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pro vyhledávání: '"Joeri Rammelaere"'
Autor:
Joeri Rammelaere, Floris Geerts
Publikováno v:
IEEE transactions on knowledge and data engineering
Methods for cleaning dirty data typically employ additional information about the data such as user-provided constraints specifying when data is dirty, e.g., domain restrictions, illegal value combinations, or logical rules. However, real-world scena
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ccc923c8f91d357360582bdf365a13b
https://hdl.handle.net/10067/1706200151162165141
https://hdl.handle.net/10067/1706200151162165141
Autor:
Joeri Rammelaere, Floris Geerts
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109271
ECML/PKDD (2)
ECML/PKDD (2)
Many techniques for cleaning dirty data are based on enforcing some set of integrity constraints. Conditional functional dependencies (CFDs) are a combination of traditional Functional dependencies (FDs) and association rules, and are widely used as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d8902ee8cd89c6d7349afb0a43fef3c
https://doi.org/10.1007/978-3-030-10928-8_33
https://doi.org/10.1007/978-3-030-10928-8_33
Autor:
Joeri Rammelaere, Floris Geerts
Publikováno v:
Proceedings of the VLDB Endowment
Many popular data cleaning approaches are rule-based: Constraints are formulated in a logical framework, and data is considered dirty if constraints are violated. These constraints are often discovered from data, but to ascertain their validity, user
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0679d33cb43b660a6ddca418f651af35
https://hdl.handle.net/10067/1553100151162165141
https://hdl.handle.net/10067/1553100151162165141
Publikováno v:
IEEE 33rd International Conference on Data Engineering (ICDE), APR 19-22, 2017, San Diego, CA
2017 IEEE 33RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2017)
ICDE
2017 IEEE 33RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2017)
ICDE
Methods for cleaning dirty data typically rely on additional information about the data, such as user-specified constraints that specify when a database is dirty. These constraints often involve domain restrictions and illegal value combinations. Tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f34297b172add01068c5094477297a9
https://hdl.handle.net/10067/1443290151162165141
https://hdl.handle.net/10067/1443290151162165141
Publikováno v:
University of Antwerp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2d7155bd49f769f0869bf6aee53b4661
https://hdl.handle.net/10067/1539710151162165141
https://hdl.handle.net/10067/1539710151162165141