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Michael Wurst
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2010 – 2019
- 2014
- [c24]Alice Marascu, Pascal Pompey, Eric Bouillet, Michael Wurst, Olivier Verscheure, Martin Grund, Philippe Cudré-Mauroux
:
TRISTAN: Real-time analytics on massive time series using sparse dictionary compression. IEEE BigData 2014: 291-300 - [c23]Torsten Steinbach, Michael Wurst:
IBM's Analytic Warehouse Cloud Service. GI-Jahrestagung 2014: 751 - 2013
- [c22]Alice Marascu, Pascal Pompey, Eric Bouillet, Olivier Verscheure, Michael Wurst, Martin Grund, Philippe Cudré-Mauroux
MiSTRAL: An architecture for low-latency analytics on MasSive time series. IEEE BigData 2013: 15-21 - [c21]Marcus Behrendt, Mischa Böhm, Mustafa Caylak, Lena Eylert, Robert Friedrichs, Dennis Höting, Kamil Knefel, Timo Lottmann, Andreas Rehfeldt, Jens Runge, Sabrina-Cynthia Schnabel, Stephan Janssen, Daniela Nicklas, Michael Wurst:
Die "schlaue Stadt" - Erzeugung virtueller Sensordaten für Smart City Anwendungen. BTW 2013: 527-530 - [c20]Marcus Behrendt, Mischa Böhm, Marina Borchers, Mustafa Caylak, Lena Eylert, Robert Friedrichs, Dennis Höting, Kamil Knefel, Timo Lottmann, Andreas Rehfeldt, Jens Runge, Sabrina-Cynthia Schnabel, Stephan Janssen, Daniela Nicklas, Michael Wurst:
Simulation einer Stadt zur Erzeugung virtueller Sensordaten für Smart City Anwendungen. BUIS-Tage 2013: 441-446 - 2012
- [j5]Katharina Morik, Andreas Kaspari, Michael Wurst, Marcin Skirzynski:
Multi-objective frequent termset clustering. Knowl. Inf. Syst. 30(3): 715-738 (2012) - [c19]Ji Won Yoon, Francesco Fusco, Michael Wurst:
Bayesian separation of wind power generation signals. ICPR 2012: 2660-2663 - [c18]Francesco Fusco, Michael Wurst, Ji Won Yoon:
Mining residential household information from low-resolution smart meter data. ICPR 2012: 3545-3548 - 2011
- [c17]Martin A. Oberhofer, Michael Wurst:
Interactive Predictive Analytics with Columnar Databases. BTW 2011: 640-649 - 2010
- [c16]Benjamin Leonhardi, Bernhard Mitschang, Rubén Pulido de los Reyes, Christoph Sieb, Michael Wurst:
Augmenting OLAP exploration with dynamic advanced analytics. EDBT 2010: 687-692 - [p2]Andreas Hotho, Rasmus Ulslev Pedersen, Michael Wurst:
Ubiquitous Data. Ubiquitous Knowledge Discovery 2010: 61-74 - [p1]Katharina Morik, Michael Wurst:
Clustering the Web 2.0. Advances in Machine Learning II 2010: 207-223
2000 – 2009
- 2008
- [b1]Michael Wurst:
Distributed collaborative structuring: a data mining approach to information management in loosely coupled domains. Dortmund University of Technology, 2008 - 2007
- [j4]Michael Wurst, Katharina Morik:
Distributed feature extraction in a p2p setting - a case study. Future Gener. Comput. Syst. 23(1): 69-75 (2007) - [c15]Michael Wurst:
Multi-agent Learning by Distributed Feature Extraction. Adaptive Agents and Multi-Agents Systems 2007: 239-254 - [c14]Andreas Kaspari, Michael Wurst:
Multi-objective Frequent Termset Clustering. LWA 2007: 133-140 - [i1]Katharina Morik, Michael Wurst:
Multi-Aspect Tagging for Collaborative Structuring. Parallel Universes and Local Patterns 2007 - 2006
- [j3]Michael Wurst:
Analysis and evaluation of distributed knowledge management by agent-based simulation. Int. J. Knowl. Based Intell. Eng. Syst. 10(4): 307-317 (2006) - [c13]Michael Wurst, Katharina Morik, Ingo Mierswa:
Localized Alternative Cluster Ensembles for Collaborative Structuring. ECML 2006: 485-496 - [c12]Ingo Mierswa, Michael Wurst:
Information preserving multi-objective feature selection for unsupervised learning. GECCO 2006: 1545-1552 - [c11]Sascha Hennig, Michael Wurst:
Incremental Clustering of Newsgroup Articles. IEA/AIE 2006: 332-341 - [c10]Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Martin Scholz, Timm Euler:
YALE: rapid prototyping for complex data mining tasks. KDD 2006: 935-940 - [c9]Ingo Mierswa, Michael Wurst:
Sound Multi-objective Feature Space Transformation for Clustering. LWA 2006: 330-337 - [c8]Michael Wurst, Martin Scholz:
Distributed Subgroup Mining. PKDD 2006: 421-433 - [c7]Oliver Flasch, Andreas Kaspari, Katharina Morik, Michael Wurst:
Aspect-Based Tagging for Collaborative Media Organization. WebMine 2006: 122-141 - 2005
- [c6]Ingo Mierswa, Michael Wurst:
Efficient Case Based Feature Construction. ECML 2005: 641-648 - [c5]Helge Homburg, Ingo Mierswa, Bülent Möller, Katharina Morik, Michael Wurst:
A Benchmark Dataset for Audio Classification and Clustering. ISMIR 2005: 528-531 - [c4]Jasminko Novak, Michael Wurst:
Collaborative Knowledge Visualization for Cross-Community Learning. Knowledge and Information Visualization 2005: 95-116 - 2004
- [j2]Jasminko Novak, Michael Wurst:
Supporting Knowledge Creation and Sharing in Communities Based on Mapping Implicit Knowledge. J. Univers. Comput. Sci. 10(3): 235-251 (2004) - 2003
- [j1]Jasminko Novak, Christoph Kunz, Michael Wurst:
Entdeckung und Nutzbarmachung von stillem Wissen in heterogenen Expertengemeinschaften - das Projekt AWAKE. i-com 2(3): 18-26 (2003) - [c3]Jasminko Novak, Michael Wurst, Monika Fleischmann, Wolfgang Strauss:
Discovering, Visualizing, and Sharing Knowledge through Personalized Learning Knowledge Maps. AMKM 2003: 213-228 - [c2]João José Vasco Furtado, Ira J. Haimowitz, Michael Wurst:
Knowledge Discovery in Databases and Agent-Mediated Knowledge Management. AMKM 2003: 339-350 - [c1]Jasminko Novak, Monika Fleischmann, Wolfgang Strauss, Michael Wurst, Katharina Morik, Christoph Kunz, Jürgen Ziegler:
Verbindung heterogener Experten-Communities durch die Entdeckung, Visualisierung und Nutzbarmachung von stillem Wissen - das AWAKE Projekt. MuC 2003
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