Using Few-Shot Learning Techniques for Named Entity Recognition and Relation Extraction › Research Explorer

DOI

https://doi.org/10.1109/S.A.I.ence50533.2020.9303192
Final published version

Ivan Bondarenko
Sergey Berezin
Alexey Pauls
Tatiana Batura
Yuliya Rubtsova
Bair Tuchinov

Original language	English
Title of host publication	Proceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020
Place of Publication	Novosibirsk, Russia
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	58-65
Number of pages	8
ISBN (Electronic)	9780738131115
ISBN (Print)	978-0-7381-3112-2
DOIs	https://doi.org/10.1109/S.A.I.ence50533.2020.9303192
Publication status	Published - 14 Nov 2020
Event	2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020 - Virtual, Novosibirsk, Russian Federation Duration: 14 Nov 2020 → 15 Nov 2020

Publication series

Name	Proceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020

Conference

Conference	2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020
Country/Territory	Russian Federation
City	Virtual, Novosibirsk
Period	14.11.2020 → 15.11.2020

OECD FOS+WOS

6.02.OT LINGUISTICS
1.02.EP COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Research areas

few-shot learning, Named entity recognition, relation extraction, transfer learning

ID: 27526694