Mag. Christian Lettner
Researcher Data Analysis Systems
Phone: +43 50 343 837
christian.lettner@scch.at
Data Science - DAS
J. Martßinez Gil, R. Stumptner, C. Lettner, M. Pichler, S. Mahmoud, P. Praher. General model for tracking manufacturing products using graph databases. Data-Driven Process Discovery and Analysis - Proc. SIMPDA 2018, SIMPDA 2019, Lecture Notes in Business Information Processing, volume 379, pages 86-100, DOI 10.1007/978-3-030-46633-6_5, April, 2020.
L. Ehrlinger, C. Lettner, J. Himmelbauer. Tackling semantic shift in industrial streaming data over time. In M. Crowe, L. Ehrlinger, F. Laux, A. Schmidt (editors), Proceedings of the 12th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2020), pages 36-39, IARIA, October, 2020.
L. Ehrlinger, V. Haunschmid, D. Palazzini, C. Lettner. A DaQL to monitor data quality in machine learning applications. In S. Hartmann, J. Küng, S. Chakravarthy, G. Anderst-Kotsis, A. Tjoa, I. Khalil (editors), Database and Expert Systems Applications - Proc. DEXA 2019, Part II, Lecture Notes of Computer Science, volume 11709, pages 227-237, DOI 10.1007/978-3-030-27615-7_17, Springer, August, 2019.
J. Martínez Gil, R. Stumptner, C. Lettner, M. Pichler, W. Fragner. Design and implementation of a graph-based solution for tracking manufacturing products. In T. Welzer, E. al. (editors), New Trends in Databases and Information Systems - Proc. ADBIS 2019, Communications in Computer and Information Science, volume 1064, pages 417-423, DOI 10.1007/978-3-030-30278-8_41, Springer, September, 2019.
C. Natschläger, F. Kossak, C. Lettner, V. Geist, A. Denkmayr, B. Käferböck. A practical approach for process mining in production processes. In F. Piazolo, V. Geist, L. Brehm, R. Schmidt (editors), Innovations in Enterprise Information Systems Management and Engineering - ERP Future 2016 - Research, Revised Papers, Lecture Notes in Business Information Processing, volume 285, pages 87-95, DOI 0.1007/978-3-319-58801-8_8, Springer, May, 2017.
R. Stumptner, C. Lettner, B. Freudenthaler. Combining relational and NoSQL database systems for processing sensor data in disaster management. In R. Moreno-Diaz, F. Pichler, A. Quesada-Arencibia (editors), Computer Aided Systems Theory - EUROCAST 2015 Revised Selected Papers, Lecture Notes in Computer Science, volume 9520, pages 663-670, DOI 10.1007/978-3-319-27340-2_82, Springer, December, 2015.
R. Stumptner, C. Lettner, B. Freudenthaler, J. Pichler, W. Kirchmayr, E. Traxler. Maintaining and analyzing production process definitions using a tree-based similarity measure. In E. Hüllermeier, M. Minor (editors), Case-Based Reasoning Research and Development - Proc. ICCBR 2015, Lecture Notes in Artificial Intelligence, volume 9343, pages 366-380, DOI 10.1007/978-3-319-24586-7_25, Springer, September, 2015.
C. Lettner, R. Stumptner, K. Bokesch. An approach on ETL attached data quality management. In L. Bellatreche, M. Mohania (editors), Data Warehousing and Knowledge Discovery - Proc. DaWaK 2014, Lecture Notes in Computer Science, volume 8646, pages 1-8, Springer, September, 2014.
T. Steinmaurer, P. Traxler, M. Zwick, R. Stumptner, L. Christian. Combining stream processing engines and big data storages for data analysis. In T. Andreasen, H. Christiansen, J. Cubero, Z. Ras (editors), Foundations of Intelligent Systems - Proc. ISMIS 2014, Lecture Notes in Computer Science, volume 8502, pages 476-485, Springer, June, 2014.
C. Lettner, M. Pichler, W. Kirchmayr, F. Kokert, M. Habringer. RDFreduce: Customized aggregations with provenance for RDF data based on an industrial use case. In E. Weippl, M. Indrawan-Santiago, M. Steinbauer, G. Kotsis, I. Khalil I. (editors), Proceedings of the 5th International Conference on Information Integration and Web-based Applications & Services - iiWAS 2013, pages 336-340, December, 2013.