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Effective and Complete Discovery of Order Dependencies via Set-based Axiomatization.

, , , , and . Proc. VLDB Endow., 10 (7): 721-732 (2017)

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iORDER: Mining Implicit Domain Orders., , , , , , and . ICDE, page 3623-3626. IEEE, (2023)BLUTune: Query-informed Multi-stage IBM Db2 Tuning via ML., , , , , , and . CIKM, page 3162-3171. ACM, (2022)Relaxation as a Platform for Cooperative Answering., , and . J. Intell. Inf. Syst., 1 (3/4): 293-321 (1992)A Framework for Intensional Query Optimization., and . DDLP, volume 295 of GMD-Studien, page 57-68. GMD, Sankt Augustin, Germany, (1996)Maximal Vector Computation in Large Data Sets., , and . VLDB, page 229-240. ACM, (2005)Interactive Visualization of Big Data., , , and . BDAS, volume 613 of Communications in Computer and Information Science, page 3-22. Springer, (2016)Bring Order to Data., , , , , and . AMW, volume 2369 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)Query Planning for Evaluating SPARQL Property Paths., , and . AMW, volume 1644 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)Relational Implementation of Multi-dimensional Indexes for Time Series., and . AMW, volume 619 of CEUR Workshop Proceedings, CEUR-WS.org, (2010)Erratum for Discovering Order Dependencies through Order Compatibility (EDBT 2019)., , , , and . EDBT, page 659-663. OpenProceedings.org, (2020)