[1] Charlie Isaksson, Margaret H. Dunham, and Michael Hahsler. SOStream: Self organizing density-based clustering over data stream. In International Conference on Machine Learning and Data Mining (MLDM'2012). Springer, July 2012. [ bib ]
[2] Maya El Dayeh and Michael Hahsler. Biological pathway completion using network motifs and random walks on graphs. In IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2012), pages 229-236. IEEE, May 2012. [ bib | .pdf ]
[3] Maya El Dayeh and Michael Hahsler. Analyzing incomplete biological pathways using network motifs. In 27th Symposium On Applied Computing (SAC 2012), volume 2, pages 1355-1360. ACM, 2012. [ bib | .pdf ]
[4] Vladimir Jovanovic, Margaret H. Dunham, Michael Hahsler, and Yu Su. Evaluating hurricane intensity prediction techniques in real time. In Third IEEE ICDM Workshop on Knowledge Discovery from Climate Data, Proceedings of the of the 2011 IEEE International Conference on Data Mining Workshops (ICDMW 2011). IEEE, December 2011. [ bib | .pdf ]
[5] Michael Hahsler and Sudheer Chelluboina. Visualizing association rules in hierarchical groups. In Computing Science and Statistics, Vol. 42, 42nd Symposium on the Interface: Statistical, Machine Learning, and Visualization Algorithms (Interface 2011). The Interface Foundation of North America, June 2011. [ bib | .pdf ]
[6] 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. [ bib | at the publisher | .pdf ]
[7] 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. [ bib | .pdf ]
[8] 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. [ bib | at the publisher ]
[9] Yu Su, Sudheer Chelluboina, Michael Hahsler, and Margaret H. Dunham. A new data mining model for hurricane intensity prediction. In Second IEEE ICDM Workshop on Knowledge Discovery from Climate Data: Prediction, Extremes and Impacts, Proceedings of the of the 2010 IEEE International Conference on Data Mining Workshops (ICDMW 2010), pages 98-105. IEEE, December 2010. [ bib | at the publisher | .pdf ]
[10] 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. [ bib | at the publisher ]
[11] Margaret H. Dunham, Michael Hahsler, and Myra Spiliopoulou, editors. Proceedings of the First International Workshop on Novel Data Stream Pattern Mining Techniques (StreamKDD'10). ACM Press, New York, NY, USA, 2010. [ bib | at the publisher ]
[12] 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. [ bib | DOI | at the publisher ]
[13] 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. [ bib | at the publisher ]
[14] Rao M. Kotamarti, Michael Hahsler, Douglas W. Raiford, and Margaret H. Dunham. Sequence transformation to a complex signature form for consistent phylogenetic tree using extensible Markov model. In Proceedings of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2010). IEEE, 2010. [ bib | .pdf ]
[15] Rao M. Kotamarti, Douglas W. Raiford, Michael Hahsler, Yuhang Wang, Monnie McGee, and Margaret H. Dunham. Targeted genomic signature profiling with quasi-alignment statistics. Article 63, COBRA Preprint Series, November 2009. [ bib | at the publisher ]
[16] Michael Hahsler and Kurt Hornik. Dissimilarity plots: A visual exploration tool for partitional clustering. Report 89, Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, September 2009. [ bib | at the publisher ]
[17] Michael Hahsler, Christian Buchta, and Kurt Hornik. Selective association rule generation. Computational Statistics, 23(2):303-315, April 2008. [ bib | DOI | at the publisher | .pdf ]
[18] 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. [ bib | at the publisher ]
[19] Michael Hahsler and Kurt Hornik. TSP - Infrastructure for the traveling salesperson problem. Journal of Statistical Software, 23(2):1-21, December 2007. [ bib | at the publisher ]
[20] Michael Hahsler, Kurt Hornik, and Christian Buchta. Getting things in order: An introduction to the R package seriation. Report 58, Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, August 2007. [ bib | at the publisher ]
[21] Christoph Breidert and Michael Hahsler. Adaptive conjoint analysis for pricing music downloads. In R. Decker and H.-J. Lenz, editors, Advances in Data Analysis, Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V., Freie Universität Berlin, March 8-10, 2006, Studies in Classification, Data Analysis, and Knowledge Organization, pages 409-416. Springer-Verlag, 2007. [ bib | at the publisher | .pdf ]
[22] Michael Hahsler and Kurt Hornik. Building on the arules infrastructure for analyzing transaction data with R. In R. Decker and H.-J. Lenz, editors, Advances in Data Analysis, Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V., Freie Universität Berlin, March 8-10, 2006, Studies in Classification, Data Analysis, and Knowledge Organization, pages 449-456. Springer-Verlag, 2007. [ bib | at the publisher | .pdf ]
[23] Michael Hahsler and Kurt Hornik. New probabilistic interest measures for association rules. Intelligent Data Analysis, 11(5):437-455, 2007. [ bib | at the publisher | .pdf ]
[24] Thomas Reutterer, Michael Hahsler, and Kurt Hornik. Data Mining und Marketing am Beispiel der explorativen Warenkorbanalyse. Marketing ZFP, 29(3):165-181, 2007. [ bib | at the publisher ]
[25] Michael Hahsler and Kurt Hornik. TSP - Infrastructure for the traveling salesperson problem. Report 45, Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, December 2006. [ bib | at the publisher ]
[26] Michael Hahsler. A model-based frequency constraint for mining associations from transaction data. Data Mining and Knowledge Discovery, 13(2):137-166, September 2006. [ bib | DOI | at the publisher | .pdf ]
[27] Michael Hahsler and Kurt Hornik. New probabilistic interest measures for association rules. Report 38, Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, August 2006. [ bib | at the publisher ]
[28] Christoph Breidert, Michael Hahsler, and Thomas Reutterer. A review of methods for measuring willingness-to-pay. Innovative Marketing, 2(4):8-32, 2006. [ bib | at the publisher | .pdf ]
[29] Michael Hahsler, Kurt Hornik, and Thomas Reutterer. Warenkorbanalyse mit Hilfe der Statistik-Software R. In Peter Schnedlitz, Renate Buber, Thomas Reutterer, Arnold Schuh, and Christoph Teller, editors, Innovationen in Marketing, pages 144-163. Linde-Verlag, 2006. [ bib | at the publisher | .pdf ]
[30] Michael Hahsler, Kurt Hornik, and Thomas Reutterer. Implications of probabilistic data modeling for mining association rules. In M. Spiliopoulou, R. Kruse, C. Borgelt, A. Nürnberger, and W. Gaul, editors, From Data and Information Analysis to Knowledge Engineering, Proceedings of the 29th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Magdeburg, March 9-11, 2005, Studies in Classification, Data Analysis, and Knowledge Organization, pages 598-605. Springer-Verlag, 2006. [ bib | at the publisher | .pdf ]
[31] 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. [ bib | at the publisher | .pdf ]
[32] Michael Hahsler, Bettina Grün, and Kurt Hornik. A computational environment for mining association rules and frequent item sets. Report 15, Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, April 2005. [ bib | at the publisher ]
[33] Michael Hahsler, Kurt Hornik, and Thomas Reutterer. Implications of probabilistic data modeling for rule mining. Report 14, Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, March 2005. [ bib | at the publisher ]
[34] Christoph Breidert, Michael Hahsler, and Lars Schmidt-Thieme. Reservation price estimation by adaptive conjoint analysis. In Claus Weihs and Wolfgang Gaul, editors, Classification - the Ubiquitous Challenge, Proceedings of the 28th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Dortmund, March 9-11, 2004, Studies in Classification, Data Analysis, and Knowledge Organization, pages 577-584. Springer-Verlag, 2005. [ bib | at the publisher | .pdf ]
[35] Georg Fessler, Michael Hahsler, and Michaela Putz. ePubWU - Erfahrungen mit einer Volltext an der Wirtschaftsuniversität Wien. In Christian Enichlmayr, editor, Bibliotheken - Fundament der Bildung, 28. Österreichischer Bibliothekartag 2004, Schriftenreihe der Oö. Landesbibliothek, pages 190-193, 2005. [ bib ]
[36] Michael Hahsler. A quantitative study of the adoption of design patterns by open source software developers. In S. Koch, editor, Free/Open Source Software Development, pages 103-123. Idea Group Publishing, 2005. [ bib | at the publisher | .pdf ]
[37] Michael Hahsler. Optimizing web sites for customer retention. In Bing Liu, Myra Spiliopoulou, Jaideep Srivastava, and Alex Tuzhilin, editors, Proceedings of the 2005 International Workshop on Customer Relationship Management: Data Mining Meets Marketing, November 18-19, 2005, New York City, USA, 2005. [ bib | .pdf ]
[38] Michael Hahsler and Stefan Koch. Discussion of a large-scale open source data collection methodology. In 38th Annual Hawaii International Conference on System Sciences (HICSS'05), January 3-6, 2005 Hilton Waikoloa Village, Big Island, Hawaii. IEEE Computer Society Press, 2005. [ bib | at the publisher | .pdf ]
[39] Michael Hahsler. A model-based frequency constraint for mining associations from transaction data. Working Paper 07/2004, Working Papers on Information Processing and Information Management, Institut für Informationsverarbeitung und -wirtschaft, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, November 2004. [ bib | at the publisher ]
[40] Susanne Hafner and Michael Hahsler. Preisvergleich zwischen Online-Shops und traditionellen Geschäften: Fallstudie Spieleeinzelhandel. Working Paper 04/2004, Working Papers on Information Processing and Information Management, Institut für Informationsverarbeitung und -wirtschaft, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, August 2004. [ bib | at the publisher ]
[41] Georg Fessler, Michael Hahsler, Michaela Putz, Judith Schwarz, and Brigitta Wiebogen. Projektbericht ePubWU 2001-2003. Augasse 2-6, 1090 Wien, Wirtschaftsuniversität Wien, January 2004. [ bib | .pdf ]
[42] Michael Hahsler and Stefan Koch. Cooperation and disruptive behaviour - learning from a multi-player internet gaming community. In Piet Kommers, Pedro Isaias, and Miguel Baptista Nunes, editors, IADIS International Conference Web Based Communities 2004, Lisbon, Portugal, 24-26 March 2004, pages 35-42. International Association for Development of the Information Society (IADIS), 2004. [ bib | at the publisher | .pdf ]
[43] 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. [ bib | at the publisher | .pdf ]
[44] Andreas Geyer-Schulz, Michael Hahsler, Andreas Neumann, and Anke Thede. Behavior-based recommender systems as value-added services for scientific libraries. In Hamparsum Bozdogan, editor, Statistical Data Mining & Knowledge Discovery, pages 433-454. Chapman & Hall / CRC, July 2003. [ bib | at the publisher ]
[45] Andreas Geyer-Schulz, Michael Hahsler, Andreas Neumann, and Anke Thede. An integration strategy for distributed recommender services in legacy library systems. In M. Schader, W. Gaul, and M. Vichi, editors, Between Data Science and Applied Data Analysis, Proceedings of the 26th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Mannheim, July 22-24, 2002, Studies in Classification, Data Analysis, and Knowledge Organization, pages 412-420. Springer-Verlag, July 2003. [ bib | at the publisher ]
[46] Andreas Geyer-Schulz, Michael Hahsler, and Anke Thede. Comparing association-rules and repeat-buying based recommender systems in a B2B environment. In M. Schader, W. Gaul, and M. Vichi, editors, Between Data Science and Applied Data Analysis, Proceedings of the 26th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Mannheim, July 22-24, 2002, Studies in Classification, Data Analysis, and Knowledge Organization, pages 421-429. Springer-Verlag, July 2003. [ bib | at the publisher ]
[47] Edward Bernroider, Michael Hahsler, Stefan Koch, and Volker Stix. Data Envelopment Analysis zur Unterstützung der Auswahl und Einführung von ERP-Systemen. In Andreas Geyer-Schulz and Alfred Taudes, editors, Informationswirtschaft: Ein Sektor mit Zukunft, Symposium 4.-5. September 2003, Wien, Österreich, Lecture Notes in Informatics (LNI) P-33, pages 11-26. Gesellschaft für Informatik, 2003. [ bib | at the publisher ]
[48] Andreas Geyer-Schulz and Michael Hahsler. Comparing two recommender algorithms with the help of recommendations by peers. In O.R. Zaiane, J. Srivastava, M. Spiliopoulou, and B. Masand, editors, WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles 4th International Workshop, Edmonton, Canada, July 2002, Revised Papers, Lecture Notes in Computer Science LNAI 2703, pages 137-158. Springer-Verlag, 2003. (Revised version of the WEBKDD 2002 paper “Evaluation of Recommender Algorithms for an Internet Information Broker based on Simple Association Rules and on the Repeat-Buying Theory”). [ bib | at the publisher | .pdf ]
[49] Andreas Geyer-Schulz, Michael Hahsler, Andreas Neumann, and Anke Thede. Recommenderdienste für wissenschaftliche Bibliotheken und Bibliotheksverbünde. In Andreas Geyer-Schulz and Alfred Taudes, editors, Informationswirtschaft: Ein Sektor mit Zukunft, Symposium 4.-5. September 2003, Wien, Österreich, Lecture Notes in Informatics (LNI) P-33, pages 43-58. Gesellschaft für Informatik, 2003. [ bib | at the publisher ]
[50] Michael Hahsler. A quantitative study of the application of design patterns in java. Working Paper 01/2003, Working Papers on Information Processing and Information Management, Institut für Informationsverarbeitung und -wirtschaft, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, January 2003. [ bib | html version | at the publisher ]
[51] Andreas Geyer-Schulz and Michael Hahsler. Software reuse with analysis patterns. In Proceedings of the 8th AMCIS, pages 1156-1165, Dallas, TX, August 2002. Association for Information Systems. [ bib | at the publisher | .pdf ]
[52] Andreas Geyer-Schulz and Michael Hahsler. Evaluation of recommender algorithms for an internet information broker based on simple association rules and on the repeat-buying theory. In Brij Masand, Myra Spiliopoulou, Jaideep Srivastava, and Osmar R. Zaiane, editors, Fourth WEBKDD Workshop: Web Mining for Usage Patterns & User Profiles, pages 100-114, Edmonton, Canada, July 2002. [ bib | .pdf ]
[53] Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. A customer purchase incidence model applied to recommender systems. In R. Kohavi, B.M. Masand, M. Spiliopoulou, and J. Srivastava, editors, WEBKDD 2001 - Mining Log Data Across All Customer Touch Points, Third International Workshop, San Francisco, CA, USA, August 26, 2001, Revised Papers, Lecture Notes in Computer Science LNAI 2356, pages 25-47. Springer-Verlag, July 2002. (Revised version of the WEBKDD 2001 paper “A Customer Purchase Incidence Model Applied to Recommender Systems”). [ bib | at the publisher | .pdf ]
[54] Walter Böhm, Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. Repeat buying theory and its application for recommender services. In O. Opitz and M. Schwaiger, editors, Exploratory Data Analysis in Empirical Research, Proceedings of the 25th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Munich, March 14-16, 2001, pages 229-239. Springer-Verlag, 2002. [ bib | at the publisher | .pdf ]
[55] Wolfgang Gaul, Andreas Geyer-Schulz, Michael Hahsler, and Lars Schmidt-Thieme. eMarketing mittels Recommendersystemen. Marketing ZFP, 24:47-55, 2002. [ bib | at the publisher ]
[56] Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. Recommendations for virtual universities from observed user behavior. In W. Gaul and G. Ritter, editors, Classification, Automation, and New Media, Proceedings of the 24th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Passau, March 15-17, 2000, pages 273-280. Springer-Verlag, 2002. [ bib | at the publisher | .pdf ]
[57] Andreas Geyer-Schulz and Michael Hahsler. Software engineering with analysis patterns. Working Paper 01/2001, Working Papers on Information Processing and Information Management, Institut für Informationsverarbeitung und -wirtschaft, Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria, November 2001. [ bib | html version | at the publisher ]
[58] Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. Wissenschaftliche Recommendersysteme in Virtuellen Universitäten. In H.-J. Appelrath, R. Beyer, U. Marquardt, H.C. Mayr, and C. Steinberger, editors, Unternehmen Hochschule, Wien, Österreich, September 2001. Symposium UH2001, GI Lecture Notes in Informatics (LNI). [ bib | at the publisher | .pdf ]
[59] Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. A customer purchase incidence model applied to recommender systems. In WEBKDD2001 Workshop: Mining Log Data Across All Customer TouchPoints, pages 35-45, San Francisco, CA, August 2001. [ bib | .pdf ]
[60] 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. [ bib | at the publisher | .pdf ]
[61] Michael Hahsler. Analyse Patterns im Softwareentwicklungsprozeß mit Beispielen für Informationsmanagement und deren Anwendungen für die Virtuellen Universität der Wirtschaftsuniversität Wien. Dissertation, Wirtschaftsuniversität Wien, Augasse 2-6, A 1090 Wien, Österreich, January 2001. [ bib | at the publisher | .pdf ]
[62] Andreas Geyer-Schulz and Michael Hahsler. Automatic labelling of references for information systems. In Reinhold Decker and Wolfgang Gaul, editors, Classification and Information Processing at the Turn of the Millennium, Proceedings of the 23rd Annual Conference of the Gesellschaft für Klassifikation e.V., University of Bielefeld, March 10-12, 1999, Studies in Classification, Data Analysis, and Knowledge Organization, pages 451-459. Springer-Verlag, 2000. [ bib | at the publisher | .pdf ]
[63] Andreas Geyer-Schulz and Michael Hahsler. Lebenslanges virtuelles Lernen. In Franciszek Grucza, editor, Europas Arbeitswelt von Morgen, pages 51-54, Wien, 2000. Wiener Zentrum der Polnischen Akademie der Wissenschaften. [ bib | at the publisher ]
[64] Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. myvu: A next generation recommender system based on observed consumer behavior and interactive evolutionary algorithms. In Wolfgang Gaul, Otto Opitz, and Martin Schader, editors, Data Analysis: Scientific Modeling and Practical Applications, Studies in Classification, Data Analysis, and Knowledge Organization, pages 447-457. Springer Verlag, Heidelberg, Germany, 2000. [ bib | at the publisher | .pdf ]
[65] Michael Hahsler and Bernd Simon. User-centered navigation re-design for web-based information systems. In H. Michael Chung, editor, Proceedings of the Sixth Americas Conference on Information Systems (AMCIS 2000), pages 192-198, Long Beach, CA, 2000. Association for Information Systems. [ bib | at the publisher | .pdf ]
[66] Andreas Geyer-Schulz, Michael Hahsler, and Georg Schneider. The virtual university as a network economy. In Heinrich C. Mayr, Claudia Steinberger, Hans-Jürgen Appelrath, and Uwe Marquardt, editors, Informatik '99, Unternehmen Hochschule '99, Workshop-Unterlagen, pages 75-86, Bielefeld, Germany, October 1999. [ bib ]
[67] Andreas Geyer-Schulz, Michael Hahsler, and Georg Schneider. The virtual university and its embedded agents. ÖGAI Journal, 18(1):14-19, 1999. [ bib ]
[68] Peter Bruhn, Andreas Geyer-Schulz, Michael Hahsler, and Markus Mottel. Genetic machine learning and intelligent internet agents. ÖGAI Journal, 17(1):18-25, 1998. [ bib ]
[69] Michael Hahsler. Software Patterns: Pinwände. Diplomarbeit, Wirtschaftsuniversität Wien, Augasse 2-6, A 1090 Wien, Österreich, November 1997. [ bib | .pdf ]

This file was generated by bibtex2html 1.96.