most citedFast Discovery of Inclusion Dependencies with Desbordante

7 citations · 16 across the 7 of their papers we have counts for

collaborators

8 papers

cs.DB2026

FastGFDs: Efficient Validation of Graph Functional Dependencies with Desbordante

Anton Chernikov, Yurii Litvinov, Kirill Smirnov +1

Graph functional dependencies (GFD) are a recently-developed concept aimed at capturing both topological structures in graphs and functional dependencies between attributes. The pr…

cs.DB20267 cited

Fast Discovery of Inclusion Dependencies with Desbordante

Alexander Smirnov, Anton Chizhov, Ilya Shchuckin +2

Inclusion dependency is a relation between attributes of tables that indicates possible Primary Key-Foreign Key references. Automatic discovery of inclusion dependencies is a relev…

cs.DB20262 cited

Extending Desbordante with Probabilistic Functional Dependency Discovery Support

Ilia Barutkin, Maxim Fofanov, Sergey Belokonny +2

Data profiling aims to extract complex patterns from data for further analysis and use that data in domains such as data cleaning, data deduplication, anomaly detection, and many m…

cs.DB20264 cited

Order in Desbordante: Techniques for Efficient Implementation of Order Dependency Discovery Algorithms

Yakov Kuzin, Dmitriy Shcheka, Michael Polyntsov +3

Science-intensive data profiling focuses on discovery and validation of various patterns in datasets. This study considers discovery of one such pattern - order dependency (OD). Si…

cs.DB20263 cited

Lightning Fast Matching Dependency Discovery with Desbordante

Alexey Shlyonskikh, Michael Sinelnikov, Daniil Nikolaev +2

Matching dependency is a generalization of the functional dependency concept, which allows users to apply custom similarity functions for matching individual attributes. Matching d…

cs.DB2026

Efficient Discovery of Conditional Dependencies with Desbordante

Ivan Kozhukov, Dmitry Fedoseev, Maksim Emelyanov +4

Conditional functional dependencies (CFDs) are functional dependencies with a restricted scope: they specify the context in which a dependency holds and are useful for data-quality…