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ORCIDThorsten Papenbrock
Person information
- affiliation: Hasso Plattner Institute, Potsdam, Germany
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2020 – today
- 2024
[j19]Tobias Bleifuß
, Thorsten Papenbrock, Thomas Bläsius, Martin Schirneck, Felix Naumann:
Discovering Functional Dependencies through Hitting Set Enumeration. Proc. ACM Manag. Data 2(1): 43:1-43:24 (2024)- [j18]Sebastian Schmidl, Felix Naumann, Thorsten Papenbrock:
AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data. Proc. VLDB Endow. 17(11): 2987-3002 (2024) - [c24]Phillip Wenig, Thorsten Papenbrock:
Series2Graph++: Distributed Detection of Correlation Anomalies in Multivariate Time Series. DaWaK 2024: 225-230 - [c23]Phillip Wenig, Sebastian Schmidl, Thorsten Papenbrock:
Anomaly Detectors for Multivariate Time Series: The Proof of the Pudding is in the Eating. ICDEW 2024: 96-101 - 2023
- [j17]Jan Kossmann, Thorsten Papenbrock, Felix Naumann:
Correction to: Data dependencies for query optimization: a survey. VLDB J. 32(2): 471 (2023) - [c22]Marcian Seeger, Sebastian Schmidl, Alexander Vielhauer, Thorsten Papenbrock:
DPQL: The Data Profiling Query Language. BTW 2023: 391-415 - [c21]Sebastian Schmidl, Phillip Wenig, Thorsten Papenbrock:
HYPEX: Hyperparameter Optimization in Time Series Anomaly Detection. BTW 2023: 461-483 - [c20]Florian Siepe, Phillip Wenig, Thorsten Papenbrock:
A Few Models to Rule Them All: Aggregating Machine Learning Models. LWDA 2023: 506-520 - [c19]Phillip Wenig, Thorsten Papenbrock:
Actix-Telepathy. REBLS@SPLASH 2023: 14-24 - 2022
- [j16]Sebastian Schmidl, Phillip Wenig, Thorsten Papenbrock:
Anomaly Detection in Time Series: A Comprehensive Evaluation. Proc. VLDB Endow. 15(9): 1779-1797 (2022) - [j15]Phillip Wenig, Sebastian Schmidl, Thorsten Papenbrock:
TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms. Proc. VLDB Endow. 15(12): 3678-3681 (2022) - [j14]Jan Kossmann, Thorsten Papenbrock, Felix Naumann:
Data dependencies for query optimization: a survey. VLDB J. 31(1): 1-22 (2022) - [j13]Sebastian Schmidl, Thorsten Papenbrock:
Efficient distributed discovery of bidirectional order dependencies. VLDB J. 31(1): 49-74 (2022) - [c18]Jan Kossmann, Felix Naumann, Daniel Lindner, Thorsten Papenbrock:
Workload-driven, Lazy Discovery of Data Dependencies for Query Optimization. CIDR 2022 - [c17]Phillip Wenig, Thorsten Papenbrock:
DataGossip: A Data Exchange Extension for Distributed Machine Learning Algorithms. EDBT 2022: 2:373-2:377 - 2021
- [j12]Hannes Mühleisen, Thorsten Papenbrock:
Front Matter. Proc. VLDB Endow. 14(6) (2021) - [j11]Johannes Schneider, Phillip Wenig, Thorsten Papenbrock:
Distributed detection of sequential anomalies in univariate time series. VLDB J. 30(4): 579-602 (2021) - [c16]Julian Weise, Sebastian Schmidl, Thorsten Papenbrock:
Optimized Theta-Join Processing. BTW 2021: 59-78 - [c15]Hazar Harmouch, Thorsten Papenbrock, Felix Naumann:
Relational Header Discovery using Similarity Search in a Table Corpus. ICDE 2021: 444-455 - 2020
- [j10]Ioannis K. Koumarelas, Thorsten Papenbrock, Felix Naumann:
MDedup: Duplicate Detection with Matching Dependencies. Proc. VLDB Endow. 13(5): 712-725 (2020) - [j9]Johann Birnick, Thomas Bläsius, Tobias Friedrich, Felix Naumann, Thorsten Papenbrock, Martin Schirneck:
Hitting Set Enumeration with Partial Information for Unique Column Combination Discovery. Proc. VLDB Endow. 13(11): 2270-2283 (2020) - [j8]Philipp Schirmer, Thorsten Papenbrock, Ioannis K. Koumarelas, Felix Naumann:
Efficient Discovery of Matching Dependencies. ACM Trans. Database Syst. 45(3): 13:1-13:33 (2020)
2010 – 2019
- 2019
- [c14]Sebastian Schmidl, Frederic Schneider, Thorsten Papenbrock:
An Actor Database System for Akka. BTW (Workshops) 2019: 225-234 - [c13]Thorsten Papenbrock:
Data Profiling - Effiziente Entdeckung Struktureller Abhängigkeiten. BTW 2019: 467-476 - [c12]Falco Dürsch, Axel Stebner, Fabian Windheuser, Maxi Fischer, Tim Friedrich, Nils Strelow, Tobias Bleifuß, Hazar Harmouch, Lan Jiang, Thorsten Papenbrock, Felix Naumann:
Inclusion Dependency Discovery: An Experimental Evaluation of Thirteen Algorithms. CIKM 2019: 219-228 - [c11]Philipp Schirmer, Thorsten Papenbrock, Sebastian Kruse, Felix Naumann, Dennis Hempfing, Torben Mayer, Daniel Neuschäfer-Rube:
DynFD: Functional Dependency Discovery in Dynamic Datasets. EDBT 2019: 253-264 - 2018
- [b2]Ziawasch Abedjan, Lukasz Golab, Felix Naumann, Thorsten Papenbrock:
Data Profiling. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2018, ISBN 978-3-031-00737-8 - 2017
- [b1]Thorsten Papenbrock:
Data profiling - efficient discovery of dependencies (Profilerstellung für Daten - Effiziente Entdeckung von Abhängigkeiten). University of Potsdam, Germany, 2017 - [j7]Fabian Tschirschnitz, Thorsten Papenbrock, Felix Naumann:
Detecting Inclusion Dependencies on Very Many Tables. ACM Trans. Database Syst. 42(3): 18:1-18:29 (2017) - [c10]Thorsten Papenbrock, Felix Naumann:
A Hybrid Approach for Efficient Unique Column Combination Discovery. BTW 2017: 195-204 - [c9]Sebastian Kruse, Thorsten Papenbrock, Christian Dullweber, Moritz Finke, Manuel Hegner, Martin Zabel, Christian Zöllner, Felix Naumann:
Fast Approximate Discovery of Inclusion Dependencies. BTW 2017: 207-226 - [c8]Thorsten Papenbrock, Felix Naumann:
Data-driven Schema Normalization. EDBT 2017: 342-353 - [p1]Thorsten Papenbrock:
Data Profiling - Effiziente Entdeckung Struktureller Abhängigkeiten. Ausgezeichnete Informatikdissertationen 2017: 191-200 - 2016
- [j6]Sebastian Kruse, Thorsten Papenbrock, Hazar Harmouch, Felix Naumann:
Data Anamnesis: Admitting Raw Data into an Organization. IEEE Data Eng. Bull. 39(2): 8-20 (2016) - [c7]Tobias Bleifuß, Susanne Bülow, Johannes Frohnhofen, Julian Risch, Georg Wiese, Sebastian Kruse, Thorsten Papenbrock, Felix Naumann:
Approximate Discovery of Functional Dependencies for Large Datasets. CIKM 2016: 1803-1812 - [c6]Jens Ehrlich, Mandy Roick, Lukas Schulze, Jakob Zwiener, Thorsten Papenbrock, Felix Naumann:
Holistic Data Profiling: Simultaneous Discovery of Various Metadata. EDBT 2016: 305-316 - [c5]Thorsten Papenbrock, Felix Naumann:
A Hybrid Approach to Functional Dependency Discovery. SIGMOD Conference 2016: 821-833 - [c4]Sebastian Kruse, Anja Jentzsch, Thorsten Papenbrock, Zoi Kaoudi, Jorge-Arnulfo Quiané-Ruiz, Felix Naumann:
RDFind: Scalable Conditional Inclusion Dependency Discovery in RDF Datasets. SIGMOD Conference 2016: 953-967 - 2015
- [j5]Thorsten Papenbrock, Sebastian Kruse, Jorge-Arnulfo Quiané-Ruiz, Felix Naumann:
Divide & Conquer-based Inclusion Dependency Discovery. Proc. VLDB Endow. 8(7): 774-785 (2015) - [j4]Thorsten Papenbrock, Jens Ehrlich, Jannik Marten, Tommy Neubert, Jan-Peer Rudolph, Martin Schönberg, Jakob Zwiener, Felix Naumann:
Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms. Proc. VLDB Endow. 8(10): 1082-1093 (2015) - [j3]Thorsten Papenbrock, Tanja Bergmann, Moritz Finke, Jakob Zwiener, Felix Naumann:
Data Profiling with Metanome. Proc. VLDB Endow. 8(12): 1860-1863 (2015) - [j2]Thorsten Papenbrock, Arvid Heise, Felix Naumann:
Progressive Duplicate Detection. IEEE Trans. Knowl. Data Eng. 27(5): 1316-1329 (2015) - [c3]Sebastian Kruse, Thorsten Papenbrock, Felix Naumann:
Scaling Out the Discovery of Inclusion Dependencies. BTW 2015: 445-454 - 2014
- [j1]Felix Naumann, Maximilian Jenders, Thorsten Papenbrock:
Ein Datenbankkurs mit 6000 Teilnehmern - Erfahrungen auf der openHPI MOOC Plattform. Inform. Spektrum 37(4): 333-340 (2014) - 2013
- [c2]Benedikt Forchhammer, Thorsten Papenbrock, Thomas Stening, Sven Viehmeier, Uwe Draisbach, Felix Naumann:
Duplicate Detection on GPUs. BTW 2013: 165-184 - 2011
- [c1]Johannes Lorey, Felix Naumann, Benedikt Forchhammer, Andrina Mascher, Peter Retzlaff, Armin Zamani Farahani, Soeren Discher, Cindy Faehnrich, Stefan Lemme, Thorsten Papenbrock, Robert Christoph Peschel, Stephan Richter, Thomas Stening, Sven Viehmeier:
Black swan: augmenting statistics with event data. CIKM 2011: 2517-2520
Coauthor Index
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