Automatic extraction of mathematical terms for precalculus

Stoykova, Velislava; Petkova, E.

doi:10.1016/j.protcy.2012.02.102

“…Also, the methodology to use parallel concordances and collocations is languageindependent approach to evaluate words semantic properties (Stoykova and Petkova, 2012) and can differentiate very subtle word semantic features with respect to their correct translation.…”

Section: Resultsmentioning

confidence: 99%

Detecting Time Expressions for Bulgarian and Slovak Language from Electronic Text Corpora

Stoykova

¹

,

Šimková

²

,

Majchráková

³

et al. 2015

Procedia - Social and Behavioral Sciences

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The paper presents a comparison of time expressions translations from Slovak to Bulgarian language using existing BulgarianSlovak/Slovak-Bulgarian electronic text corpora. It uses techniques of concordances and collocations generation from sentence aligned parallel bilingual text corpora to compare semantic content and related translations. The approach is applicable in language teaching and is useful for teaching less resourced languages.

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“…(Lossio- Ventura et al, 2016). ATE is applied in several domains such as biomedical (Lossio- Ventura et al, 2014b), ecological (Conrado et al, 2013), mathematical (Stoykova and Petkova, 2012), social networks (Lossio Ventura et al, 2012), natural sciences (Dobrov and Loukachevitch, 2011), and information technology (Newman et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Biomedical term extraction using fuzzy association

Das,

Majumder,

Phadikar

et al. 2023

Soft Comput

0

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Automatic term extraction from a biomedical text is a well-known problem in the area of natural language processing. It is carried out by employing four kinds of measures: linguistic and rule-based, dictionary-based, statistical, and machine learning. Automatic term extraction indicates whether or not two or more words come together in the text more often than by chance to form a biomedical term that automatically extracted using an automated system. A fuzzy set-theoretic approach is presented in this article that compares with the existing statistical measures. The experimental result shows that the fuzzy-measure offers better precision than the popular statistical-measures for extracting biomedical terms, especially when we have compared more than 60% ranked list of extracted terms.

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“…(Lossio- Ventura et al, 2016). ATE is applied in several domains such as biomedical (Lossio- Ventura et al, 2014b), ecological (Conrado et al, 2013), mathematical (Stoykova and Petkova, 2012), social networks (Lossio Ventura et al, 2012), natural sciences (Dobrov and Loukachevitch, 2011), and information technology (Newman et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Biomedical term extraction using fuzzy association

Das

¹

,

Majumder

²

,

Phadikar

³

et al. 2022

Preprint

0

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Automatic term extraction from a biomedical text is a well-known problem in the area of natural language processing. It is carried out by employing four kinds of measures: linguistic and rule-based, dictionary-based, statistical, and machine learning. Automatic term extraction indicates whether or not two or more words come together in the text more often than by chance to form a biomedical term that automatically extracted using an automated system. A fuzzy set-theoretic approach is presented in this article that compares with the existing statistical measures. The experimental result shows that the fuzzy-measure offers better precision than the popular statistical-measures for extracting biomedical terms, especially when we have compared more than 60% ranked list of extracted terms.

show abstract

Automatic extraction of mathematical terms for precalculus

Cited by 11 publications

References 4 publications

Detecting Time Expressions for Bulgarian and Slovak Language from Electronic Text Corpora

Detecting Time Expressions for Bulgarian and Slovak Language from Electronic Text Corpora

Biomedical term extraction using fuzzy association

Biomedical term extraction using fuzzy association

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