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ParaPhraser : Russian paraphrase corpus and shared task. / Pivovarova, Lidia; Pronoza, Ekaterina; Yagunova, Elena; Pronoza, Anton.

Artificial Intelligence and Natural Language - 6th Conference, AINL 2017, Revised Selected Papers. Том 789 CCIS Springer, Cham. ред. Springer Nature, 2018. стр. 211-225 (Communications in Computer and Information Science; Том 789).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование

Harvard

Pivovarova, L, Pronoza, E, Yagunova, E & Pronoza, A 2018, ParaPhraser: Russian paraphrase corpus and shared task. в Artificial Intelligence and Natural Language - 6th Conference, AINL 2017, Revised Selected Papers. CCIS Springer, Cham изд., Том. 789, Communications in Computer and Information Science, Том. 789, Springer Nature, стр. 211-225, 6th Conference on Artificial Intelligence and Natural Language, AINL 2017, St. Petersburg, Российская Федерация, 19/09/17. https://doi.org/10.1007/978-3-319-71746-3_18, https://doi.org/10.1007/978-3-319-71746-3_18

APA

Pivovarova, L., Pronoza, E., Yagunova, E., & Pronoza, A. (2018). ParaPhraser: Russian paraphrase corpus and shared task. в Artificial Intelligence and Natural Language - 6th Conference, AINL 2017, Revised Selected Papers (CCIS Springer, Cham ред., Том 789, стр. 211-225). (Communications in Computer and Information Science; Том 789). Springer Nature. https://doi.org/10.1007/978-3-319-71746-3_18, https://doi.org/10.1007/978-3-319-71746-3_18

Vancouver

Pivovarova L, Pronoza E, Yagunova E, Pronoza A. ParaPhraser: Russian paraphrase corpus and shared task. в Artificial Intelligence and Natural Language - 6th Conference, AINL 2017, Revised Selected Papers. CCIS Springer, Cham ред. Том 789. Springer Nature. 2018. стр. 211-225. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-319-71746-3_18, https://doi.org/10.1007/978-3-319-71746-3_18

Author

Pivovarova, Lidia ; Pronoza, Ekaterina ; Yagunova, Elena ; Pronoza, Anton. / ParaPhraser : Russian paraphrase corpus and shared task. Artificial Intelligence and Natural Language - 6th Conference, AINL 2017, Revised Selected Papers. Том 789 CCIS Springer, Cham. ред. Springer Nature, 2018. стр. 211-225 (Communications in Computer and Information Science).

BibTeX

@inproceedings{22331ac669f64629b565d8493ae8dee4,
title = "ParaPhraser: Russian paraphrase corpus and shared task",
abstract = "The paper describes the results of the First Russian Paraphrase Detection Shared Task held in St.-Petersburg, Russia, in October 2016. Research in the area of paraphrase extraction, detection and generation has been successfully developing for a long time while there has been only a recent surge of interest towards the problem in the Russian community of computational linguistics. We try to overcome this gap by introducing the project ParaPhraser.ru dedicated to the collection of Russian paraphrase corpus and organizing a Paraphrase Detection Shared Task, which uses the corpus as the training data. The participants of the task applied a wide variety of techniques to the problem of paraphrase detection, from rule-based approaches to deep learning, and results of the task reflect the following tendencies: the best scores are obtained by the strategy of using traditional classifiers combined with fine-grained linguistic features, however, complex neural networks, shallow methods and purely technical methods also demonstrate competitive results.",
keywords = "корпус парафраз, распознавание парафраз, русские парафразы, дорожка по распознаванию парафраз, Paraphrase corpus, Paraphrase detection, Russian paraphrase, Shared task",
author = "Lidia Pivovarova and Ekaterina Pronoza and Elena Yagunova and Anton Pronoza",
note = "Pivovarova L., Pronoza E., Yagunova E., Pronoza A. (2018) ParaPhraser: Russian Paraphrase Corpus and Shared Task. In: Filchenkov A., Pivovarova L., {\v Z}i{\v z}ka J. (eds) Artificial Intelligence and Natural Language. AINL 2017. Communications in Computer and Information Science, vol 789. Springer, Cham; 6th Conference on Artificial Intelligence and Natural Language, AINL 2017 ; Conference date: 19-09-2017 Through 22-09-2017",
year = "2018",
doi = "https://doi.org/10.1007/978-3-319-71746-3_18",
language = "English",
isbn = "9783319717456",
volume = "789",
series = "Communications in Computer and Information Science",
publisher = "Springer Nature",
pages = "211--225",
booktitle = "Artificial Intelligence and Natural Language - 6th Conference, AINL 2017, Revised Selected Papers",
address = "Germany",
edition = "CCIS Springer, Cham",

}

RIS

TY - GEN

T1 - ParaPhraser

T2 - 6th Conference on Artificial Intelligence and Natural Language, AINL 2017

AU - Pivovarova, Lidia

AU - Pronoza, Ekaterina

AU - Yagunova, Elena

AU - Pronoza, Anton

N1 - Pivovarova L., Pronoza E., Yagunova E., Pronoza A. (2018) ParaPhraser: Russian Paraphrase Corpus and Shared Task. In: Filchenkov A., Pivovarova L., Žižka J. (eds) Artificial Intelligence and Natural Language. AINL 2017. Communications in Computer and Information Science, vol 789. Springer, Cham

PY - 2018

Y1 - 2018

N2 - The paper describes the results of the First Russian Paraphrase Detection Shared Task held in St.-Petersburg, Russia, in October 2016. Research in the area of paraphrase extraction, detection and generation has been successfully developing for a long time while there has been only a recent surge of interest towards the problem in the Russian community of computational linguistics. We try to overcome this gap by introducing the project ParaPhraser.ru dedicated to the collection of Russian paraphrase corpus and organizing a Paraphrase Detection Shared Task, which uses the corpus as the training data. The participants of the task applied a wide variety of techniques to the problem of paraphrase detection, from rule-based approaches to deep learning, and results of the task reflect the following tendencies: the best scores are obtained by the strategy of using traditional classifiers combined with fine-grained linguistic features, however, complex neural networks, shallow methods and purely technical methods also demonstrate competitive results.

AB - The paper describes the results of the First Russian Paraphrase Detection Shared Task held in St.-Petersburg, Russia, in October 2016. Research in the area of paraphrase extraction, detection and generation has been successfully developing for a long time while there has been only a recent surge of interest towards the problem in the Russian community of computational linguistics. We try to overcome this gap by introducing the project ParaPhraser.ru dedicated to the collection of Russian paraphrase corpus and organizing a Paraphrase Detection Shared Task, which uses the corpus as the training data. The participants of the task applied a wide variety of techniques to the problem of paraphrase detection, from rule-based approaches to deep learning, and results of the task reflect the following tendencies: the best scores are obtained by the strategy of using traditional classifiers combined with fine-grained linguistic features, however, complex neural networks, shallow methods and purely technical methods also demonstrate competitive results.

KW - корпус парафраз

KW - распознавание парафраз

KW - русские парафразы

KW - дорожка по распознаванию парафраз

KW - Paraphrase corpus

KW - Paraphrase detection

KW - Russian paraphrase

KW - Shared task

UR - http://www.scopus.com/inward/record.url?scp=85037545952&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/paraphraser-russian-paraphrase-corpus-shared-task

U2 - https://doi.org/10.1007/978-3-319-71746-3_18

DO - https://doi.org/10.1007/978-3-319-71746-3_18

M3 - Conference contribution

AN - SCOPUS:85037545952

SN - 9783319717456

VL - 789

T3 - Communications in Computer and Information Science

SP - 211

EP - 225

BT - Artificial Intelligence and Natural Language - 6th Conference, AINL 2017, Revised Selected Papers

PB - Springer Nature

Y2 - 19 September 2017 through 22 September 2017

ER -

ID: 11888226