License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICDT.2023.22
URN: urn:nbn:de:0030-drops-177644
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/17764/
Go to the corresponding LIPIcs Volume Portal

Gilad, Amir ; Imber, Aviram ; Kimelfeld, Benny

The Consistency of Probabilistic Databases with Independent Cells

pdf-format:
LIPIcs-ICDT-2023-22.pdf (0.8 MB)

Abstract

A probabilistic database with attribute-level uncertainty consists of relations where cells of some attributes may hold probability distributions rather than deterministic content. Such databases arise, implicitly or explicitly, in the context of noisy operations such as missing data imputation, where we automatically fill in missing values, column prediction, where we predict unknown attributes, and database cleaning (and repairing), where we replace the original values due to detected errors or violation of integrity constraints. We study the computational complexity of problems that regard the selection of cell values in the presence of integrity constraints. More precisely, we focus on functional dependencies and study three problems: (1) deciding whether the constraints can be satisfied by any choice of values, (2) finding a most probable such choice, and (3) calculating the probability of satisfying the constraints. The data complexity of these problems is determined by the combination of the set of functional dependencies and the collection of uncertain attributes. We give full classifications into tractable and intractable complexities for several classes of constraints, including a single dependency, matching constraints, and unary functional dependencies.

BibTeX - Entry

@InProceedings{gilad_et_al:LIPIcs.ICDT.2023.22,
  author =	{Gilad, Amir and Imber, Aviram and Kimelfeld, Benny},
  title =	{{The Consistency of Probabilistic Databases with Independent Cells}},
  booktitle =	{26th International Conference on Database Theory (ICDT 2023)},
  pages =	{22:1--22:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-270-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{255},
  editor =	{Geerts, Floris and Vandevoort, Brecht},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/17764},
  URN =		{urn:nbn:de:0030-drops-177644},
  doi =		{10.4230/LIPIcs.ICDT.2023.22},
  annote =	{Keywords: Probabilistic databases, attribute-level uncertainty, functional dependencies, most probable database}
}

Keywords: Probabilistic databases, attribute-level uncertainty, functional dependencies, most probable database
Collection: 26th International Conference on Database Theory (ICDT 2023)
Issue Date: 2023
Date of publication: 17.03.2023

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI