Foreign Key Constraint Identification in Relational Databases

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F17%3A00312699" target="_blank" >RIV/68407700:21240/17:00312699 - isvavai.cz</a>

Result on the web

<a href="http://ceur-ws.org/Vol-1885/106.pdf" target="_blank" >http://ceur-ws.org/Vol-1885/106.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Foreign Key Constraint Identification in Relational Databases

Original language description

For relational learning, it is important to know the relationships between the tables. In relational databases, the relationships can be described with foreign key constraints. However, the foreign keys may not be explicitly specified. In this article, we present how to automatically and quickly identify primary & foreign key constraints from metadata about the data. Our method was evaluated on 72 databases and has F-measure of 0.87 for foreign key constraint identification. The proposed method significantly outperforms in runtime related methods reported in the literature and is database vendor agnostic.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

ITAT 2017: Information Technologies – Applications and Theory

ISBN

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ISSN

1613-0073

e-ISSN

1613-0073

Number of pages

6

Pages from-to

106-111

Publisher name

CEUR Workshop Proceedings

Place of publication

Aachen

Event location

Martinské hole, Malá Fatra

Event date

Sep 22, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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