Thomas Seidl - researchr alias

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Viewing Publication 1 - 100 from 207

2017

Multimedia Similarity SearchThomas Seidl. btw 2017: 397

2014

Context-based location clustering and prediction using conditional random fieldsRoland Assam, Thomas Seidl. mum 2014: 1-10 [doi]

(k, d)-core anonymity: structural anonymization of massive networksRoland Assam, Marwan Hassani, Michael Brysch, Thomas Seidl. ssdbm 2014: 17 [doi]

On the Stability of Signature-Based Distance Functions for Content-Based Image RetrievalChristian Severin Beecks, Steffen Kirchhoff, Thomas Seidl. lwa 2014: 226 [doi]

On stability of signature-based similarity measures for content-based image retrievalChristian Beecks, Steffen Kirchhoff, Thomas Seidl. mta, 71(1):349-362, 2014. [doi]

Density-Based Subspace Clustering in Heterogeneous NetworksBrigitte Boden, Martin Ester, Thomas Seidl. pkdd 2014: 149-164 [doi]

Projected Clustering for Huge Data Sets in MapReduceSergej Fries, Stephan Wels, Thomas Seidl. edbt 2014: 49-60 [doi]

PHiDJ: Parallel similarity self-join for high-dimensional vector data with MapReduceSergej Fries, Brigitte Boden, Grzegorz Stepien, Thomas Seidl. icde 2014: 796-807 [doi]

The Normalized Freebase DistanceFréderic Godin, Tom De Nies, Christian Beecks, Laurens De Vocht, Wesley De Neve, Erik Mannens, Thomas Seidl, Rik Van de Walle. esws 2014: 218-221 [doi]

SMVC: semi-supervised multi-view clustering in subspace projectionsStephan Günnemann, Ines Färber, Matthias Rüdiger, Thomas Seidl. kdd 2014: 253-262 [doi]

GAMer: a synthesis of subspace clustering and dense subgraph miningStephan Günnemann, Ines Färber, Brigitte Boden, Thomas Seidl. kais, 40(2):243-278, 2014. [doi]

Parallel Implementation of a Density-Based Stream Clustering Algorithm Over a GPU Scheduling SystemMarwan Hassani, Ayman Tarakji, Lyubomir Georgiev, Thomas Seidl. pakdd 2014: 441-453 [doi]

Efficient Streaming Detection of Hidden Clusters in Big Data Using Subspace Stream ClusteringMarwan Hassani, Thomas Seidl. dasfaa 2014: 146-160 [doi]

Adaptive Multiple-Resolution Stream ClusteringMarwan Hassani, Pascal Spaus, Thomas Seidl. mldm 2014: 134-148 [doi]

Subspace anytime stream clusteringMarwan Hassani, Philipp Kranen, Rajveer Saini, Thomas Seidl. ssdbm 2014: 37 [doi]

On Efficient Query Processing with the Earth Mover's DistanceMerih Seran Uysal, Christian Beecks, Thomas Seidl. CIKM 2014: 25-32 [doi]

Efficient Filter Approximation Using the Earth Mover's Distance in Very Large Multimedia Databases with Feature SignaturesMerih Seran Uysal, Christian Beecks, Jochen Schmücking, Thomas Seidl. CIKM 2014: 979-988 [doi]

Inverse predictions on continuous models in scientific databasesAnca Maria Zimmer, Philip Driessen, Philipp Kranen, Thomas Seidl. ssdbm 2014: 26 [doi]

2013

A Model for Context-Aware Location Identity Preservation Using Differential PrivacyRoland Assam, Thomas Seidl. trustcom 2013: 346-353 [doi]

BodyGuards: A Clairvoyant Location Predictor Using Frequent Neighbors and Markov ModelRoland Assam, Thomas Seidl. uic 2013: 25-32 [doi]

Private Map Matching: Realistic Private Route Cognition on Road NetworksRoland Assam, Thomas Seidl. uic 2013: 178-185 [doi]

Content-based exploration of multimedia databasesChristian Beecks, Merih Seran Uysal, Philip Driessen, Thomas Seidl. cbmi 2013: 59-64 [doi]

Signature matching distance for content-based image retrievalChristian Beecks, Steffen Kirchhoff, Thomas Seidl. mir 2013: 41-48 [doi]

Detecting and exploring clusters in attributed graphs: a plugin for the gephi platformBrigitte Boden, Roman Haag, Thomas Seidl. CIKM 2013: 2505-2508 [doi]

RMiCS: a robust approach for mining coherent subgraphs in edge-labeled multi-layer graphsBrigitte Boden, Stephan Günnemann, Holger Hoffmann, Thomas Seidl. ssdbm 2013: 23 [doi]

Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature VectorsStephan Günnemann, Brigitte Boden, Ines Färber, Thomas Seidl. pakdd 2013: 261-275 [doi]

Spectral Subspace Clustering for Graphs with Feature VectorsStephan Günnemann, Ines Färber, Sebastian Raubach, Thomas Seidl. icdm 2013: 231-240 [doi]

Support Vector Machine Classification Based on Correlation Prototypes Applied to Bone Age AssessmentMarkus Harmsen, Benedikt Fischer, Hauke Schramm, Thomas Seidl, Thomas Martin Deserno. titb, 17(1):190-197, 2013. [doi]

Effective Evaluation Measures for Subspace Clustering of Data StreamsMarwan Hassani, Yunsu Kim, Seungjin Choi, Thomas Seidl. pakdd 2013: 342-353 [doi]

Subspace MOA: Subspace Stream Clustering Evaluation Using the MOA FrameworkMarwan Hassani, Yunsu Kim, Thomas Seidl. dasfaa 2013: 446-449 [doi]

An Evaluation Framework for Temporal Subspace Clustering ApproachesHardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl. icdm 2013: 1089-1092 [doi]

Nesting the earth mover's distance for effective cluster tracingHardy Kremer, Stephan Günnemann, Simon Wollwage, Thomas Seidl. ssdbm 2013: 34 [doi]

HealthNet: A System for Mobile and Wearable Health Information ManagementChristoph Quix, Johannes Barnickel, Sandra Geisler, Marwan Hassani, Saim Kim, Xiang Li 0002, Andreas Lorenz, Till Quadflieg, Thomas Gries, Matthias Jarke, Steffen Leonhardt, Ulrike Meyer, Thomas Seidl. immoa 2013: 36-43 [doi]

Datenmanagement und -exploration an der RWTH AachenThomas Seidl. dbsk, 13(1):55-58, 2013. [doi]

MR-DSJ: Distance-Based Self-Join for Large-Scale Vector Data Analysis with MapReduceThomas Seidl, Sergej Fries, Brigitte Boden. btw 2013: 37-56 [doi]

Using a Multitasking GPU Environment for Content-Based Similarity Measures of Big DataAyman Tarakji, Marwan Hassani, Stefan Lankes, Thomas Seidl. iccsa 2013: 181-196 [doi]

Adaptive Model Tree for Streaming DataAnca Maria Zimmer, Michael Kurze, Thomas Seidl. icdm 2013: 1319-1324 [doi]

2012

Differential Private Trajectory ObfuscationRoland Assam, Marwan Hassani, Thomas Seidl. mobiquitous 2013: 139-151 [doi]

AnyOut: Anytime Outlier Detection on Streaming DataIra Assent, Philipp Kranen, Corinna Baldauf, Thomas Seidl. dasfaa 2012: 228-242 [doi]

On Stability of Adaptive Similarity Measures for Content-Based Image RetrievalChristian Beecks, Thomas Seidl. mmm 2012: 346-357 [doi]

Mining coherent subgraphs in multi-layer graphs with edge labelsBrigitte Boden, Stephan Günnemann, Holger Hoffmann, Thomas Seidl. kdd 2012: 1258-1266 [doi]

Tracing clusters in evolving graphs with node attributesBrigitte Boden, Stephan Günnemann, Thomas Seidl. CIKM 2012: 2331-2334 [doi]

Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the dataStephan Günnemann, Ines Färber, Kittipat Virochsiri, Thomas Seidl. kdd 2012: 352-360 [doi]

Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data TypesStephan Günnemann, Brigitte Boden, Thomas Seidl. ssdbm 2012: 280-297 [doi]

Multi-view clustering using mixture models in subspace projectionsStephan Günnemann, Ines Färber, Thomas Seidl. kdd 2012: 132-140 [doi]

A Subspace Clustering Extension for the KNIME Data Mining FrameworkStephan Günnemann, Hardy Kremer, Richard Musiol, Roman Haag, Thomas Seidl. icdm 2012: 886-889 [doi]

Finding density-based subspace clusters in graphs with feature vectorsStephan Günnemann, Brigitte Boden, Thomas Seidl. datamine, 25(2):243-269, 2012. [doi]

Tracing Evolving Subspace Clusters in Temporal Climate DataStephan Günnemann, Hardy Kremer, Charlotte Laufkötter, Thomas Seidl. datamine, 24(2):387-410, 2012. [doi]

Resource-Aware Distributed Clustering of Drifting Sensor Data StreamsMarwan Hassani, Thomas Seidl. mindtrek 2012: 592-607 [doi]

Density-Based Projected Clustering of Data StreamsMarwan Hassani, Pascal Spaus, Mohamed Medhat Gaber, Thomas Seidl. sum 2012: 311-324 [doi]

PA-Miner: Process Analysis Using Retrieval, Modeling, and PredictionAnca Maria Ivanescu, Philipp Kranen, Manfred Smieschek, Philip Driessen, Thomas Seidl. dasfaa 2012: 319-322 [doi]

Hinging Hyperplane Models for Multiple Predicted VariablesAnca Maria Ivanescu, Philipp Kranen, Thomas Seidl. ssdbm 2012: 431-448 [doi]

Employing the Principal Hessian Direction for Building Hinging Hyperplane ModelsAnca Maria Ivanescu, Thivaharan Albin, Dirk Abel, Thomas Seidl. icdm 2012: 481-485 [doi]

The ClasSi coefficient for the evaluation of ranking quality in the presence of class similaritiesAnca Maria Ivanescu, Marc Wichterich, Christian Beecks, Thomas Seidl. fcsc, 6(5):568-580, 2012. [doi]

Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081)Daniel A. Keim, Fabrice Rossi, Thomas Seidl, Michel Verleysen, Stefan Wrobel. dagstuhl-reports, 2(2):58-83, 2012. [doi]

A tool for automated evaluation of algorithmsPhilipp Kranen, Stephan Wels, Tim Rohlfs, Sebastian Raubach, Thomas Seidl. CIKM 2012: 2692-2694 [doi]

Stream Data Mining Using the MOA FrameworkPhilipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read. dasfaa 2012: 309-313 [doi]

BT* - An Advanced Algorithm for Anytime ClassificationPhilipp Kranen, Marwan Hassani, Thomas Seidl. ssdbm 2012: 298-315 [doi]

An Index-Inspired Algorithm for Anytime Classification on Evolving Data StreamsPhilipp Kranen, Ira Assent, Thomas Seidl. dbsk, 12(1):43-50, 2012. [doi]

Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series DatabasesHardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl. pakdd 2012: 444-455 [doi]

Effective and Robust Mining of Temporal Subspace ClustersHardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl. icdm 2012: 369-378 [doi]

Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the DataEmmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl. icde 2012: 1207-1210 [doi]

CC-MR - Finding Connected Components in Huge Graphs with MapReduceThomas Seidl, Brigitte Boden, Sergej Fries. pkdd 2012: 458-473 [doi]

Subspace search and visualization to make sense of alternative clusterings in high-dimensional dataAndrada Tatu, Fabian Maass, Ines Färber, Enrico Bertini, Tobias Schreck, Thomas Seidl, Daniel A. Keim. ieeevast 2012: 63-72 [doi]

2011

A hybrid control approach for low temperature combustion engine controlThivaharan Albin, Peter Drews, Frank J. Hesseler, Anca Maria Ivanescu, Thomas Seidl, Dirk Abel. cdc 2010: 6846-6851 [doi]

Preserving privacy of moving objects via temporal clustering of spatio-temporal data streamsRoland Assam, Thomas Seidl. gis 2011: 9-16 [doi]

Indexing the signature quadratic form distance for efficient content-based multimedia retrievalChristian Beecks, Jakub Lokoc, Thomas Seidl, Tomás Skopal. mir 2011: 24 [doi]

Analyzing the inner workings of the Signature Quadratic Form DistanceChristian Beecks, Thomas Seidl. icmcs 2011: 1-6 [doi]

Applying similarity search for the investigation of the fuel injection processChristian Beecks, Anca Maria Ivanescu, Thomas Seidl, Diana Martin, Philipp Pischke, Reinhold Kneer. sisap 2011: 117-118 [doi]

::::L::::2-Signature Quadratic Form Distance for Efficient Query Processing in Very Large Multimedia DatabasesChristian Beecks, Merih Seran Uysal, Thomas Seidl. mmm 2011: 381-391 [doi]

Modeling multimedia contents through probabilistic feature signaturesChristian Beecks, Anca Maria Ivanescu, Steffen Kirchhoff, Thomas Seidl. mm 2011: 1433-1436 [doi]

Modeling image similarity by Gaussian mixture models and the Signature Quadratic Form DistanceChristian Beecks, Anca Maria Ivanescu, Steffen Kirchhoff, Thomas Seidl. iccv 2011: 1754-1761 [doi]

Content-Based Multimedia Retrieval in the Presence of Unknown User PreferencesChristian Beecks, Ira Assent, Thomas Seidl. mmm 2011: 140-150 [doi]

MOA: A Real-Time Analytics Open Source FrameworkAlbert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl. pkdd 2011: 617-620 [doi]

Biometric Template Protection - Ein Bericht über das Projekt BioKeySChristoph 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. dud, 35(3):183-191, 2011. [doi]

Filtertechniken für geschützte biometrische DatenbankenChristian Böhm, Ines Färber, Sergej Fries, Ulrike Korte, Johannes Merkle, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther. btw 2011: 379-389

Efficient Database Techniques for Identification with Fuzzy Vault TemplatesChristian Böhm, Ines Färber, Sergej Fries, Ulrike Korte, Johannes Merkle, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther. biosig 2011: 115-126 [doi]

DB-CSC: A Density-Based Approach for Subspace Clustering in Graphs with Feature VectorsStephan Günnemann, Brigitte Boden, Thomas Seidl. pkdd 2011: 565-580 [doi]

Tracing Evolving Clusters by Subspace and Value SimilarityStephan Günnemann, Hardy Kremer, Charlotte Laufkötter, Thomas Seidl. pakdd 2011: 444-456 [doi]

Subspace clustering for indexing high dimensional data: a main memory index based on local reductions and individual multi-representationsStephan Günnemann, Hardy Kremer, Dominik Lenhard, Thomas Seidl. edbt 2011: 237-248 [doi]

Flexible Fault Tolerant Subspace Clustering for Data with Missing ValuesStephan Günnemann, Emmanuel Müller, Sebastian Raubach, Thomas Seidl. icdm 2011: 231-240 [doi]

External evaluation measures for subspace clusteringStephan Günnemann, Ines Färber, Emmanuel Müller, Ira Assent, Thomas Seidl. CIKM 2011: 1363-1372 [doi]

Towards a Mobile Health Context Prediction: Sequential Pattern Mining in Multiple StreamsMarwan Hassani, Thomas Seidl. MDM 2011: 55-57 [doi]

ClasSi: Measuring Ranking Quality in the Presence of Object Classes with Similarity InformationAnca Maria Ivanescu, Marc Wichterich, Thomas Seidl. pakdd 2012: 185-196 [doi]

Hierarchical Clustering for Real-Time Stream Data with NoisePhilipp Kranen, Felix Reidl, Fernando Sanchez Villaamil, Thomas Seidl. ssdbm 2011: 405-413 [doi]

The ClusTree: indexing micro-clusters for anytime stream miningPhilipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl. kais, 29(2):249-272, 2011. [doi]

An effective evaluation measure for clustering on evolving data streamsHardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer. kdd 2011: 868-876 [doi]

Efficient Processing of Multiple DTW Queries in Time Series DatabasesHardy Kremer, Stephan Günnemann, Anca Maria Ivanescu, Ira Assent, Thomas Seidl. ssdbm 2011: 150-167 [doi]

Processing the signature quadratic form distance on many-core GPU architecturesMartin Krulis, Jakub Lokoc, Christian Beecks, Tomás Skopal, Thomas Seidl. CIKM 2011: 2373-2376 [doi]

Parameterized earth mover s distance for efficient metric space indexingJakub Lokoc, Christian Beecks, Thomas Seidl, Tomás Skopal. sisap 2011: 121-122 [doi]

Special section on spatial and temporal databasesNikos Mamoulis, Thomas Seidl. geoinformatica, 15(4):663-664, 2011. [doi]

Statistical selection of relevant subspace projections for outlier rankingEmmanuel Müller, Matthias Schiffer, Thomas Seidl. icde 2011: 434-445 [doi]

A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional DatabasesEmmanuel Müller, Ira Assent, Stephan Günnemann, Patrick Gerwert, Matthias Hannen, Timm Jansen, Thomas Seidl. btw 2011: 347-366

Scalable density-based subspace clusteringEmmanuel Müller, Ira Assent, Stephan Günnemann, Thomas Seidl. CIKM 2011: 1077-1086 [doi]

Binary SearchThomas Seidl, Jost Enderle. In Berthold Vöcking, Helmut Alt, Martin Dietzfelbinger, Rüdiger Reischuk, Christian Scheideler, Heribert Vollmer, Dorothea Wagner, editors, Algorithms Unplugged. pages 5-11, Springer, 2011. [doi]

Feature-Based Graph Similarity with Co-Occurrence Histograms and the Earth Mover s DistanceMarc Wichterich, Anca Maria Ivanescu, Thomas Seidl. btw 2011: 135-146

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