Year: 2024
Type: conference-paper
Abstract: Pioneering data profiling systems — such as Metanome and OpenClean — brought public attention to science-intensive data profiling. This type of profiling aims to extract complex patterns, such as data dependencies, data constraints, association rules, and others. However, these tools are research prototypes rather than production-ready systems.
Authors: George Chernishev, Michael Polyntsov, Anton Chizhov, Kirill Stupakov, Ilya Shchuckin, Alexander Smirnov, Maxim Strutovsky, Alexey Shlyonskikh, Mikhail Firsov, Stepan Manannikov, Nikita Bobrov, Daniil Goncharov, Ilia Barutkin, Vadim Yakshigulov, Vladislav Shalnev, Kirill Muraviev, Anna Rakhmukova, Dmitriy Shcheka, Anton Chernikov, Yakov Kuzin, Michael Sinelnikov, Grigorii Abrosimov, Dmitriy Popov, Artem Demchenko, Sergey Belokonny, Liana-Iuliia Soloveva, Yaroslav Kurbatov, Mikhail Vyrodov, Arthur Saliou, Eduard Gaisin, Kirill Smirnov
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4411624799