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A hybrid approach for anaphora resolution in the Russian language

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

DOI

https://doi.org/10.1109/SSDSE.2017.8071960
Final published version

Anna Kozlova
Alexey Svischev
Olga Gureenkova
Tatiana Batura

Original language	English
Title of host publication	Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	36-40
Number of pages	5
ISBN (Electronic)	9781538615935
ISBN (Print)	9781538615935
DOIs	https://doi.org/10.1109/SSDSE.2017.8071960
Publication status	Published - 18 Oct 2017
Event	2017 Siberian Symposium on Data Science and Engineering - Akademgorodok, Novosibirsk, Russian Federation Duration: 12 Apr 2017 → 13 Apr 2017

Publication series

Name	Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017

Conference

Conference	2017 Siberian Symposium on Data Science and Engineering
Abbreviated title	SSDSE 2017
Country/Territory	Russian Federation
City	Novosibirsk
Period	12.04.2017 → 13.04.2017

OECD FOS+WOS

1.02.ET COMPUTER SCIENCE, INFORMATION SYSTEMS
1.02.EW COMPUTER SCIENCE, SOFTWARE ENGINEERING
2.02.AC AUTOMATION & CONTROL SYSTEMS
2.02 ELECTRICAL ENG, ELECTRONIC ENG

Research areas

anaphora, antecedent, classification, coreference, ensemble learning, machine learning

State classification of scientific and technological information

28.23 Artificial intelligence

ID: 9094337