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Keyword extraction from single Russian document. / Sandul, Mikhail Vadimovich; Mikhailova, Elena Georgievna.

в: CEUR Workshop Proceedings, Том 2135, 01.01.2018, стр. 30-36.

Результаты исследований: Научные публикации в периодических изданияхстатья в журнале по материалам конференцииРецензирование

Harvard

Sandul, MV & Mikhailova, EG 2018, 'Keyword extraction from single Russian document', CEUR Workshop Proceedings, Том. 2135, стр. 30-36.

APA

Sandul, M. V., & Mikhailova, E. G. (2018). Keyword extraction from single Russian document. CEUR Workshop Proceedings, 2135, 30-36.

Vancouver

Sandul MV, Mikhailova EG. Keyword extraction from single Russian document. CEUR Workshop Proceedings. 2018 Янв. 1;2135:30-36.

Author

Sandul, Mikhail Vadimovich ; Mikhailova, Elena Georgievna. / Keyword extraction from single Russian document. в: CEUR Workshop Proceedings. 2018 ; Том 2135. стр. 30-36.

BibTeX

@article{749462373f2442b9abffa8f504288d6a,
title = "Keyword extraction from single Russian document",
abstract = "The problem of automatic keyword and phrases extraction from a text occurs in different tasks of information retrieval and text mining. The task is the identification of terms that best describe the subject of a document. Currently there are a lot of research to solve this problem. Basically, algorithms are developed for texts in English. The possibility of applying these algorithms to the Russian texts are not sufficiently investigated. One of the most known algorithms for solving the problem of keyword extraction is RAKE. This article examines the effectiveness of RAKE algorithm for texts in Russian. The work also applies the hybrid method, which uses the Γ-index metric for phrases weighting, which were obtained using the algorithm RAKE. The article shows that this algorithm is more accurate than PAKE while reducing the number of selected phrases.",
author = "Sandul, {Mikhail Vadimovich} and Mikhailova, {Elena Georgievna}",
year = "2018",
month = jan,
day = "1",
language = "English",
volume = "2135",
pages = "30--36",
journal = "CEUR Workshop Proceedings",
issn = "1613-0073",
publisher = "RWTH Aahen University",
note = "3rd Conference on Software Engineering and Information Management, SEIM 2018 ; Conference date: 14-04-2018",

}

RIS

TY - JOUR

T1 - Keyword extraction from single Russian document

AU - Sandul, Mikhail Vadimovich

AU - Mikhailova, Elena Georgievna

PY - 2018/1/1

Y1 - 2018/1/1

N2 - The problem of automatic keyword and phrases extraction from a text occurs in different tasks of information retrieval and text mining. The task is the identification of terms that best describe the subject of a document. Currently there are a lot of research to solve this problem. Basically, algorithms are developed for texts in English. The possibility of applying these algorithms to the Russian texts are not sufficiently investigated. One of the most known algorithms for solving the problem of keyword extraction is RAKE. This article examines the effectiveness of RAKE algorithm for texts in Russian. The work also applies the hybrid method, which uses the Γ-index metric for phrases weighting, which were obtained using the algorithm RAKE. The article shows that this algorithm is more accurate than PAKE while reducing the number of selected phrases.

AB - The problem of automatic keyword and phrases extraction from a text occurs in different tasks of information retrieval and text mining. The task is the identification of terms that best describe the subject of a document. Currently there are a lot of research to solve this problem. Basically, algorithms are developed for texts in English. The possibility of applying these algorithms to the Russian texts are not sufficiently investigated. One of the most known algorithms for solving the problem of keyword extraction is RAKE. This article examines the effectiveness of RAKE algorithm for texts in Russian. The work also applies the hybrid method, which uses the Γ-index metric for phrases weighting, which were obtained using the algorithm RAKE. The article shows that this algorithm is more accurate than PAKE while reducing the number of selected phrases.

UR - http://www.scopus.com/inward/record.url?scp=85050482656&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85050482656

VL - 2135

SP - 30

EP - 36

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 3rd Conference on Software Engineering and Information Management, SEIM 2018

Y2 - 14 April 2018

ER -

ID: 38400996