TY - JOUR

T1 - Automatic text summarization based on syntactic links

AU - Yerimbetova, A. S.

AU - Batura, T. V.

AU - Murzin, F. A.

AU - Sagnayeva, S. K.

N1 - Publisher Copyright: Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0) Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - The task of information retrieval is to find documents relevant to the query in a certain collection of documents. The document is a text selected by the author as a single fragment. A query is usually a meaningful phrase or set of words describing the information needed. Instead of searching through the whole document, organizing a search by topic or resume of the document becomes enough. By the term "topic" we refer to a set of small reference texts. Therefore, one of the interesting tasks in information retrieval systems is the task of classifying texts by topic. The whole classification process is carried out in four stages: preprocessing the text, weighing the terms, weighing the sentences, extracting meaningful sentences. In the process of selecting topics, fragments of the text are studied (for example, paragraphs) and compared with the chosen standard. Different fragments can be attributed to different topics. Selected fragments can be combined into a summary on this topic. This paper considers the issues of automatic summarization of text documents taking into account the syntactic relations between words and word forms in sentences that can be obtained at the output of the Link Gramma Parser (LGP) system for the Kazakh and Turkish languages. The authors operate on the results of studies on customizing the LGP parser for agglutinative languages.

AB - The task of information retrieval is to find documents relevant to the query in a certain collection of documents. The document is a text selected by the author as a single fragment. A query is usually a meaningful phrase or set of words describing the information needed. Instead of searching through the whole document, organizing a search by topic or resume of the document becomes enough. By the term "topic" we refer to a set of small reference texts. Therefore, one of the interesting tasks in information retrieval systems is the task of classifying texts by topic. The whole classification process is carried out in four stages: preprocessing the text, weighing the terms, weighing the sentences, extracting meaningful sentences. In the process of selecting topics, fragments of the text are studied (for example, paragraphs) and compared with the chosen standard. Different fragments can be attributed to different topics. Selected fragments can be combined into a summary on this topic. This paper considers the issues of automatic summarization of text documents taking into account the syntactic relations between words and word forms in sentences that can be obtained at the output of the Link Gramma Parser (LGP) system for the Kazakh and Turkish languages. The authors operate on the results of studies on customizing the LGP parser for agglutinative languages.

KW - Closeness centrality

KW - Directed graph

KW - Information retrieval

KW - LGP

KW - Summarization

KW - Text topics

KW - Word weight

UR - http://www.scopus.com/inward/record.url?scp=85081539628&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85081539628

VL - 2570

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 1st International Conference of Information Systems and Design, ICID 2019

Y2 - 5 December 2019

ER -