Mirko Böttcher
Mirko Böttcher
AI Architect, Techniker Krankenkasse, Hamburg
Dirección de correo verificada de sema4.org
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Mining changing customer segments in dynamic markets
M Böttcher, M Spott, D Nauck, R Kruse
Expert systems with Applications 36 (1), 155-164, 2009
782009
On exploiting the power of time in data mining
M Böttcher, F Höppner, M Spiliopoulou
ACM SIGKDD Explorations Newsletter 10 (2), 3-11, 2008
772008
Contrast and change mining
M Boettcher
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1 (3 …, 2011
392011
Data processing method for controlling a network
M Boettcher, D Nauck, D Ruta, M Spott
US Patent 8,407,176, 2013
262013
Method for capturing local and evolving clusters
M Boettcher, F Hoeppner
US Patent 7,885,791, 2011
252011
Predicting future decision trees from evolving data
M Böttcher, M Spott, R Kruse
2008 Eighth IEEE International Conference on Data Mining, 33-42, 2008
172008
Towards a framework for change detection in data sets
M Böttcher, D Nauck, D Ruta, M Spott
International Conference on Innovative Techniques and Applications of …, 2006
172006
A framework for discovering interesting business changes from data
M Böttcher, D Nauck, C Borgelt, R Kruse
BT Technology Journal 24 (2), 219-228, 2006
132006
Detecting temporally redundant association rules
M Bottcher, M Spott, D Nauck
Fourth International Conference on Machine Learning and Applications (ICMLA …, 2005
112005
From Change Mining to Relevance Feedback: A Unified View on Assessing Rule Interestingness
M Boettcher, G Ruß, D Nauck, R Kruse
Post-Mining of association rules: Techniques for effective knowledge …, 2009
92009
Matching partitions over time to reliably capture local clusters in noisy domains
F Höppner, M Böttcher
European Conference on Principles of Data Mining and Knowledge Discovery …, 2007
72007
A framework for discovering and analyzing changing customer segments
M Böttcher, M Spott, D Nauck
Industrial Conference on Data Mining, 255-268, 2007
62007
Relevance feedback for association rules using fuzzy score aggregation
G Ruß, M Bottcher, R Kruse
NAFIPS 2007-2007 Annual Meeting of the North American Fuzzy Information …, 2007
62007
A condensed representation of itemsets for analyzing their evolution over time
M Boettcher, M Spott, R Kruse
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2009
52009
Temporal aspects in data mining
R Kruse, M Steinbrecher, M Boettcher
Proceedings of the 2010 World Congress on Computational Intelligence, 18-23, 2010
32010
An algorithm for anticipating future decision trees from concept-drifting data
M Böttcher, M Spott, R Kruse
International Conference on Innovative Techniques and Applications of …, 2008
32008
Relevance feedback for association rules by leveraging concepts from information retrieval
G Ruß, D Nauck, M Böttcher, R Kruse
International Conference on Innovative Techniques and Applications of …, 2007
32007
Exploring time series of patterns: guided drill-down in hierarchies using change mining on frequent item sets
M Böttcher, M Spott
Computational Intelligence in Intelligent Data Analysis, 181-194, 2013
12013
Modelling Customer Satisfaction Using Bayesian Networks
J Fatah, D Nauck, M Boettcher
Proc. 11th Int. Conf. Information Processing and Management of Uncertainty …, 0
1
On utilising change over time in data mining
M Böttcher
Universitätsbibl., 2013
2013
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Artículos 1–20