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Development of Kazakh Named Entity Recognition Models. / Akhmed-Zaki, Darkhan; Mansurova, Madina; Barakhnin, Vladimir и др.

Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings. ред. / Ngoc Thanh Nguyen; Ngoc Thanh Nguyen; Bao Hung Hoang; Cong Phap Huynh; Dosam Hwang; Bogdan Trawinski; Gottfried Vossen. Springer Science and Business Media Deutschland GmbH, 2020. стр. 697-708 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12496 LNAI).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Akhmed-Zaki, D, Mansurova, M, Barakhnin, V, Kubis, M, Chikibayeva, D & Kyrgyzbayeva, M 2020, Development of Kazakh Named Entity Recognition Models. в NT Nguyen, NT Nguyen, BH Hoang, CP Huynh, D Hwang, B Trawinski & G Vossen (ред.), Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 12496 LNAI, Springer Science and Business Media Deutschland GmbH, стр. 697-708, 12th International Conference on Computational Collective Intelligence, ICCCI 2020, Da Nang, Вьетнам, 30.11.2020. https://doi.org/10.1007/978-3-030-63007-2_54

APA

Akhmed-Zaki, D., Mansurova, M., Barakhnin, V., Kubis, M., Chikibayeva, D., & Kyrgyzbayeva, M. (2020). Development of Kazakh Named Entity Recognition Models. в N. T. Nguyen, N. T. Nguyen, B. H. Hoang, C. P. Huynh, D. Hwang, B. Trawinski, & G. Vossen (Ред.), Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings (стр. 697-708). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12496 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-63007-2_54

Vancouver

Akhmed-Zaki D, Mansurova M, Barakhnin V, Kubis M, Chikibayeva D, Kyrgyzbayeva M. Development of Kazakh Named Entity Recognition Models. в Nguyen NT, Nguyen NT, Hoang BH, Huynh CP, Hwang D, Trawinski B, Vossen G, Редакторы, Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. стр. 697-708. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-63007-2_54

Author

Akhmed-Zaki, Darkhan ; Mansurova, Madina ; Barakhnin, Vladimir и др. / Development of Kazakh Named Entity Recognition Models. Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings. Редактор / Ngoc Thanh Nguyen ; Ngoc Thanh Nguyen ; Bao Hung Hoang ; Cong Phap Huynh ; Dosam Hwang ; Bogdan Trawinski ; Gottfried Vossen. Springer Science and Business Media Deutschland GmbH, 2020. стр. 697-708 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{ff4eb4647fa24c728c798166b514f06e,
title = "Development of Kazakh Named Entity Recognition Models",
abstract = "Named entity recognition is one of the important tasks in natural language processing. Its practical application can be found in various areas such as speech recognition, information retrieval, filtering, etc. Nowadays there are a variety of available methods for implementing named entity recognition. In this work we experimented with three models and compared the performances of machine learning based models and probabilistic sequence modeling method on the task of Kazakh language named entity recognition. We considered three models based on BERT, Bi-LSTM and CRF baseline. In the future these models can be parts of an ensemble learning system for name entity recognition in order to achieve better performance results.",
keywords = "BERT, Bi-LSTM, Conditional random fields, Named entity recognition",
author = "Darkhan Akhmed-Zaki and Madina Mansurova and Vladimir Barakhnin and Marek Kubis and Darya Chikibayeva and Marzhan Kyrgyzbayeva",
note = "Funding Information: Acknowledgements. This work was supported in part under grants of Foundation of Ministry of Education and Science of the Republic of Kazakhstan AP05132933 – “Development of a system for knowledge extraction from heterogeneous data sources to improve the quality of decision-making” (2018–2020) and O.0856 BR05236340 – «Creation of high-performance intelligent technologies for analysis and decision making for the “logistics-agglomeration”; system in the framework of the digital economy of the Republic of Kazakhstan» (2018–2020). Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 12th International Conference on Computational Collective Intelligence, ICCCI 2020 ; Conference date: 30-11-2020 Through 03-12-2020",
year = "2020",
doi = "10.1007/978-3-030-63007-2_54",
language = "English",
isbn = "9783030630065",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "697--708",
editor = "Nguyen, {Ngoc Thanh} and Nguyen, {Ngoc Thanh} and Hoang, {Bao Hung} and Huynh, {Cong Phap} and Dosam Hwang and Bogdan Trawinski and Gottfried Vossen",
booktitle = "Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings",
address = "Germany",

}

RIS

TY - GEN

T1 - Development of Kazakh Named Entity Recognition Models

AU - Akhmed-Zaki, Darkhan

AU - Mansurova, Madina

AU - Barakhnin, Vladimir

AU - Kubis, Marek

AU - Chikibayeva, Darya

AU - Kyrgyzbayeva, Marzhan

N1 - Funding Information: Acknowledgements. This work was supported in part under grants of Foundation of Ministry of Education and Science of the Republic of Kazakhstan AP05132933 – “Development of a system for knowledge extraction from heterogeneous data sources to improve the quality of decision-making” (2018–2020) and O.0856 BR05236340 – «Creation of high-performance intelligent technologies for analysis and decision making for the “logistics-agglomeration”; system in the framework of the digital economy of the Republic of Kazakhstan» (2018–2020). Publisher Copyright: © 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - Named entity recognition is one of the important tasks in natural language processing. Its practical application can be found in various areas such as speech recognition, information retrieval, filtering, etc. Nowadays there are a variety of available methods for implementing named entity recognition. In this work we experimented with three models and compared the performances of machine learning based models and probabilistic sequence modeling method on the task of Kazakh language named entity recognition. We considered three models based on BERT, Bi-LSTM and CRF baseline. In the future these models can be parts of an ensemble learning system for name entity recognition in order to achieve better performance results.

AB - Named entity recognition is one of the important tasks in natural language processing. Its practical application can be found in various areas such as speech recognition, information retrieval, filtering, etc. Nowadays there are a variety of available methods for implementing named entity recognition. In this work we experimented with three models and compared the performances of machine learning based models and probabilistic sequence modeling method on the task of Kazakh language named entity recognition. We considered three models based on BERT, Bi-LSTM and CRF baseline. In the future these models can be parts of an ensemble learning system for name entity recognition in order to achieve better performance results.

KW - BERT

KW - Bi-LSTM

KW - Conditional random fields

KW - Named entity recognition

UR - http://www.scopus.com/inward/record.url?scp=85097528781&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-63007-2_54

DO - 10.1007/978-3-030-63007-2_54

M3 - Conference contribution

AN - SCOPUS:85097528781

SN - 9783030630065

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 697

EP - 708

BT - Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings

A2 - Nguyen, Ngoc Thanh

A2 - Nguyen, Ngoc Thanh

A2 - Hoang, Bao Hung

A2 - Huynh, Cong Phap

A2 - Hwang, Dosam

A2 - Trawinski, Bogdan

A2 - Vossen, Gottfried

PB - Springer Science and Business Media Deutschland GmbH

T2 - 12th International Conference on Computational Collective Intelligence, ICCCI 2020

Y2 - 30 November 2020 through 3 December 2020

ER -

ID: 27081678