The aim of cluster analysis is to group objects according to their similarity. Beside traditional cluster analysis there are many current challenges concerning semi-supervised clustering or co-clustering. Incremental clustering for interactive applications is an important current research topic.
Bohnen/etal/2013a |
Bohnen, Fabian and Stolpe, Marco and Deuse, Jochen and Morik, Katharina.
Using a Clustering Approach with Evolutionary Optimized Attribute Weights to Form Product Families for Production Leveling.
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Bohnen/etal/2013b |
Bohnen, Fabian and Buhl, Matthias and Deuse, Jochen.
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Kaspari/2007a |
Kaspari, Andreas.
Maschinelle Lernverfahren für kollaboratives Tagging.
2007.
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Kaspari/Wurst/2007a |
Kaspari, Andreas and Wurst, Michael.
Multi-objective Frequent Termset Clustering.
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Morik/Wurst/2007a |
Morik, Katharina and Wurst, Michael.
Multi-Aspect Tagging for Collaborative Structuring.
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Deutsch/2006a |
Deutsch, Stephan.
Outlier Detection in USENET Newsgruppen.
University of Dortmund,
2006.
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Hennig/Wurst/2006a |
Hennig, Sascha and Wurst, Michael.
Incremental Clustering of Newsgroup Articles.
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Mierswa/Wurst/2006a |
Mierswa, Ingo and Wurst, Michael.
Information Preserving Multi-Objective Feature Selection for Unsupervised Learning.
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Mierswa/Wurst/2006b |
Mierswa, Ingo and Wurst, Michael.
Sound Multi-Objective Feature Space Transformation for Clustering.
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Morik/Rueping/2006a |
Morik, Katharina and Rüping, Stefan.
Klassifikations-/Clustermethoden und Konjunkturanalyse.
Duncker & Humbolt,
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Morik/Rueping/2006b |
Morik, Katharina and Rüping, Stefan.
An Inductive Logic Programming Approach to the Classification of Phases in Business Cycles.
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Wurst/etal/2006a |
Wurst, Michael and Morik, Katharina and Mierswa, Ingo.
Localized Alternative Cluster Ensembles for Collaborative Structuring.
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Heinle/2005a |
Heinle, Eduard.
Benutzergeleitetes Clustering von Musikdaten.
Fachbereich Informatik, Universit\"at Dortmund,
2005.
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Homburg/etal/2005a |
Homburg, Helge and Mierswa,Ingo and Moller, Bulent and Morik, Katharina and Wurst, Michael.
A Benchmark Dataset for Audio Classification and Clustering.
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Proc. of the International Symposium on Music Information Retrieval 2005,
pages 528--531,
London, UK,
Queen Mary University,
2005.
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Wurst/etal/2005a |
Wurst, Michael and Mierswa, Ingo and Morik, Katharina.
Structuring Music Collections by Exploiting Peers' Processing.
No. 43/05,
Collaborative Research Center 475, University of Dortmund,
2005.
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Stolpe/2003a |
Stolpe, Marco.
Ein Algorithmus zur Losung des Farthest-Pair-Problems.
Universitat Dortmund,
2003.
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Schewe/97b |
Schewe, Sandra.
Automatische Kategorisierung von Volltexten unter Anwendung von NLP-Techniken.
Fachbereich Informatik, Universitat Dortmund,
1997.
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Morik/Kietz/89b |
Morik, Katharina and Kietz, Jörg-Uwe.
A Bootstrapping Approach to Conceptual Clustering.
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