Standard

Construction of paraphrase graphs as a means of news clusters extraction. / Yagunova, Elena; Pronoza, Ekaterina; Kochetkova, Nataliya.

в: Computacion y Sistemas, Том 22, № 4, 2018, стр. 1329-1336.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Yagunova, E, Pronoza, E & Kochetkova, N 2018, 'Construction of paraphrase graphs as a means of news clusters extraction', Computacion y Sistemas, Том. 22, № 4, стр. 1329-1336. https://doi.org/10.13053/CyS-22-4-3065

APA

Yagunova, E., Pronoza, E., & Kochetkova, N. (2018). Construction of paraphrase graphs as a means of news clusters extraction. Computacion y Sistemas, 22(4), 1329-1336. https://doi.org/10.13053/CyS-22-4-3065

Vancouver

Yagunova E, Pronoza E, Kochetkova N. Construction of paraphrase graphs as a means of news clusters extraction. Computacion y Sistemas. 2018;22(4):1329-1336. https://doi.org/10.13053/CyS-22-4-3065

Author

Yagunova, Elena ; Pronoza, Ekaterina ; Kochetkova, Nataliya. / Construction of paraphrase graphs as a means of news clusters extraction. в: Computacion y Sistemas. 2018 ; Том 22, № 4. стр. 1329-1336.

BibTeX

@article{48d0ff66a9d941feac09c9ebb57a4199,
title = "Construction of paraphrase graphs as a means of news clusters extraction",
abstract = "In this paper, we construct paraphrase graphs for news text collections (clusters). Our aims are, first, to prove that paraphrase graph construction method can be used for news clusters identification and, second, to analyze and compare stylistically different news collections. Our news collections include dynamic, static and combined (dynamic and static) texts. Their respective paraphrase graphs reflect their main characteristics. We also automatically extract the most informationally important linked fragments of news texts, and these fragments characterize news texts as either informative, conveying some information, or publicistic ones, trying to affect the readers emotionally.",
keywords = "Linked text segments, News cluster, Paraphrase extraction, Paraphrase graph, Text analysis",
author = "Elena Yagunova and Ekaterina Pronoza and Nataliya Kochetkova",
note = "Publisher Copyright: {\textcopyright} 2018 Instituto Politecnico Nacional. All rights reserved. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.",
year = "2018",
doi = "10.13053/CyS-22-4-3065",
language = "English",
volume = "22",
pages = "1329--1336",
journal = "Computacion y Sistemas",
issn = "1405-5546",
publisher = "Centro de Investigacion en Computacion (CIC) del Instituto Politecnico Nacional (IPN)",
number = "4",

}

RIS

TY - JOUR

T1 - Construction of paraphrase graphs as a means of news clusters extraction

AU - Yagunova, Elena

AU - Pronoza, Ekaterina

AU - Kochetkova, Nataliya

N1 - Publisher Copyright: © 2018 Instituto Politecnico Nacional. All rights reserved. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2018

Y1 - 2018

N2 - In this paper, we construct paraphrase graphs for news text collections (clusters). Our aims are, first, to prove that paraphrase graph construction method can be used for news clusters identification and, second, to analyze and compare stylistically different news collections. Our news collections include dynamic, static and combined (dynamic and static) texts. Their respective paraphrase graphs reflect their main characteristics. We also automatically extract the most informationally important linked fragments of news texts, and these fragments characterize news texts as either informative, conveying some information, or publicistic ones, trying to affect the readers emotionally.

AB - In this paper, we construct paraphrase graphs for news text collections (clusters). Our aims are, first, to prove that paraphrase graph construction method can be used for news clusters identification and, second, to analyze and compare stylistically different news collections. Our news collections include dynamic, static and combined (dynamic and static) texts. Their respective paraphrase graphs reflect their main characteristics. We also automatically extract the most informationally important linked fragments of news texts, and these fragments characterize news texts as either informative, conveying some information, or publicistic ones, trying to affect the readers emotionally.

KW - Linked text segments

KW - News cluster

KW - Paraphrase extraction

KW - Paraphrase graph

KW - Text analysis

UR - http://www.scopus.com/inward/record.url?scp=85069584235&partnerID=8YFLogxK

U2 - 10.13053/CyS-22-4-3065

DO - 10.13053/CyS-22-4-3065

M3 - Article

AN - SCOPUS:85069584235

VL - 22

SP - 1329

EP - 1336

JO - Computacion y Sistemas

JF - Computacion y Sistemas

SN - 1405-5546

IS - 4

ER -

ID: 73343554