Michael Hahsler

Department of Engineering Management, Information and Systems

Michael Hahsler

Assistant Professor

M.S. Wirtschaftsuniversität Wien, Austria; Ph.D., Wirtschaftsuniversität Wien, Austria


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Data Mining, Machine Learning, Business Analytics, Data Stream Mining, Recommender Systems, Data Visualization, Association Rule Mining, Market Basket Analysis.


Michael Hahsler, Sudheer Chelluboina, Kurt Hornik, and Christian Buchta. The arules R-package ecosystem: Analyzing interesting patterns from large transaction datasets. Journal of Machine Learning Research, 12:1977-1981, 2011.

Michael Hahsler and Kurt Hornik. Dissimilarity plots: A visual exploration tool for partitional clustering. Journal of Computational and Graphical Statistics, 10(2):335-354, June 2011.

Michael Hahsler and Margaret H. Dunham. Temporal structure learning for clustering massive data streams in real-time. In SIAM Conference on Data Mining (SDM11), pages 664-675. SIAM, April 2011.

Margaret H. Dunham, Michael Hahsler, and Myra Spiliopoulou. Novel data stream pattern mining, Report on the StreamKDD'10 Workshop. SIGKDD Explorations, 12(2):54-55, 2010.

Rao M. Kotamarti, Michael Hahsler, Douglas Raiford, Monnie McGee, and Margaret H. Dunham. Analyzing taxonomic classification using extensible Markov models. Bioinformatics, 26(18):2235-2241, 2010.

Michael Hahsler and Margaret H. Dunham. rEMM: Extensible Markov model for data stream clustering in R. Journal of Statistical Software, 35(5):1-31, 2010.

Michael Hahsler, Christian Buchta, and Kurt Hornik. Selective association rule generation. Computational Statistics, 23(2):303-315, April 2008.

Michael Hahsler, Kurt Hornik, and Christian Buchta. Getting things in order: An introduction to the R package seriation. Journal of Statistical Software, 25(3):1-34, March 2008.

Michael Hahsler and Kurt Hornik. TSP - Infrastructure for the traveling salesperson problem. Journal of Statistical Software, 23(2):1-21, December 2007.

Michael Hahsler and Kurt Hornik. New probabilistic interest measures for association rules. Intelligent Data Analysis, 11(5):437-455, 2007.

Michael Hahsler. A model-based frequency constraint for mining associations from transaction data. Data Mining and Knowledge Discovery, 13(2):137-166, September 2006.

Christoph Breidert, Michael Hahsler, and Thomas Reutterer. A review of methods for measuring willingness-to-pay. Innovative Marketing, 2(4):8-32, 2006.

Michael Hahsler, Bettina Grün, and Kurt Hornik. arules - A computational environment for mining association rules and frequent item sets. Journal of Statistical Software, 14(15):1-25, October 2005.

Michael Hahsler. Integrating digital document acquisition into a university library: A case study of social and organizational challenges. Journal of Digital Information Management, 1(4):162-171, December 2003.

Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. Educational and scientific recommender systems: Designing the information channels of the virtual university. International Journal of Engineering Education, 17(2):153-163, 2001.