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Discovering Band Order Dependencies

Li, Pei; Szlichta, Jaroslaw; Böhlen, Michael; Srivastava, Divesh (2020). Discovering Band Order Dependencies. In: 36th IEEE International Conference on Data Engineering, ICDE 2020, Dallas, TX, USA, 20 April 2020 - 24 April 2020. IEEE, 1878-1881.

Abstract

We introduce band ODs to model the semantics of attributes that are monotonically related with small variations without there being an intrinsic violation of semantics. To make band ODs relevant to real-world applications, we make them less strict to hold approximately with some exceptions. Since formulating integrity constraints manually is cumbersome, we study the problem of automatic approximate band OD discovery. We devise an algorithm that determines the optimal solution in polynomial time. We perform a thorough experimental evaluation of our techniques over real-world and synthetic datasets.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Signal Processing
Physical Sciences > Information Systems
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:24 April 2020
Deposited On:01 Mar 2021 08:47
Last Modified:06 Mar 2024 14:34
Publisher:IEEE
OA Status:Green
Publisher DOI:https://doi.org/10.1109/ICDE48307.2020.00193
Other Identification Number:merlin-id:20729
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