Business intelligence is an often-used term for applications that deploy data analysis with the aim of understanding and controlling the behaviour of an enterprise. Classic analysis methods like OLAP are as important as Data Mining in this area. These techniques can be used in virtually all areas within an enterprise: in production, administration, controlling, in marketing or in the analysis of past and future market segments.
Had/etal/2009a |
Had, Martin and Jungermann, Felix and Morik, Katharina.
Relation Extraction for Monitoring Economic Networks.
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Drozdzynski/2008a |
Drozdzynski, Maik.
Insolvenzprognose anhand von betriebswirtschaftlichen Kennzahlen.
Technische Universität Dortmund,
2008.
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Liebe/2008a |
Liebe, Miguel.
Lokale Modelle in Jahresabschlussdaten.
Technische Universität Dortmund,
2008.
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Scholz/Klinkenberg/2006b |
Scholz, Martin and Klinkenberg, Ralf.
Boosting Classifiers for Drifting Concepts.
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Vol. 11,
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pages 3--28,
2007.
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Morik/Rueping/2006a |
Morik, Katharina and Rüping, Stefan.
Klassifikations-/Clustermethoden und Konjunkturanalyse.
Duncker & Humbolt,
2006.
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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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Classification and Clustering in Business Cycle Analysis,
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Scholz/Klinkenberg/2006a |
Scholz, Martin and Klinkenberg, Ralf.
Boosting Classifiers for Drifting Concepts.
No. 6/06,
Collaborative Research Center on the Reduction of Complexity for Multivariate Data Structures (SFB 475), University of Dortmund,
Dortmund, Germany,
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Scholz/Klinkenberg/2005a |
Scholz, Martin and Klinkenberg, Ralf.
An Ensemble Classifier for Drifting Concepts.
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Proceedings of the Second International Workshop on Knowledge Discovery in Data Streams,
pages 53--64,
Porto, Portugal,
2005.
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Morik/Koepcke/2004a |
Morik, Katharina and Köpcke, Hanna.
Analysing Customer Churn in Insurance Data - A Case Study.
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Jean-Francois Boulicaut and Floriana Esposito and Fosca Giannotti and Dino Pedreschi (editors),
PKDD '04: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases,
Vol. 3202,
pages 325--336,
New York, NY, USA,
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Klinkenberg/2003a |
Klinkenberg, Ralf.
Predicting Phases in Business Cycles Under Concept Drift.
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Hotho, Andreas and Stumme, Gerd (editors),
LLWA 2003 -- Tagungsband der GI-Workshop-Woche \em Lehren -- Lernen -- Wissen -- Adaptivitat, Proceedings of the Workshop Week \em Teaching -- Learning -- Knowledge -- Adaptivity of the National German Computer Science Society (GI) / Annual Workshop on Machine Learning,
pages 3--10,
Karlsruhe, Germany,
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Kleiner/etal/2002a |
Kleiner, M. and Dirksen, U. and Chatti, K. and Morik, K. and Ritthoff, O..
Online-Regelung fuer das Profilbiegen mit Methoden der Computational Intelligence.
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Gronau, N. and Krallmann, H. and Scholz-Reiter, B. (editors),
Industrie Management,
No. 6,
pages 29--32,
Berlin,
GITO-Verlag,
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Morik/Rueping/2002a |
Morik, Katharina and Rüping, Stefan.
A Multistrategy Approach to the Classification of Phases in Business Cycles.
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Vol. 2430,
pages 307--318,
Berlin,
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2002.
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Michaelis/2000a |
Michaelis, Stefan.
Techniken des Data Mining zur Analyse von Telekommunikationsnetzwerken.
Fachbereich Informatik, Universitat Dortmund, Germany,
2000.
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Chliapnikov/99a |
Chliapnikov, Victor.
Anwendung von Data Mining Verfahren auf Datenbestaende der Bauwirtschaft.
Fachbereich Informatik, Universitaet Dortmund,
Universitaet Dortmund,
1999.
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Rueping/99a |
Rüping, Stefan.
Zeitreihenprognose fur Warenwirtschaftssysteme unter Berucksichtigung asymmetrischer Kostenfunktionen.
Universitat Dortmund,
1999.
|
Siebert/97a |
Mark Siebert.
Erwerb funktionaler, raumlicher und kausaler Beziehungen von Fahrzeugteilen aus einer technischen Dokumentation.
Fachbereich Informatik, Universitat Dortmund,
1997.
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Rossbach/94a |
Peter Ro?bach.
Optimierung von Belegungsplanen auf Grundlage Basiskonnektonistischer Methoden.
Fachbereich Informatik, Universitat Dortmund,
1994.
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