Vytautas Magnus University Research Management System (VDU CRIS)
 
Use this url to cite publication: https://hdl.handle.net/20.500.12259/59640

Detecting information-dense texts: towards an automated analysis

Type of publication
Straipsnis konferencijos medžiagoje Scopus duomenų bazėje / Article in conference proceedings in Scopus database (P1a2)
Author(s)
AuthorAffiliation
Kalinauskaitė, Danguolė
Lituanistikos katedra / Department of Lithuanian Studies
LT
Baltijos pažangių technologijų institutas
LT
Title
Detecting information-dense texts: towards an automated analysis
[en]
Is part of
CEUR Workshop proceedings [electronic resource]: IVUS 2018, International conference on information technologies, Kaunas, Lithuania, 27 April, 2018. Aachen : CEUR-WS, 2018, Vol. 2145
Date Issued
Date
2018
Publisher
Aachen : CEUR-WS
Is Referenced by
Scopus
Extent
p. 95-98
URI
URI
http://ceur-ws.org/Vol-2145/p17.pdf
https://hdl.handle.net/20.500.12259/59640
Field of Science
Keywords (en)
Abstract (en)

Determining information density has become a central issue in natural language processing. While information density is seen as too complex to measure globally, a study of lexical and syntactic features allows a comparison of information density between different texts or different text genres. This paper provides a part of methodology proposed for automatic analysis of information density based on lexical and syntactic levels of language.

Type of document
type::text::journal::journal article::research article
Language
Anglų / English (en)
Coverage Spatial
Vokietija / Germany (DE)
ISSN (of the container)
1613-0073
Other Identifier(s)
VDU02-000023022
Access Rights
Apribota prieiga / Restricted Access
JournalCite ScoreSNIPSJRYearQuartile
CEUR Workshop Proceedings
0.6
0.313
0.166
2018
Q4