Publications |
| Schlitter N, Lässig J. Distributed Privacy Preserving Classification Based on Local Cluster Identifiers.; 2012. under review |
| Schlitter N, Falkowski T, Lässig J. DenGraph-HO: Density-based Hierarchical Community Detection for Explorative Visual Network Analysis. In: Research and Development in Intelligent Systems XXVIII Incorporating Applications and Innovations in Intelligent Systems XIX Proceedings of AI-2011, the Thirty-first SGAI International Conference on Innovative Techniques and Applications of Artificial Int. Cambridge: Springer; 2011. p. 283-96. |  |
| Schlitter N, Lässig J. Market Simulation of Smart Grids with adaptive Transmission Fees. Journal of the University of Applied Sciences Mittweida. 2011:46-9. | |
| Schlitter N, Falkowski T. Mining the Dynamics of Music Preferences from a Social Networking Site. In: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining. Athens: IEEE Computer Society; 2009. p. 243-8. | |
| Falkowski T, Schlitter N. Analyzing the Music Listening Behavior and its Temporal Dynamics Using Data from a Social Networking Site. Zurich; 2008. Presented at The 5th conference on Applications of Social Network Analysis (ASNA) |
| Schlitter N. A Protocol for Privacy Preserving Neural Network Learning on Horizontal Partitioned Data. In: Privacy Statistics in Databases (PSD) 2008. Istanbul,Turkey; 2008. on CD. | |
| Schlitter N, Schilz ST. Strategischer IKT-Einsatz schafft Wettbewerbsvorteile durch unternehmensübergreifendes Data Mining. In: Teich T, Schumann C, Dürr H, Gäse T, editors. Tagungsband ZFPro'08. Plauen: M&S-Verlags-OHG; 2008. p. 25-34. | |
| Schlitter N. Analyse und Prognose ökonomischer Zeitreihen: Neuronale Netze zur Aktienkursprognose. Saarbrücken: VDM Verlag Dr. Müller; 2008. | |
| Möller M, Schlitter N. Analyse und Prognose ökonomischer Zeitreihen mit Support Vector Machines. In: Steinmüller J, Langner H, Ritter M, Zeidler J, editors. 15 Jahre Künstliche Intelligenz an der Fakultät für Informatik. Chemnitz: Techn. Univ. Chemnitz, Fak. für Informatik; 2008. p. 189-201. (Chemnitzer Informatik-Berichte). | |
| Schlitter N. A Case Study of Time Series Forecasting with Backpropagation Networks. In: Steinmüller J, Langner H, Ritter M, Zeidler J, editors. 15 Jahre Künstliche Intelligenz an der TU Chemnitz. Chemnitz: Techn. Univ. Chemnitz, Fak. für Informatik; 2008. p. 203-17. (Chemnitzer Informatik-Berichte). | |
| Schlitter N, Schilz ST, Kähne F. Funkchips liefern Produktdaten - Kategorisierung durch Datamining vereinfacht die Qualitätskontrolle. Computer Zeitung. 2008. | |
| Rauch-Gebbensleben B, Kähne F, Horton G, Schlitter N, Schilz ST, Neike M. Ein Simulationsmodell zur Nachbildung von unternehmensübergreifenden Produktionsfehlern. In: Advances in simulation for production and logistics applications. Stuttgart: Fraunhofer IRB Verlag; 2008. p. 309-18. | |
| Schlitter N. RFID-basiertes integriertes Data Mining zur Manufakturfehlerprognose.; 2008. Presented at Research-/VDI Seminar of department of Mechanical Engineering, Chemnitz University of Technology |
| Schlitter N. Improving Time Series Forecasting With Backpropagation Networks. Freiburg; 2007. Presented at The 31st Annual Conference of the GfKl on Data Analysis, Machine Learning, and Applications |
| Schlitter N, Kähne F, Schilz ST, Mattke H. Potentials and problems of RFID-based cooperations in supply chains. In: Kersten W, Blecker T, Herstatt C, editors. Innovative Logistics Management: Competitive Advantages through new Processes and Services. Berlin: Erich Schmidt Verlag GmbH & Co.; 2007. p. 147-64. | |
| Schilz ST, Schlitter N, Kähne F, Genc E. RFID Rollout – What Can We Learn From EDI? In: Blecker T, Huang GQ, Salvador F, editors. Key Factors for Successful Logistics: Services, Transportation Concepts, IT and Management Tools. Berlin: Erich Schmidt Verlag GmbH & Co.; 2007. p. 153-68. | |