Publications

  1. 2020

    1. Gazzarri, L., & Herschel, M. (2020). Boosting Blocking Performance in Entity Resolution Pipelines: Comparison Cleaning using Bloom Filters. Proceedings of the 23nd International Conference on Extending Database Technology, EDBT 2020, Copenhagen, Denmark, March 30 - April 02, 2020, 419--422.
    2. Oppold, S., & Herschel, M. (2020). A System Framework for Personalized and Transparent Data-Driven Decisions. Proceedings of the  International Conference on Advanced Information Systems Engineering (CAiSE).
    3. Diestelkämper, R., & Herschel, M. (2020). Tracing nested data with structural provenance for big data analytics. Proceedings of the 23nd International Conference on Extending Database Technology, EDBT 2020, Copenhagen, Denmark, March 30 - April 02, 2020, 253--264. https://doi.org/10.5441/002/edbt.2020.23
  2. 2019

    1. Gazzarri, L., & Herschel, M. (2019). Towards task-based parallelization for entity resolution. SICS Software-Intensive Cyber-Physical Systems. https://doi.org/10.1007/s00450-019-00409-6
    2. Oppold, S., & Herschel, M. (2019). LuPe: A System for Personalized and Transparent Data-driven Decisions. In W. Zhu, D. Tao, X. Cheng, P. Cui, E. A. Rundensteiner, D. Carmel, Q. He, & J. X. Yu (Eds.), CIKM (pp. 2905–2908). ACM. http://dblp.uni-trier.de/db/conf/cikm/cikm2019.html#OppoldH19
    3. Diestelkämper, R., Glavic, B., Herschel, M., & Lee, S. (2019). Query-based Why-not Explanations for Nested Data. 11th International Workshop on Theory and Practice of Provenance (TaPP 2019). https://www.usenix.org/conference/tapp2019/presentation/diestelkamper
    4. Diestelkämper, R., & Herschel, M. (2019). Capturing and Querying Structural Provenance in Spark with Pebble. In P. A. Boncz, S. Manegold, A. Ailamaki, A. Deshpande, & T. Kraska (Eds.), SIGMOD Conference (pp. 1893–1896). ACM. http://dblp.uni-trier.de/db/conf/sigmod/sigmod2019.html#DiestelkamperH19
  3. 2018

    1. Oppold, S., & Herschel, M. (2018). Provenance for Entity Resolution. In K. Belhajjame, A. Gehani, & P. Alper (Eds.), IPAW (Vol. 11017, pp. 226–230). Springer. http://dblp.uni-trier.de/db/conf/ipaw/ipaw2018.html#OppoldH18
  4. 2017

    1. Diestelkämper, R., Herschel, M., & Jadhav, P. (2017). Provenance in DISC Systems: Reducing Space Overhead at Runtime. Proceedings of the USENIX Conference on Theory and Practice of Provenance (TAPP), 1–13. https://dl.acm.org/doi/abs/10.5555/3183865.3183883
  5. 2016

    1. Bidoit, N., Herschel, M., & Tzompanaki, K. (2016). Refining SQL Queries based on Why-Not Polynomials. 8th USENIX Workshop on the Theory and Practice of Provenance, TaPP 2016, Washington, D.C., USA, June 8-9, 2016. https://www.usenix.org/conference/tapp16/workshop-program/presentation/bidoit
  6. 2015

    1. Herschel, M. (2015). A hybrid approach to answering why-not questions on relational query results. Journal of Data and Information Quality, 5(3), 10:1-10:29. http://dblp.uni-trier.de/db/journals/jdiq/jdiq5.html#Herschel15
    2. Bidoit, N., Herschel, M., & Tzompanaki, A. (2015a). Efficient computation of polynomial explanations of why-not questions. In J. Bailey, A. Moffat, C. C. Aggarwal, M. de Rijke, R. Kumar, V. Murdock, T. K. Sellis, & J. X. Yu (Eds.), CIKM’15 (pp. 713–722). Association for Computing Machinery. https://doi.org/10.1145/2806416.2806426
    3. Bidoit, N., Herschel, M., & Tzompanaki, K. (2015b). EFQ: why-not answer polynomials in action. Proceedings of the VLDB Endowment (PVLDB), 8(12), 1980–1983. http://dblp.uni-trier.de/db/journals/pvldb/pvldb8.html#BidoitHT15
    4. Bidoit, N., Herschel, M., & Tzompanaki, K. (2015c). Immutably answering Why-Not questions for equivalent conjunctive queries. Ingénierie Des Systèmes d’information, 20(5), 27–52. https://doi.org/10.3166/isi.20.5.27-52
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