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Stefan Hagedorn
Stefan Hagedorn
PhD Student, TU Ilmenau
Bestätigte E-Mail-Adresse bei tu-ilmenau.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
The STARK framework for spatio-temporal data analytics on spark
S Hagedorn, P Gotze, KU Sattler
Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017
742017
Big Spatial Data Processing Frameworks: Feature and Performance Evaluation.
S Hagedorn, P Götze, KU Sattler
EDBT, 490-493, 2017
302017
Efficient spatio-temporal event processing with STARK
S Hagedorn
Deutsche Nationalbibliothek, 2017
252017
Putting pandas in a box
S Hagedorn, S Kläbe, KU Sattler
CIDR, 2021
242021
A gray-box modeling methodology for runtime prediction of apache spark jobs
H Al-Sayeh, S Hagedorn, KU Sattler
Distributed and Parallel Databases 38, 819-839, 2020
142020
Piglet: interactive and platform transparent analytics for rdf & dynamic data
S Hagedorn, KU Sattler
Proceedings of the 25th International Conference Companion on World Wide Web …, 2016
132016
Complex event processing on linked stream data
O Saleh, S Hagedorn, KU Sattler
Datenbank-Spektrum 15 (2), 119-129, 2015
132015
Sparqling pig-processing linked data with pig latin
S Hagedorn, K Hose, KU Sattler
Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015
82015
Resource Planning for SPARQL Query Execution on Data Sharing Platforms.
S Hagedorn, K Hose, KU Sattler, J Umbrich
COLD 1264, 2014
82014
Efficient parallel processing of analytical queries on linked data
S Hagedorn, KU Sattler
On the Move to Meaningful Internet Systems: OTM 2013 Conferences …, 2013
82013
Applying machine learning models to scalable dataframes with grizzly
S Kläbe, S Hagedorn
BTW 2021, 2021
72021
Discovery querying in linked open data
S Hagedorn, KU Sattler
Proceedings of the Joint EDBT/ICDT 2013 Workshops, 38-44, 2013
72013
Stream processing platforms for analyzing big dynamic data
S Hagedorn, P Götze, O Saleh, KU Sattler
it-Information Technology 58 (4), 195-205, 2016
62016
When sweet and cute isn't enough anymore: Solving scalability issues in Python Pandas with Grizzly.
S Hagedorn
CIDR, 2020
52020
Cost-based sharing and recycling of (intermediate) results in dataflow programs
S Hagedorn, KU Sattler
Advances in Databases and Information Systems: 22nd European Conference …, 2018
42018
LODHub—A platform for sharing and integrated processing of linked open data
S Hagedorn, KU Sattler
2014 IEEE 30th International Conference on Data Engineering Workshops, 260-262, 2014
42014
Accelerating Python UDFs in Vectorized Query Execution
S Kläbe, R DeSantis, S Hagedorn, KU Sattler
12th Conference on Innovative Data Systems Research, CIDR, 2022
32022
Processing large raster and vector data in apache spark
S Hagedorn, O Birli, KU Sattler
BTW 2019, 2019
32019
Refining imprecise spatio-temporal events: a network-based approach
A Spitz, J Geiß, M Gertz, S Hagedorn, KU Sattler
Proceedings of the 10th Workshop on Geographic Information Retrieval, 1-10, 2016
32016
A Framework for Scalable Correlation of Spatio-temporal Event Data
S Hagedorn, KU Sattler, M Gertz
Data Science: 30th British International Conference on Databases, BICOD 2015 …, 2015
32015
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