| Efficient Discovery of Approximate Dependencies S Kruse, F Naumann Proceedings of the VLDB Endowment 11 (7), 759-772, 2018 | 50 | 2018 |
| Divide & conquer-based inclusion dependency discovery T Papenbrock, S Kruse, JA Quiané-Ruiz, F Naumann Proceedings of the VLDB Endowment 8 (7), 774-785, 2015 | 49 | 2015 |
| Automating Data Exchange in Process Choreographies A Meyer, L Pufahl, K Batoulis, S Kruse, T Lindhauer, T Stoff, D Fahland, ... Advanced Information Systems Engineering, 316-331, 2014 | 45 | 2014 |
| Rheem: Enabling Multi-Platform Task Execution D Agrawal, L Berti-Equille, ML Ba, A Elmagarmid, S Chawla, Z Kaoudi, ... Proceedings of the ACM SIGMOD Conference, 2016 | 33 | 2016 |
| Efficient Denial Constraint Discovery with Hydra T Bleifuß, S Kruse, F Naumann Proceedings of the VLDB Endowment 11 (3), 311-323, 2017 | 31 | 2017 |
| Approximate Discovery of Functional Dependencies for Large Datasets T Bleifuß, S Bülow, J Frohnhofen, J Risch, G Wiese, S Kruse, ... Proceedings of the 25th ACM International on Conference on Information and …, 2016 | 19 | 2016 |
| RHEEM: enabling cross-platform data processing: may the big data be with you! D Agrawal, S Chawla, B Contreras-Rojas, A Elmagarmid, Y Idris, ... Proceedings of the VLDB Endowment 11 (11), 1414-1427, 2018 | 18 | 2018 |
| Fast Approximate Discovery of Inclusion Dependencies S Kruse, T Papenbrock, C Dullweber, M Finke, M Hegner, M Zabel, ... Conference on Database Systems for Business, Technology, and Web, 207-216, 2017 | 17 | 2017 |
| Data Anamnesis: Admitting Raw Data into an Organization S Kruse, T Papenbrock, H Harmouch, F Naumann IEEE Data Engineering Bulletin 39 (2), 8-20, 2016 | 17 | 2016 |
| Scaling Out the Discovery of Inclusion Dependencies S Kruse, T Papenbrock, F Naumann Datenbanksysteme für Business, Technology und Web (BTW) 16, 2015 | 16 | 2015 |
| Estimating Data Integration and Cleaning Effort S Kruse, P Papotti, F Naumann International Conference on Extending Database Technology (EDBT) 18, 61-72, 2015 | 15 | 2015 |
| RDFind: Scalable Conditional Inclusion Dependency Discovery in RDF Datasets S Kruse, A Jentzsch, T Papenbrock, Z Kaoudi, JA Quiané-Ruiz, ... ACM SIGMOD Conference, 2016 | 12 | 2016 |
| Data Perspective in Process Choreographies: Modeling and Execution A Meyer, L Pufahl, K Batoulis, S Kruse, T Lindhauer, T Stoff, D Fahland, ... Tech. Rep. BPM-13-29, BPMcenter. org, 2013 | 11 | 2013 |
| DynFD: Functional Dependency Discovery in Dynamic Datasets. P Schirmer, T Papenbrock, S Kruse, F Naumann, D Hempfing, T Mayer, ... EDBT, 253-264, 2019 | 9 | 2019 |
| RHEEMix in the Data Jungle--A Cross-Platform Query Optimizer-- S Kruse, Z Kaoudi, JA Quiané-Ruiz, S Chawla, F Naumann, B Contreras arXiv preprint arXiv:1805.03533, 2018 | 7 | 2018 |
| Metacrate: Organize and Analyze Millions of Data Profiles S Kruse, D Hahn, M Walter, F Naumann ACM Conference on Information and Knowledge Management, 2483-2486, 2017 | 7 | 2017 |
| Systems and methods for data integration P Papotti, F Naumann, S Kruse US Patent 10,528,532, 2020 | 5 | 2020 |
| Optimizing Cross-Platform Data Movement S Kruse, Z Kaoudi, JA Quiané-Ruiz, S Chawla, F Naumann, ... 2019 IEEE 35th International Conference on Data Engineering (ICDE), 1642-1645, 2019 | 2 | 2019 |
| RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems S Kruse, Z Kaoudi, B Contreras-Rojas, S Chawla, F Naumann, ... VLDB JOURNAL, 2020 | 1 | 2020 |
| Building your Cross-Platform Application with RHEEM S Chawla, B Contreras-Rojas, Z Kaoudi, S Kruse, JA Quiané-Ruiz arXiv preprint arXiv:1805.11723, 2018 | 1 | 2018 |
Felix NaumannHasso Plattner Institute, University of PotsdamVerifierad e-postadress på hpi.de
