Thomas Seidl

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Ira AssentProfessor of Computer Science, Aarhus University, Denmark; IAS-8, Forschungszentrum JülichE-mail confirmado em cs.au.dk
Hans-Peter KriegelProfessor für Informatik, Ludwig-Maximilians-University MunichE-mail confirmado em dbs.ifi.lmu.de
Stephan GünnemannProfessor of Computer Science, Technical University of MunichE-mail confirmado em in.tum.de
Emmanuel MüllerProfessor of Computer Science, Technical University of DortmundE-mail confirmado em cs.tu-dortmund.de
Christian BeecksProfessor of Computer Science, University of Hagen || Fraunhofer FITE-mail confirmado em fernuni-hagen.de
Philipp KranenMicrosoft ResearchE-mail confirmado em microsoft.com
Hardy KremerDeloitte Analytics Institute, GermanyE-mail confirmado em deloitte.de
Marwan HassaniAssistant Professor of Computer Science at Eindhoven University of TechnologyE-mail confirmado em tue.nl
Ines FärberData Management and Data ExplorationE-mail confirmado em cs.rwth-aachen.de
Merih Seran UysalDr.-Ing, Process and Data Science Chair, RWTH Aachen UniversityE-mail confirmado em cs.rwth-aachen.de
Albert BifetTélécom ParisTech & University of WaikatoE-mail confirmado em telecom-paristech.fr
Bernhard PfahringerProfessor of Computer Science, University of WaikatoE-mail confirmado em waikato.ac.nz
Geoffrey HolmesUniversity of WaikatoE-mail confirmado em waikato.ac.nz
Peer KrögerChristian-Albrechts-University KielE-mail confirmado em informatik.uni-kiel.de
Daniel KeimProfessor of Computer Science, Data Analysis and Visualization, University of KonstanzE-mail confirmado em uni-konstanz.de
Anna BeerPostdoc, University of ViennaE-mail confirmado em univie.ac.at
Florian RichterLMU MunichE-mail confirmado em dbs.ifi.lmu.de
Daniyal KazempourPostdoc, CAU KielE-mail confirmado em informatik.uni-kiel.de
Gabi KastenmüllerHelmholtz Zentrum München - German Research Center for Environmental HealthE-mail confirmado em helmholtz-muenchen.de
Evgeniy FaermanPhD Student, Ludwig-Maximilians-Universität MünchenE-mail confirmado em dbs.ifi.lmu.de

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Thomas Seidl

Professor of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), MCML, Germany

E-mail confirmado em dbs.ifi.lmu.de - Página inicial

Databases Data Mining Clustering Similarity Search


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering A Bifet, G Holmes, B Pfahringer, P Kranen, H Kremer, T Jansen, T Seidl JMLR Proceedings of Machine Learning Research 11 (WAPA), 44-50, 2010	2290	2010
3D shape histograms for similarity search and classification in spatial databases M Ankerst, G Kastenmüller, HP Kriegel, T Seidl Advances in Spatial Databases: 6th International Symposium, SSD’99 Hong Kong …, 1999	885	1999
Optimal multi-step k-nearest neighbor search T Seidl, HP Kriegel Proceedings of the 1998 ACM SIGMOD international conference on Management of …, 1998	729	1998
Evaluating clustering in subspace projections of high dimensional data E Müller, S Günnemann, I Assent, T Seidl Proceedings of the VLDB Endowment 2 (1), 1270-1281, 2009	366	2009
The clustree: indexing micro-clusters for anytime stream mining P Kranen, I Assent, C Baldauf, T Seidl Knowledge and information systems 29, 249-272, 2011	350	2011
Efficient user-adaptable similarity search in large multimedia databases T Seidl, HP Kriegel VLDB 97, 506-515, 1997	266	1997
Fast nearest neighbor search in high-dimensional space S Berchtold, B Ertl, DA Keim, HP Kriegel, T Seidl Proceedings 14th International Conference on Data Engineering, 209-218, 1998	242	1998
Nearest neighbor classification in 3D protein databases. M Ankerst, G Kastenmüller, HP Kriegel, T Seidl ISMB 99, 34-43, 1999	212	1999
Managing intervals efficiently in object-relational databases HP Kriegel, M Pötke, T Seidl VLDB 20 (0), 0, 2000	183	2000
Statistical selection of relevant subspace projections for outlier ranking E Müller, M Schiffer, T Seidl 2011 IEEE 27th international conference on data engineering, 434-445, 2011	177	2011
On using class-labels in evaluation of clusterings I Färber, S Günnemann, HP Kriegel, P Kröger, E Müller, E Schubert, ... MultiClust: 1st international workshop on discovering, summarizing and using …, 2010	173	2010
DUSC: Dimensionality unbiased subspace clustering I Assent, R Krieger, E Müller, T Seidl seventh IEEE international conference on data mining (ICDM 2007), 409-414, 2007	168	2007
Mining coherent subgraphs in multi-layer graphs with edge labels B Boden, S Günnemann, H Hoffmann, T Seidl Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012	162	2012
Subspace search and visualization to make sense of alternative clusterings in high-dimensional data A Tatu, F Maaß, I Färber, E Bertini, T Schreck, T Seidl, D Keim 2012 IEEE Conference on Visual Analytics Science and Technology (VAST), 63-72, 2012	151	2012
Subspace clustering meets dense subgraph mining: A synthesis of two paradigms S Günnemann, I Färber, B Boden, T Seidl 2010 IEEE international conference on data mining, 845-850, 2010	149	2010
Clicks: An effective algorithm for mining subspace clusters in categorical datasets MJ Zaki, M Peters, I Assent, T Seidl Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005	142	2005
An effective evaluation measure for clustering on evolving data streams H Kremer, P Kranen, T Jansen, T Seidl, A Bifet, G Holmes, B Pfahringer Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011	139	2011
Signature quadratic form distance C Beecks, MS Uysal, T Seidl Proceedings of the ACM International Conference on Image and Video Retrieval …, 2010	137	2010
Anyout: Anytime outlier detection on streaming data I Assent, P Kranen, C Baldauf, T Seidl Database Systems for Advanced Applications: 17th International Conference …, 2012	134	2012
INSCY: Indexing subspace clusters with in-process-removal of redundancy I Assent, R Krieger, E Müller, T Seidl 2008 Eighth IEEE International Conference on Data Mining, 719-724, 2008	132	2008

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