Ines Färber

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Thomas SeidlProfessor of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), MCML, GermanyDirección de correo verificada de dbs.ifi.lmu.de
Stephan GünnemannProfessor of Computer Science, Technical University of MunichDirección de correo verificada de in.tum.de
Emmanuel MüllerProfessor of Computer Science, Technical University of DortmundDirección de correo verificada de cs.tu-dortmund.de
Erich SchubertProfessor of Data Mining, TU Dortmund UniversityDirección de correo verificada de cs.tu-dortmund.de
Arthur ZimekUniversity of Southern DenmarkDirección de correo verificada de imada.sdu.dk
Peer KrögerChristian-Albrechts-University KielDirección de correo verificada de informatik.uni-kiel.de
Hans-Peter KriegelProfessor für Informatik, Ludwig-Maximilians-University MunichDirección de correo verificada de dbs.ifi.lmu.de
Enrico BertiniNortheastern UniversityDirección de correo verificada de northeastern.edu
Andrada TatuProduct Manager, Porsche AGDirección de correo verificada de porsche.de
Daniel KeimProfessor of Computer Science, Data Analysis and Visualization, University of KonstanzDirección de correo verificada de uni-konstanz.de
Fabian MaaßUniversity of Konstanz, GermanyDirección de correo verificada de uni-konstanz.de
Hardy KremerDeloitte Analytics Institute, GermanyDirección de correo verificada de deloitte.de
Christian BöhmProfessor of Computer Science, University of Vienna, Vienna, AustriaDirección de correo verificada de univie.ac.at
Annahita OswaldLudwig-Maximilians-Universität Munich, GermanyDirección de correo verificada de dbs.ifi.lmu.de
Christoph BuschProfessor for Biometrics, Norwegian University of Science and Technology (NTNU)Dirección de correo verificada de ntnu.no

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Ines Färber

Data Management and Data Exploration

Dirección de correo verificada de cs.rwth-aachen.de - Página principal

Data Mining


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	171	2010
Subspace search and visualization to make sense of alternative clusterings in high-dimensional data A Tatu, F Maas, I Farber, E Bertini, T Schreck, T Seidl, D Keim Visual Analytics Science and Technology (VAST), 2012 IEEE Conference on, 63-72, 2012	150	2012
Subspace clustering meets dense subgraph mining: A synthesis of two paradigms S Gunnemann, I Farber, B Boden, T Seidl Data Mining (ICDM), 2010 IEEE 10th International Conference on, 845-850, 2010	149	2010
Discovering multiple clustering solutions: Grouping objects in different views of the data E Muller, S Gunnemann, I Farber, T Seidl Data Engineering (ICDE), 2012 IEEE 28th International Conference on, 1207-1210, 2012	91	2012
Spectral Subspace Clustering for Graphs with Feature Vectors S Günnemann, I Färber, S Raubach, T Seidl	75*
External evaluation measures for subspace clustering S Günnemann, I Färber, E Müller, I Assent, T Seidl Proceedings of the 20th ACM international conference on Information and …, 2011	63	2011
Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors S Günnemann, B Boden, I Färber, T Seidl Advances in Knowledge Discovery and Data Mining, 261-275, 2013	51	2013
Detection of orthogonal concepts in subspaces of high dimensional data S Günnemann, E Müller, I Färber, T Seidl Proceedings of the 18th ACM conference on Information and knowledge …, 2009	43	2009
GAMer: a synthesis of subspace clustering and dense subgraph mining S Günnemann, I Färber, B Boden, T Seidl Knowledge and Information Systems, 1-36, 2013	41	2013
Multi-view clustering using mixture models in subspace projections S Günnemann, I Färber, T Seidl Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012	31	2012
SMVC: semi-supervised multi-view clustering in subspace projections S Günnemann, I Färber, M Rüdiger, T Seidl Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	29	2014
Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data S Günnemann, I Färber, K Virochsiri, T Seidl Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012	28	2012
ASCLU: Alternative subspace clustering S Günnemann, I Färber, E Müller, T Seidl In MultiClust at KDD, 2010	19	2010
CoDA: Interactive cluster based concept discovery S Günnemann, I Färber, H Kremer, T Seidl Proceedings of the VLDB Endowment 3 (1-2), 1633-1636, 2010	12	2010
MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering Solutions S Gunnemann, H Kremer, I Farber, T Seidl Data Mining Workshops (ICDMW), 2010 IEEE International Conference on, 1387-1390, 2010	8	2010
Efficient Database Techniques for Identification with Fuzzy Vault Templates. C Böhm, I Färber, S Fries, U Korte, J Merkle, A Oswald, T Seidl, ... BIOSIG, 115-126, 2011	6	2011
Biometric Template Protection C Busch, U Korte, S Abt, C Böhm, I Färber, S Fries, J Merkle, C Nickel, ... Datenschutz und Datensicherheit-DuD 35 (3), 183-191, 2011	3	2011
Mining orthogonaler Konzepte in hochdimensionalen Datenbanken. I Färber, DIE Müller, DIS Günnemann Informatiktage, 153-156, 2009		2009
Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors—Complexity Proofs— S Günnemann, B Boden, I Färber, T Seidl

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