Thomas Seidl - researchr alias

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2011

::::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]

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]

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

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

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]

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

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

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]

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

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

2010

Pattern detector: fast detection of suspicious stream patterns for immediate reactionIra Assent, Hardy Kremer, Stephan GÃ¼nnemann, Thomas Seidl. edbt 2010: 709-712 [doi]

Speeding Up Complex Video Copy Detection QueriesIra Assent, Hardy Kremer, Thomas Seidl. dasfaa 2010: 307-321 [doi]

Similarity matrix compression for efficient signature quadratic form distance computationChristian Beecks, Merih Seran Uysal, Thomas Seidl. sisap 2010: 109-114 [doi]

Efficient k-nearest neighbor queries with the Signature Quadratic Form DistanceChristian Beecks, Merih Seran Uysal, Thomas Seidl. icde 2010: 10-15 [doi]

Signature Quadratic Form DistanceChristian Beecks, Merih Seran Uysal, Thomas Seidl. civr 2010: 438-445 [doi]

Improving the Efficiency of Content-Based Multimedia ExplorationChristian Beecks, Sascha Wiedenfeld, Thomas Seidl. icpr 2010: 3163-3166 [doi]

A comparative study of similarity measures for content-based multimedia retrievalChristian Beecks, Merih Seran Uysal, Thomas Seidl. icmcs 2010: 1552-1557 [doi]

Index support for content-based multimedia explorationChristian Beecks, Philip Driessen, Thomas Seidl. mm 2010: 999-1002 [doi]

Visual speaker model explorationChristian Beecks, Thilo Stadelmann, Bernd Freisleben, Thomas Seidl. icmcs 2010: 727-728 [doi]

MOA: Massive Online Analysis, a Framework for Stream Classification and ClusteringAlbert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl. jmlr, 11:44-50, 2010. [doi]

Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two ParadigmsStephan Günnemann, Ines Färber, Brigitte Boden, Thomas Seidl. icdm 2010: 845-850 [doi]

MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering SolutionsStephan Günnemann, Hardy Kremer, Ines Färber, Thomas Seidl. icdm 2010: 1387-1390 [doi]

Subspace Clustering for Uncertain DataStephan Günnemann, Hardy Kremer, Thomas Seidl. sdm 2010: 385-396 [doi]

CoDA: Interactive Cluster Based Concept DiscoveryStephan Günnemann, Ines Färber, Hardy Kremer, Thomas Seidl. pvldb, 3(2):1633-1636, 2010. [doi]

Subgraph Mining on Directed and Weighted GraphsStephan Günnemann, Thomas Seidl. pakdd 2010: 133-146 [doi]

Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOAPhilipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer. icdm 2010: 1400-1403 [doi]

MC-Tree: Improving Bayesian Anytime ClassificationPhilipp Kranen, Stephan Günnemann, Sergej Fries, Thomas Seidl. ssdbm 2010: 252-269 [doi]

Bulk Loading Hierarchical Mixture Models for Efficient Stream ClassificationPhilipp Kranen, Ralph Krieger, Stefan Denker, Thomas Seidl. pakdd 2010: 325-334 [doi]

Detecting Climate Change in Multivariate Time Series Data by Novel Clustering and Cluster Tracing TechniquesHardy Kremer, Stephan Günnemann, Thomas Seidl. icdm 2010: 96-97 [doi]

Adaptive outlierness for subspace outlier rankingEmmanuel Müller, Matthias Schiffer, Thomas Seidl. CIKM 2010: 1629-1632 [doi]

Air-Indexing on Error Prone Communication ChannelsEmmanuel Müller, Philipp Kranen, Michael Nett, Felix Reidl, Thomas Seidl. dasfaa 2010: 505-519 [doi]

::::SOREX::::: Subspace Outlier Ranking Exploration ToolkitEmmanuel Müller, Matthias Schiffer, Patrick Gerwert, Matthias Hannen, Timm Jansen, Thomas Seidl. pkdd 2010: 607-610 [doi]

Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the DataEmmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl. icdm 2010: 1220 [doi]

2009

Type-based categorization of relational attributesBabak Ahmadi, Marios Hadjieleftheriou, Thomas Seidl, Divesh Srivastava, Suresh Venkatasubramanian. edbt 2009: 84-95 [doi]

High-Dimensional Indexing for Multimedia FeaturesIra Assent, Stephan Günnemann, Hardy Kremer, Thomas Seidl. btw 2009: 187-206

Anticipatory DTW for Efficient Similarity Search in Time Series DatabasesIra Assent, Marc Wichterich, Ralph Krieger, Hardy Kremer, Thomas Seidl. pvldb, 2(1):826-837, 2009. [doi]

Metrische Anpassung der Earth Mover s Distanz zur Ähnlichkeitssuche in Multimedia-DatenbankenChristian Beecks, Marc Wichterich, Thomas Seidl. btw 2009: 207-216

Signature quadratic form distances for content-based similarityChristian Beecks, Merih Seran Uysal, Thomas Seidl. mm 2009: 697-700 [doi]

Detection of orthogonal concepts in subspaces of high dimensional dataStephan GÃ¼nnemann, Emmanuel MÃ¼ller, Ines FÃ¤rber, Thomas Seidl. CIKM 2009: 1317-1326 [doi]

EDISKCO: energy efficient distributed in-sensor-network k-center clustering with outliersMarwan Hassani, Emmanuel MÃ¼ller, Thomas Seidl. kdd 2009: 39-48 [doi]

Self-Adaptive Anytime Stream ClusteringPhilipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl. icdm 2009: 249-258 [doi]

Using Index Structures for Anytime Stream MiningPhilipp Kranen, Thomas Seidl. VLDB 2009: [doi]

Harnessing the strengths of anytime algorithms for constant data streamsPhilipp Kranen, Thomas Seidl. datamine, 19(2):245-260, 2009. [doi]

Harnessing the Strengths of Anytime Algorithms for Constant Data StreamsPhilipp Kranen, Thomas Seidl. pkdd 2009: 31 [doi]

Advances in Spatial and Temporal Databases, 11th International Symposium, SSTD 2009, Aalborg, Denmark, July 8-10, 2009, ProceedingsNikos Mamoulis, Thomas Seidl, Torben Bach Pedersen, Kristian Torp, Ira Assent, editors, Volume 5644 of Lecture Notes in Computer Science, Springer, 2009. [doi]

Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional DataEmmanuel MÃ¼ller, Ira Assent, Stephan GÃ¼nnemann, Ralph Krieger, Thomas Seidl. icdm 2009: 377-386 [doi]

Evaluating Clustering in Subspace Projections of High Dimensional DataEmmanuel MÃ¼ller, Stephan GÃ¼nnemann, Ira Assent, Thomas Seidl. pvldb, 2(1):1270-1281, 2009. [doi]

HSM: Heterogeneous Subspace Mining in High Dimensional DataEmmanuel Müller, Ira Assent, Thomas Seidl. ssdbm 2009: 497-516 [doi]

DensEst: Density Estimation for Data Mining in High Dimensional SpacesEmmanuel Müller, Ira Assent, Ralph Krieger, Stephan Günnemann, Thomas Seidl. sdm 2009: 173-184 [doi]

SubRank: Ranking Local Outliers in Projections of High-Dimensional SpacesMatthias Schiffer, Emmanuel Müller, Thomas Seidl. dbsk, 29:53-55, 2009.

Indexing density models for incremental learning and anytime classification on data streamsThomas Seidl, Ira Assent, Philipp Kranen, Ralph Krieger, Jennifer Herrmann. edbt 2009: 311-322 [doi]

Relevance Feedback for the Earth Mover s DistanceMarc Wichterich, Christian Beecks, Martin Sundermeyer, Thomas Seidl. amr 2011: 72-86 [doi]

Exploring multimedia databases via optimization-based relevance feedback and the earth mover s distanceMarc Wichterich, Christian Beecks, Martin Sundermeyer, Thomas Seidl. CIKM 2009: 1621-1624 [doi]

2008

Pleiades: Subspace Clustering and EvaluationIra Assent, Emmanuel Müller, Ralph Krieger, Timm Jansen, Thomas Seidl. pkdd 2008: 666-671 [doi]

Clustering multidimensional sequences in spatial and temporal databasesIra Assent, Ralph Krieger, Boris Glavic, Thomas Seidl. kais, 16(1):29-51, 2008. [doi]

Efficient similarity search using the Earth Mover s Distance for large multimedia databasesIra Assent, Marc Wichterich, Tobias Meisen, Thomas Seidl. icde 2008: 307-316 [doi]

The TS-tree: efficient time series search and retrievalIra Assent, Ralph Krieger, Farzad Afschari, Thomas Seidl. edbt 2008: 252-263 [doi]

INSCY: Indexing Subspace Clusters with In-Process-Removal of RedundancyIra Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl. icdm 2008: 719-724 [doi]

SubClass: Classification of Multidimensional Noisy Data Using Subspace ClustersIra Assent, Ralph Krieger, Petra Welter, Jörg Herbers, Thomas Seidl. pakdd 2008: 40-52 [doi]

EDSC: efficient density-based subspace clusteringIra Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl. CIKM 2008: 1093-1102 [doi]

IndeGSRI: Efficient View-Dependent Ranking in CFD Post- processing Queries with RDBMSChristoph Brochhaus, Thomas Seidl. ssdbm 2008: 598-604 [doi]

Extended Query Refinement for Medical Image RetrievalThomas Martin Deserno, Mark Oliver Güld, Bartosz Plodowski, Klaus Spitzer, Berthold B. Wein, Henning Schubert, Hermann Ney, Thomas Seidl. jdi, 21(3):280-289, 2008. [doi]

Mobile Mining and Information Management in HealthNet ScenariosPhilipp Kranen, David Kensche, Saim Kim, Nadine Zimmermann, Emmanuel Müller, Christoph Quix, Xiang Li 0002, Thomas Gries, Thomas Seidl, Matthias Jarke, Steffen Leonhardt. MDM 2008: 215-216 [doi]

Morpheus: interactive exploration of subspace clusteringEmmanuel Müller, Ira Assent, Ralph Krieger, Timm Jansen, Thomas Seidl. kdd 2008: 1089-1092 [doi]

OutRank: ranking outliers in high dimensional dataEmmanuel Müller, Ira Assent, Uwe Steinhausen, Thomas Seidl. icde 2008: 600-603 [doi]

Public microarray repository semantic annotation with ontologies employing text mining and expression profile correlationDavid Ruau, Corinna Kolárik, Heinz-Theodor Mevissen, Emmanuel Müller, Ira Assent, Ralph Krieger, Thomas Seidl, Martin Hofmann-Apitius, Martin Zenke. bmcbi, 9(S-10), 2008. [doi]

Ranking multimedia databases via relevance feedback with history and foresight supportMarc Wichterich, Christian Beecks, Thomas Seidl. icde 2008: 596-599 [doi]

Efficient EMD-based similarity search in multimedia databases via flexible dimensionality reductionMarc Wichterich, Ira Assent, Philipp Kranen, Thomas Seidl. sigmod 2008: 199-212 [doi]

2007

Subspace outlier mining in large multimedia databasesIra Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl. dagstuhl 2007: [doi]

DUSC: Dimensionality Unbiased Subspace ClusteringIra Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl. icdm 2007: 409-414 [doi]

AttentionAttractor: efficient video stream similarity query processing in real timeIra Assent, Ralph Krieger, Thomas Seidl. icde 2007: 1509-1510 [doi]

VISA: visual subspace clustering analysisIra Assent, Ralph Krieger, Emmanuel Müller, Thomas Seidl. sigkdd, 9(2):5-12, 2007. [doi]

Efficient Index Support for View-Dependent Queries on CFD DataChristoph Brochhaus, Thomas Seidl. ssd 2007: 57-74 [doi]

IndeGS: Index Supported Graphics Data Server for CFD Data PostprocessingChristoph Brochhaus, Thomas Seidl. VLDB 2007: 1354-1357 [doi]

Datenbanksysteme in Business, Technologie und Web (BTW 2007), Workshop Proceedings, 5.-6. März 2007, Aachen, GermanyMatthias 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, editors, Verlagshaus Mainz, Aachen, 2007.

Datenbanksysteme in Business, Technologie und Web (BTW 2007), 12. Fachtagung des GI-Fachbereichs Datenbanken und Informationssysteme (DBIS), Proceedings, 7.-9. März 2007, Aachen, GermanyAlfons Kemper, Harald Schöning, Thomas Rose, Matthias Jarke, Thomas Seidl, Christoph Quix, Christoph Brochhaus, editors, Volume 103 of LNI, GI, 2007.

Clicks: An effective algorithm for mining subspace clusters in categorical datasetsMohammed J. Zaki, Markus Peters, Ira Assent, Thomas Seidl. DKE, 60(1):51-70, 2007. [doi]

2006

2005

Efficient interval management using object-relational database serversChristoph Brochhaus, Jost Enderle, Achim Schlosser, Thomas Seidl, Knut Stolze. ife, 20(3):121-137, 2005. [doi]

Integrating the Relational Interval Tree into IBM s DB2 Universal Database ServerChristoph Brochhaus, Jost Enderle, Achim Schlosser, Thomas Seidl, Knut Stolze. btw 2005: 67-86

Efficiently Processing Queries on Interval-and-Value Tuples in Relational DatabasesJost Enderle, Nicole Schneider, Thomas Seidl. VLDB 2005: 385-396 [doi]

Object-Relational Spatial IndexingHans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Thomas Seidl, Jost Enderle. In Yannis Manolopoulos, Apostolos Papadopoulos, Michael Vassilakopoulos, editors, Spatial Databases: Technologies, Techniques and Trends. pages 49-80, Idea Group, 2005.

CLICKS: an effective algorithm for mining subspace clusters in categorical datasetsMohammed Javeed Zaki, Markus Peters, Ira Assent, Thomas Seidl. kdd 2005: 736-742 [doi]

2004

Joining Interval Data in Relational DatabasesJost Enderle, Matthias Hampel, Thomas Seidl. sigmod 2004: 683-694 [doi]

Efficient Similarity Search in Large Databases of Tree Structured ObjectsKarin Kailing, Hans-Peter Kriegel, Stefan Schönauer, Thomas Seidl. icde 2004: 835-836 [doi]

Efficient Similarity Search for Hierarchical Data in Large DatabasesKarin Kailing, Hans-Peter Kriegel, Stefan Schönauer, Thomas Seidl. edbt 2004: 676-693 [doi]

A Cost Model for Spatial Intersection Queries on RI-TreesHans-Peter Kriegel, Martin Pfeifle, Marco Pötke, Thomas Seidl. dasfaa 2004: 331-338 [doi]

Nearest Neighbor Search on Multimedia Indexing StructuresThomas Seidl. cvdb 2004: 2 [doi]

CVDB 2004 Panel: Future Applications and SolutionsM. Tamer Özsu, Jean Carrive, Sébastien Gilles, Izabela Grasland, Roger Mohr, Thomas Seidl. cvdb 2004: 67-68 [doi]

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