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Coreference resolution using clusterization. / Bodrova, A.; Grafeeva, N.

Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016. Institute of Electrical and Electronics Engineers Inc., 2016. стр. 9-16.

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

Harvard

Bodrova, A & Grafeeva, N 2016, Coreference resolution using clusterization. в Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016. Institute of Electrical and Electronics Engineers Inc., стр. 9-16, 2016 International FRUCT Conference on Intelligence, Social Media and Web, Saint-Petersburg, Российская Федерация, 28/08/16. https://doi.org/10.1109/FRUCT.2016.7584764

APA

Bodrova, A., & Grafeeva, N. (2016). Coreference resolution using clusterization. в Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016 (стр. 9-16). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FRUCT.2016.7584764

Vancouver

Bodrova A, Grafeeva N. Coreference resolution using clusterization. в Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016. Institute of Electrical and Electronics Engineers Inc. 2016. стр. 9-16 https://doi.org/10.1109/FRUCT.2016.7584764

Author

Bodrova, A. ; Grafeeva, N. / Coreference resolution using clusterization. Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016. Institute of Electrical and Electronics Engineers Inc., 2016. стр. 9-16

BibTeX

@inproceedings{c49d942e8a4d452b9a44e12d69dc2562,
title = "Coreference resolution using clusterization",
abstract = "{\textcopyright} 2016 FRUCT.This work deseribes the experience of ereating a corefarence resolution system for Russian language. Coreference resolution is a key subtask of Information Extraction, and aims to grouping mentions that refer to the same discourse entity. This work was aimed to applying a clusterization algorithm for Russian-language newswire texts. We narrowed the task to Person proper names clusterization. Our approach model included two steps: mention extraction and clusterization. Mention extraction was proceeded by manually-created grammars for Tomita-parser. For mention grouping, we used agglomerative clusterization on entity level with the help of weighted feature vectors. We run our experiments on newswire texts, annotated for factRuEval-2016 competition, organized by Dialogue Evaluation. We compare our results with competitors. As a baseline, we set built-in Tonuta-parser algorithms for name extraction and name clusterization. We got comparable results and outperformed the baseline.",
author = "A. Bodrova and N. Grafeeva",
note = "A. Bodrova and N. Grafeeva, {"}Coreference resolution using clusterization,{"} 2016 International FRUCT Conference on Intelligence, Social Media and Web (ISMW FRUCT), 2016, pp. 1-8, doi: 10.1109/FRUCT.2016.7584764.; 2016 International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016 ; Conference date: 28-08-2016 Through 04-09-2016",
year = "2016",
doi = "10.1109/FRUCT.2016.7584764",
language = "English",
isbn = "978-952-68397-6-9",
pages = "9--16",
booktitle = "Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

RIS

TY - GEN

T1 - Coreference resolution using clusterization

AU - Bodrova, A.

AU - Grafeeva, N.

N1 - A. Bodrova and N. Grafeeva, "Coreference resolution using clusterization," 2016 International FRUCT Conference on Intelligence, Social Media and Web (ISMW FRUCT), 2016, pp. 1-8, doi: 10.1109/FRUCT.2016.7584764.

PY - 2016

Y1 - 2016

N2 - © 2016 FRUCT.This work deseribes the experience of ereating a corefarence resolution system for Russian language. Coreference resolution is a key subtask of Information Extraction, and aims to grouping mentions that refer to the same discourse entity. This work was aimed to applying a clusterization algorithm for Russian-language newswire texts. We narrowed the task to Person proper names clusterization. Our approach model included two steps: mention extraction and clusterization. Mention extraction was proceeded by manually-created grammars for Tomita-parser. For mention grouping, we used agglomerative clusterization on entity level with the help of weighted feature vectors. We run our experiments on newswire texts, annotated for factRuEval-2016 competition, organized by Dialogue Evaluation. We compare our results with competitors. As a baseline, we set built-in Tonuta-parser algorithms for name extraction and name clusterization. We got comparable results and outperformed the baseline.

AB - © 2016 FRUCT.This work deseribes the experience of ereating a corefarence resolution system for Russian language. Coreference resolution is a key subtask of Information Extraction, and aims to grouping mentions that refer to the same discourse entity. This work was aimed to applying a clusterization algorithm for Russian-language newswire texts. We narrowed the task to Person proper names clusterization. Our approach model included two steps: mention extraction and clusterization. Mention extraction was proceeded by manually-created grammars for Tomita-parser. For mention grouping, we used agglomerative clusterization on entity level with the help of weighted feature vectors. We run our experiments on newswire texts, annotated for factRuEval-2016 competition, organized by Dialogue Evaluation. We compare our results with competitors. As a baseline, we set built-in Tonuta-parser algorithms for name extraction and name clusterization. We got comparable results and outperformed the baseline.

UR - https://ieeexplore.ieee.org/document/7584764/authors#authors

U2 - 10.1109/FRUCT.2016.7584764

DO - 10.1109/FRUCT.2016.7584764

M3 - Conference contribution

SN - 978-952-68397-6-9

SP - 9

EP - 16

BT - Proceedings of the International FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 International FRUCT Conference on Intelligence, Social Media and Web

Y2 - 28 August 2016 through 4 September 2016

ER -

ID: 7966426