@inproceedings{fontanella-etal-2023-unsupervised,
title = "Unsupervised Methods for Domain Specific Ambiguity Detection. The Case of {G}erman Physics Language",
author = "Fontanella, Vitor and
Wartena, Christian and
Friege, Gunnar",
editor = "Amblard, Maxime and
Breitholtz, Ellen",
booktitle = "Proceedings of the 15th International Conference on Computational Semantics",
month = jun,
year = "2023",
address = "Nancy, France",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.iwcs-1.26/",
pages = "252--257",
abstract = "Many terms used in physics have a different meaning or usage pattern in general language, constituting a learning barrier in physics teaching. The systematic identification of such terms is considered to be useful for science education as well as for terminology extraction. This article compares three methods based on vector semantics and a simple frequency-based baseline for automatically identifying terms used in general language with domain-specific use in physics. For evaluation, we use ambiguity scores from a survey among physicists and data about the number of term senses from Wiktionary. We show that the so-called Vector Initialization method obtains the best results."
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="fontanella-etal-2023-unsupervised">
<titleInfo>
<title>Unsupervised Methods for Domain Specific Ambiguity Detection. The Case of German Physics Language</title>
</titleInfo>
<name type="personal">
<namePart type="given">Vitor</namePart>
<namePart type="family">Fontanella</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Christian</namePart>
<namePart type="family">Wartena</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Gunnar</namePart>
<namePart type="family">Friege</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2023-06</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 15th International Conference on Computational Semantics</title>
</titleInfo>
<name type="personal">
<namePart type="given">Maxime</namePart>
<namePart type="family">Amblard</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ellen</namePart>
<namePart type="family">Breitholtz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Nancy, France</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Many terms used in physics have a different meaning or usage pattern in general language, constituting a learning barrier in physics teaching. The systematic identification of such terms is considered to be useful for science education as well as for terminology extraction. This article compares three methods based on vector semantics and a simple frequency-based baseline for automatically identifying terms used in general language with domain-specific use in physics. For evaluation, we use ambiguity scores from a survey among physicists and data about the number of term senses from Wiktionary. We show that the so-called Vector Initialization method obtains the best results.</abstract>
<identifier type="citekey">fontanella-etal-2023-unsupervised</identifier>
<location>
<url>https://aclanthology.org/2023.iwcs-1.26/</url>
</location>
<part>
<date>2023-06</date>
<extent unit="page">
<start>252</start>
<end>257</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Unsupervised Methods for Domain Specific Ambiguity Detection. The Case of German Physics Language
%A Fontanella, Vitor
%A Wartena, Christian
%A Friege, Gunnar
%Y Amblard, Maxime
%Y Breitholtz, Ellen
%S Proceedings of the 15th International Conference on Computational Semantics
%D 2023
%8 June
%I Association for Computational Linguistics
%C Nancy, France
%F fontanella-etal-2023-unsupervised
%X Many terms used in physics have a different meaning or usage pattern in general language, constituting a learning barrier in physics teaching. The systematic identification of such terms is considered to be useful for science education as well as for terminology extraction. This article compares three methods based on vector semantics and a simple frequency-based baseline for automatically identifying terms used in general language with domain-specific use in physics. For evaluation, we use ambiguity scores from a survey among physicists and data about the number of term senses from Wiktionary. We show that the so-called Vector Initialization method obtains the best results.
%U https://aclanthology.org/2023.iwcs-1.26/
%P 252-257
Markdown (Informal)
[Unsupervised Methods for Domain Specific Ambiguity Detection. The Case of German Physics Language](https://aclanthology.org/2023.iwcs-1.26/) (Fontanella et al., IWCS 2023)
ACL