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About

Martin Scholz studied computer sciences at the University of Dortmund from 1994 to 2001. Since September 2001 he is a research assistant and Ph. D. student at the Artificial Intelligence Unit of the University of Dortmund.

Projects

Research Topics

Publications

Scholz/2007a Scholz, Martin. Scalable and Accurate Knowledge Discovery in Real-World Databases. Department of Computer Science, University of Dortmund, 2007.
Scholz/Klinkenberg/2006b Scholz, Martin and Klinkenberg, Ralf. Boosting Classifiers for Drifting Concepts. In Intelligent Data Analysis (IDA), Special Issue on Knowledge Discovery from Data Streams, Vol. 11, No. 1, pages 3--28, 2007.
Mierswa/etal/2006a Mierswa, Ingo and Wurst, Michael and Klinkenberg, Ralf and Scholz, Martin and Euler, Timm. YALE: Rapid Prototyping for Complex Data Mining Tasks. In Tina Eliassi-Rad and Lyle H. Ungar and Mark Craven and Dimitrios Gunopulos (editors), Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2006), pages 935--940, New York, USA, ACM Press, 2006.
Scholz/2006a Scholz, Martin. Boosting in PN Spaces. In Johannes Furnkranz, Tobias Scheffer, Myra Spiliopoulou (editors), Proceedings of the 17th European Conference on Machine Learning (ECML-06), Vol. 4212, pages 377--388, Berlin, Germany, Springer, 2006.
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, 2006.
Wurst/Scholz/2006a Wurst, Michael and Scholz, Martin. Distributed Subgroup Discovery. In Johannes Furnkranz, Tobias Scheffer, Myra Spiliopoulou (editors), Proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD-06), Vol. 4213, pages 421--433, Berlin, Germany, Springer, 2006.
Scholz/2005a Scholz, Martin. Knowledge-Based Sampling for Subgroup Discovery. In Morik, Katharina and Boulicaut, Jean-Francois and Siebes, Arno (editors), Local Pattern Detection, Vol. LNAI 3539, pages 171--189, Springer, 2005.
Scholz/2005b Scholz, Martin. Sampling-Based Sequential Subgroup Mining. In Grossman, R. L. and Bayardo, R. and Bennett, K. and Vaidya, J. (editors), Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '05), pages 265--274, Chicago, Illinois, USA, ACM Press, 2005.
Scholz/2005c Scholz, Martin. Comparing Knowledge-Based Sampling to Boosting. No. 26, Collaborative Research Center on the Reduction of Complexity for Multivariate Data Structures (SFB 475), University of Dortmund, Dortmund, Germany, 2005.
Scholz/2005d Scholz, Martin. On the Tractability of Rule Discovery from Distributed Data. In Han, J. and Wah, B.W. and Raghavan, V. and Wu, X. and Rastogi, R. (editors), Proceedings of the 5th IEEE International Conference on Data Mining (ICDM '05), pages 761--764, Houston, Texas, USA, IEEE Computer Society, 2005.
Scholz/2005e Scholz, Martin. On the Complexity of Rule Discovery from Distributed Data. No. 31, SFB475, Universitat Dortmund, Dortmund, Germany, 2005.
Scholz/Klinkenberg/2005a Scholz, Martin and Klinkenberg, Ralf. An Ensemble Classifier for Drifting Concepts. In Gama, J. and Aguilar-Ruiz, J. S. (editors), Proceedings of the Second International Workshop on Knowledge Discovery in Data Streams, pages 53--64, Porto, Portugal, 2005.
Euler/Scholz/2004a Euler, Timm and Scholz, Martin. Using Ontologies in a KDD Workbench. In Buitelaar, P. and Franke, J. and Grobelnik, M. and Paa?, G. and Svatek, V. (editors), Workshop on Knowledge Discovery and Ontologies at ECML/PKDD '04, pages 103--108, Pisa, Italy, 2004.
Foussette/etal/2004a Foussette, Christophe and Hakenjos, Daniel and Scholz, Martin. KDD-Cup 2004: Protein Homology Task. In ACM SIGKDD Explorations Newsletter, Vol. 6, No. 2, pages 128 -- 131, 2004.
Morik/Scholz/2004a Morik, Katharina and Scholz, Martin. The MiningMart Approach to Knowledge Discovery in Databases. In Ning Zhong and Jiming Liu (editors), Intelligent Technologies for Information Analysis, pages 47--65, Springer, 2004.
Euler/etal/2003a Euler, Timm and Morik, Katharina and Scholz, Martin. MiningMart: Sharing Successful KDD Processes. In Hotho, Andreas and Stumme, Gerd (editors), LLWA 2003 -- Tagungsband der GI-Workshop-Woche Lehren -- Lernen -- Wissen -- Adaptivitat, pages 121--122, 2003.
Morik/etal/2003a Morik,Katharina and Scholz, Martin and Euler, Timm. MiningMart Final Report. No. D20.4, IST Project MiningMart, IST-11993, 2003.
Morik/etal/2003b Morik, Katharina and Scholz, Martin and Euler, Timm. Ext-MM Final Report. No. D20.5, IST Project MiningMart, IST-11993, 2003.
Morik/Scholz/2002a Morik, Katharina and Scholz, Martin. The MiningMart Approach. In Workshop Management des Wandels der 32. GI Jahrestagung, 2002.
Scholz/2002a Scholz, Martin. Using real world data for modeling a protocol for ICU monitoring. In Lucas, Peter and Asker, Lars and Miksch, Silvia (editors), Intelligent Data Analysis in Medicine and Pharmacology Workshop (IDAMAP 2002), at 15th European Conference on Artificial Intelligence, pages 85--90, Lyon, France, 2002.
Scholz/2001a Scholz, Martin. Modellierung eines intensivmedizinischen Behandlungsprotokolls zur Validierung anhand realer Patientendaten. Fachbereich Informatik, Universitat Dortmund, 2001.
Scholz/Haustein/2001b Scholz, Martin and Haustein, Stefan. The MLnet II Training Interactive AI Resources. In Proceedings of the IJCAI 2001 Workshop on Interactive AI Resources, 2001.

Software

Supervised Master's Theses