Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
A System for Information Extraction from Scientific Texts in Russian. / Bruches, Elena; Mezentseva, Anastasia; Batura, Tatiana.
Communications in Computer and Information Science. Том 1620 Springer Science and Business Media Deutschland GmbH, 2022. стр. 234-245.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - A System for Information Extraction from Scientific Texts in Russian
AU - Bruches, Elena
AU - Mezentseva, Anastasia
AU - Batura, Tatiana
N1 - Acknowledgement: The study was funded by RFBR according to the research project 19-07-01134.
PY - 2022
Y1 - 2022
N2 - In this paper, we present a system for information extraction from scientific texts in the Russian language. The system performs several tasks in an end-to-end manner: term recognition, extraction of relations between terms, and term linking with entities from the knowledge base. These tasks are extremely important for information retrieval, recommendation systems, and classification. The advantage of the implemented methods is that the system does not require a large amount of labeled data, which saves time and effort for data labeling and therefore can be applied in low- and mid-resource settings. The source code is publicly available and can be used for different research purposes.
AB - In this paper, we present a system for information extraction from scientific texts in the Russian language. The system performs several tasks in an end-to-end manner: term recognition, extraction of relations between terms, and term linking with entities from the knowledge base. These tasks are extremely important for information retrieval, recommendation systems, and classification. The advantage of the implemented methods is that the system does not require a large amount of labeled data, which saves time and effort for data labeling and therefore can be applied in low- and mid-resource settings. The source code is publicly available and can be used for different research purposes.
UR - https://www.scopus.com/inward/record.url?eid=2-s2.0-85148026037&partnerID=40&md5=56035fac87e6e3d21b4c232e65dd82c5
UR - https://www.mendeley.com/catalogue/012a8a79-d69c-360b-adfa-5f8a3e7dd541/
U2 - 10.1007/978-3-031-12285-9_15
DO - 10.1007/978-3-031-12285-9_15
M3 - Conference contribution
SN - 978-3-031-12284-2
VL - 1620
SP - 234
EP - 245
BT - Communications in Computer and Information Science
PB - Springer Science and Business Media Deutschland GmbH
ER -
ID: 45615791