M. Böttcher

Predicting Future Decision Trees from Evolving Data

Rudolf Kruse, Martin Spott, Mirko Böttcher, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Mining changing customer segments in dynamic markets

Rudolf Kruse, Detlef D. Nauck, Martin Spott, 2009, Expert Syst. Appl..

A Framework for Discovering and Analyzing Changing Customer Segments

Detlef D. Nauck, Martin Spott, Mirko Böttcher, 2007, ICDM.

Towards a Framework for Change Detection in Data Sets

Detlef D. Nauck, Martin Spott, Dymitr Ruta, 2006, SGAI Conf..

A framework for discovering interesting business changes from data

Christian Borgelt, Rudolf Kruse, Detlef Nauck, 2006 .

Contrast and change mining

Mirko Böttcher, M. Böttcher, 2011, WIREs Data Mining Knowl. Discov..

A Condensed Representation of Itemsets for Analyzing Their Evolution over Time

Rudolf Kruse, Martin Spott, Mirko Böttcher, 2009, ECML/PKDD.

On exploiting the power of time in data mining

Myra Spiliopoulou, Frank Höppner, Mirko Böttcher, 2008, SKDD.

Relevance Feedback for Association Rules by Leveraging Concepts from Information Retrieval

Rudolf Kruse, Detlef D. Nauck, Mirko Böttcher, 2007, SGAI Conf..

Detecting temporally redundant association rules

Detlef D. Nauck, Martin Spott, Mirko Böttcher, 2005, Fourth International Conference on Machine Learning and Applications (ICMLA'05).

An Algorithm for Anticipating Future Decision Trees from Concept-Drifting Data

Rudolf Kruse, Martin Spott, Mirko Böttcher, 2008, SGAI Conf..