: ranking outliers in high dimensional data. ICDE Workshops 2008: 600-603
- [c50]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl: INSCY: Indexing Subspace Clusters with In-Process-Removal of Redundancy. ICDM 2008: 719-724
- [c49]Emmanuel Müller, Ira Assent, Ralph Krieger, Timm Jansen, Thomas Seidl: Morpheus: interactive exploration of subspace clustering. KDD 2008: 1089-1092
- [c48]Philipp Kranen, David Kensche, Saim Kim, Nadine Zimmermann, Emmanuel Müller, Christoph Quix, Xiang Li, Thomas Gries, Thomas Seidl, Matthias Jarke, Steffen Leonhardt: Mobile Mining and Information Management in HealthNet Scenarios. MDM 2008: 215-216
- [c47]Ira Assent, Ralph Krieger, Petra Welter, Jörg Herbers, Thomas Seidl: SubClass: Classification of Multidimensional Noisy Data Using Subspace Clusters. PAKDD 2008: 40-52
- [c46]Ira Assent, Emmanuel Müller, Ralph Krieger, Timm Jansen, Thomas Seidl: Pleiades: Subspace Clustering and Evaluation. ECML/PKDD (2) 2008: 666-671
- [c45]Marc Wichterich, Ira Assent, Philipp Kranen, Thomas Seidl: Efficient EMD-based similarity search in multimedia databases via flexible dimensionality reduction. SIGMOD Conference 2008: 199-212
- [c44]Christoph Brochhaus, Thomas Seidl: IndeGSRI: Efficient View-Dependent Ranking in CFD Post- processing Queries with RDBMS. SSDBM 2008: 598-604
- [p2]
- 2007
- [j10]Mohammed J. Zaki, Markus Peters, Ira Assent, Thomas Seidl: Clicks: An effective algorithm for mining subspace clusters in categorical datasets. Data Knowl. Eng. 60(1): 51-70 (2007)
- [j9]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl: VISA: visual subspace clustering analysis. SIGKDD Explorations 9(2): 5-12 (2007)
- [c43]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl: Subspace outlier mining in large multimedia databases. Parallel Universes and Local Patterns 2007
- [c42]Ira Assent, Ralph Krieger, Thomas Seidl: AttentionAttractor: efficient video stream similarity query processing in real time. ICDE 2007: 1509-1510
- [c41]Ira Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl: DUSC: Dimensionality Unbiased Subspace Clustering. ICDM 2007: 409-414
- [c40]Christoph Brochhaus, Thomas Seidl: Efficient Index Support for View-Dependent Queries on CFD Data. SSTD 2007: 57-74
- [c39]Christoph Brochhaus, Thomas Seidl: IndeGS: Index Supported Graphics Data Server for CFD Data Postprocessing. VLDB 2007: 1354-1357
- [e2]Alfons Kemper, Harald Schöning, Thomas Rose, Matthias Jarke, Thomas Seidl, Christoph Quix, Christoph Brochhaus (Eds.): Datenbanksysteme in Business, Technologie und Web (BTW 2007), 12. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), Proceedings, 7.-9. März 2007, Aachen, Germany. LNI 103, GI 2007, ISBN 978-3-88579-197-3
- [e1]Matthias Jarke, Thomas Seidl, Christoph Quix, David Kensche, Stefan Conrad, Erhard Rahm, Ralf Klamma, Harald Kosch, Michael Granitzer, Sven Apel, Marko Rosenmüller, Gunter Saake, Olaf Spinczyk (Eds.): Datenbanksysteme in Business, Technologie und Web (BTW 2007), Workshop Proceedings, 5.-6. März 2007, Aachen, Germany. Verlagshaus Mainz, Aachen 2007, ISBN 3-86130-929-7
- 2006
- [j8]Ira Assent, Marc Wichterich, Thomas Seidl: Adaptable Distance Functions for Similarity-based Multimedia Retrieval. Datenbank-Spektrum 19: 23-31 (2006)
- [c38]Ira Assent, Thomas Seidl: Efficient multi-step query processing for EMD-based similarity. Content-Based Retrieval 2006
- [c37]Christoph Brochhaus, Marc Wichterich, Thomas Seidl: Approximation Techniques to Enable Dimensionality Reduction for Voronoi-Based Nearest Neighbor Search. EDBT 2006: 204-221
- [c36]Ira Assent, Andrea Wenning, Thomas Seidl: Approximation Techniques for Indexing the Earth Mover's Distance in Multimedia Databases. ICDE 2006: 11
- [c35]Ira Assent, Ralph Krieger, Boris Glavic, Thomas Seidl: Spatial Multidimensional Sequence Clustering. ICDM Workshops 2006: 343-348
- 2005
- [j7]Christoph Brochhaus, Jost Enderle, Achim Schlosser, Thomas Seidl, Knut Stolze: Efficient interval management using object-relational database servers. Inform., Forsch. Entwickl. 20(3): 121-137 (2005)
- [c34]Christoph Brochhaus, Jost Enderle, Achim Schlosser, Thomas Seidl, Knut Stolze: Integrating the Relational Interval Tree into IBM's DB2 Universal Database Server. BTW 2005: 67-86
- [c33]Mohammed Javeed Zaki, Markus Peters, Ira Assent, Thomas Seidl: CLICKS: an effective algorithm for mining subspace clusters in categorical datasets. KDD 2005: 736-742
- [c32]Jost Enderle, Nicole Schneider, Thomas Seidl: Efficiently Processing Queries on Interval-and-Value Tuples in Relational Databases. VLDB 2005: 385-396
- [p1]Hans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Thomas Seidl, Jost Enderle: Object-Relational Spatial Indexing. Spatial Databases 2005: 49-80
- 2004
- [c31]
- [c30]M. Tamer Özsu, Jean Carrive, Sébastien Gilles, Izabela Grasland, Roger Mohr, Thomas Seidl: CVDB 2004 Panel: Future Applications and Solutions. CVDB 2004: 67-68
- [c29]Hans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Thomas Seidl: A Cost Model for Spatial Intersection Queries on RI-Trees. DASFAA 2004: 331-338
- [c28]Karin Kailing, Hans-Peter Kriegel, Stefan Schönauer, Thomas Seidl: Efficient Similarity Search for Hierarchical Data in Large Databases. EDBT 2004: 676-693
- [c27]Karin Kailing, Hans-Peter Kriegel, Stefan Schönauer, Thomas Seidl: Efficient Similarity Search in Large Databases of Tree Structured Objects. ICDE 2004: 835
- [c26]Jost Enderle, Matthias Hampel, Thomas Seidl: Joining Interval Data in Relational Databases. SIGMOD Conference 2004: 683-694
- 2003
- [c25]Hans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Matthias Renz, Thomas Seidl: Spatial Data Management for Virtual Product Development. Computer Science in Perspective 2003: 216-230
- [c24]Hans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Thomas Seidl: The Paradigm of Relational Indexing: a Survey. BTW 2003: 285-304
- [c23]Hans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Thomas Seidl: Spatial Query Processing for High Resolutions. DASFAA 2003: 17-26
- [c22]Hans-Peter Kriegel, Peer Kröger, Zahi Mashael, Martin Pfeifle, Marco Pötke, Thomas Seidl: Effective Similarity Search on Voxelized CAD Object. DASFAA 2003: 27-36
- 2002
- [j6]Christian Böhm, Hans-Peter Kriegel, Thomas Seidl: Combining Approximation Techniques and Vector Quantization for Adaptable Similarity Search. J. Intell. Inf. Syst. 19(2): 207-230 (2002)
- [c21]Hans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Thomas Seidl: A Cost Model for Interval Intersection Queries on RI-Trees. SSDBM 2002: 131-141
- 2001
- [c20]Christian Böhm, Hans-Peter Kriegel, Thomas Seidl: Adaptable Similarity Search Using Vector Quantization. DaWaK 2001: 317-327
- [c19]Hans-Peter Kriegel, Andreas Müller, Marco Pötke, Thomas Seidl: DIVE: Database Integration for Virtual Engineering. ICDE Demo Sessions 2001: 15-16
- [c18]Hans-Peter Kriegel, Andreas Müller, Marco Pötke, Thomas Seidl: Spatial Data Management for Computer Aided Design. SIGMOD Conference 2001: 614
- [c17]Hans-Peter Kriegel, Marco Pötke, Thomas Seidl: Interval Sequences: An Object-Relational Approach to Manage Spatial Data. SSTD 2001: 481-501
- [c16]Hans-Peter Kriegel, Marco Pötke, Thomas Seidl: Object-Relational Indexing for General Interval Relationships. SSTD 2001: 522-542
- 2000
- [j5]Stefan Berchtold, Daniel A. Keim, Hans-Peter Kriegel, Thomas Seidl: Indexing the Solution Space: A New Technique for Nearest Neighbor Search in High-Dimensional Space. IEEE Trans. Knowl. Data Eng. 12(1): 45-57 (2000)
- [c15]Hans-Peter Kriegel, Marco Pötke, Thomas Seidl: Managing Intervals Efficiently in Object-Relational Databases. VLDB 2000: 407-418
1990 – 1999
- 1999
- [j4]Rolf Backofen, François Bry, Peter Clote, Hans-Peter Kriegel, Thomas Seidl, Klaus U. Schulz: Bioinformatik - Aktuelles Schlagwort. Informatik Spektrum 22(5): 376-378 (1999)
- [c14]Thomas Seidl, Hans-Peter Kriegel: Adaptable Similarity Search in Large Image Databases. State-of-the-Art in Content-Based Image and Video Retrieval 1999: 297-317
- [c13]Mihael Ankerst, Gabi Kastenmüller, Hans-Peter Kriegel, Thomas Seidl: Nearest Neighbor Classification in 3D Protein Databases. ISMB 1999: 34-43
- [c12]Mihael Ankerst, Gabi Kastenmüller, Hans-Peter Kriegel, Thomas Seidl: 3D Shape Histograms for Similarity Search and Classification in Spatial Databases. SSD 1999: 207-226
- 1998
- [j3]Hans-Peter Kriegel, Thomas Seidl: Approximation-Based Similarity Search for 3-D Surface Segments. GeoInformatica 2(2): 113-147 (1998)
- [j2]Thomas Seidl: Adaptable Similarity Search in 3-D Spatial Database Systems (Abstract). Datenbank Rundbrief 21: 96 (1998)
- [j1]Mihael Ankerst, Hans-Peter Kriegel, Thomas Seidl: A Multistep Approach for Shape Similarity Search in Image Databases. IEEE Trans. Knowl. Data Eng. 10(6): 996-1004 (1998)
- [c11]Thomas Seidl, Gabi Kastenmüller, Hans-Peter Kriegel: Similarity Search in 3D Protein Databases. German Conference on Bioinformatics 1998
- [c10]Stefan Berchtold, Bernhard Ertl, Daniel A. Keim, Hans-Peter Kriegel, Thomas Seidl: Fast Nearest Neighbor Search in High-Dimensional Space. ICDE 1998: 209-218
- [c9]Thomas Seidl, Hans-Peter Kriegel: Optimal Multi-Step k-Nearest Neighbor Search. SIGMOD Conference 1998: 154-165
- [c8]Mihael Ankerst, Bernhard Braunmüller, Hans-Peter Kriegel, Thomas Seidl: Improving Adaptable Similarity Query Processing by Using Approximations. VLDB 1998: 206-217
- 1997
- [c7]Hans-Peter Kriegel, Thomas Schmidt, Thomas Seidl: 3D Similarity Search by Shape Approximation. SSD 1997: 11-28
- [c6]Thomas Seidl, Hans-Peter Kriegel: Efficient User-Adaptable Similarity Search in Large Multimedia Databases. VLDB 1997: 506-515
- 1995
- [c5]Martin Ester, Hans-Peter Kriegel, Thomas Seidl, Xiaowei Xu: Formbasierte Suche nach komplementären 3D-Oberflächen in einer Protein-Datenbank. BTW 1995: 373-382
- [c4]Thomas Seidl, Hans-Peter Kriegel: Solvent Accessible Surface Representation in a Database System for Protein Docking. ISMB 1995: 350-358
- [c3]Thomas Seidl, Hans-Peter Kriegel: A 3D Molecular Surface Representation Supporting Neighborhood Queries. SSD 1995: 240-258
- 1994
- [c2]Daniel A. Keim, Hans-Peter Kriegel, Thomas Seidl: Supporting Data Mining of Large Databases by Visual Feedback Queries. ICDE 1994: 302-313
- 1993
- [c1]Daniel A. Keim, Hans-Peter Kriegel, Thomas Seidl: Visual Feedback in Querying Large Databases. IEEE Visualization 1993: 158-165
Coauthor Index
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last updated on 2013-10-02 11:07 CEST by the dblp team