@inproceedings{toney-dunham-2022-multi,
title = "Multi-label Classification of Scientific Research Documents Across Domains and Languages",
author = "Toney, Autumn and
Dunham, James",
editor = "Cohan, Arman and
Feigenblat, Guy and
Freitag, Dayne and
Ghosal, Tirthankar and
Herrmannova, Drahomira and
Knoth, Petr and
Lo, Kyle and
Mayr, Philipp and
Shmueli-Scheuer, Michal and
de Waard, Anita and
Wang, Lucy Lu",
booktitle = "Proceedings of the Third Workshop on Scholarly Document Processing",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.sdp-1.12",
pages = "105--114",
abstract = "Automatically organizing scholarly literature is a necessary and challenging task. By assigning scientific research publications key concepts, researchers, policymakers, and the general public are able to search for and discover relevant research literature. The organization of scientific research evolves with new discoveries and publications, requiring an up-to-date and scalable text classification model. Additionally, scientific research publications benefit from multi-label classification, particularly with more fine-grained sub-domains. Prior work has focused on classifying scientific publications from one research area (e.g., computer science), referencing static concept descriptions, and implementing an English-only classification model. We propose a multi-label classification model that can be implemented in non-English languages, across all of scientific literature, with updatable concept descriptions.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="toney-dunham-2022-multi">
<titleInfo>
<title>Multi-label Classification of Scientific Research Documents Across Domains and Languages</title>
</titleInfo>
<name type="personal">
<namePart type="given">Autumn</namePart>
<namePart type="family">Toney</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">James</namePart>
<namePart type="family">Dunham</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2022-10</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Third Workshop on Scholarly Document Processing</title>
</titleInfo>
<name type="personal">
<namePart type="given">Arman</namePart>
<namePart type="family">Cohan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Guy</namePart>
<namePart type="family">Feigenblat</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dayne</namePart>
<namePart type="family">Freitag</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tirthankar</namePart>
<namePart type="family">Ghosal</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Drahomira</namePart>
<namePart type="family">Herrmannova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Petr</namePart>
<namePart type="family">Knoth</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kyle</namePart>
<namePart type="family">Lo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Philipp</namePart>
<namePart type="family">Mayr</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Michal</namePart>
<namePart type="family">Shmueli-Scheuer</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anita</namePart>
<namePart type="family">de Waard</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lucy</namePart>
<namePart type="given">Lu</namePart>
<namePart type="family">Wang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Gyeongju, Republic of Korea</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Automatically organizing scholarly literature is a necessary and challenging task. By assigning scientific research publications key concepts, researchers, policymakers, and the general public are able to search for and discover relevant research literature. The organization of scientific research evolves with new discoveries and publications, requiring an up-to-date and scalable text classification model. Additionally, scientific research publications benefit from multi-label classification, particularly with more fine-grained sub-domains. Prior work has focused on classifying scientific publications from one research area (e.g., computer science), referencing static concept descriptions, and implementing an English-only classification model. We propose a multi-label classification model that can be implemented in non-English languages, across all of scientific literature, with updatable concept descriptions.</abstract>
<identifier type="citekey">toney-dunham-2022-multi</identifier>
<location>
<url>https://aclanthology.org/2022.sdp-1.12</url>
</location>
<part>
<date>2022-10</date>
<extent unit="page">
<start>105</start>
<end>114</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Multi-label Classification of Scientific Research Documents Across Domains and Languages
%A Toney, Autumn
%A Dunham, James
%Y Cohan, Arman
%Y Feigenblat, Guy
%Y Freitag, Dayne
%Y Ghosal, Tirthankar
%Y Herrmannova, Drahomira
%Y Knoth, Petr
%Y Lo, Kyle
%Y Mayr, Philipp
%Y Shmueli-Scheuer, Michal
%Y de Waard, Anita
%Y Wang, Lucy Lu
%S Proceedings of the Third Workshop on Scholarly Document Processing
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F toney-dunham-2022-multi
%X Automatically organizing scholarly literature is a necessary and challenging task. By assigning scientific research publications key concepts, researchers, policymakers, and the general public are able to search for and discover relevant research literature. The organization of scientific research evolves with new discoveries and publications, requiring an up-to-date and scalable text classification model. Additionally, scientific research publications benefit from multi-label classification, particularly with more fine-grained sub-domains. Prior work has focused on classifying scientific publications from one research area (e.g., computer science), referencing static concept descriptions, and implementing an English-only classification model. We propose a multi-label classification model that can be implemented in non-English languages, across all of scientific literature, with updatable concept descriptions.
%U https://aclanthology.org/2022.sdp-1.12
%P 105-114
Markdown (Informal)
[Multi-label Classification of Scientific Research Documents Across Domains and Languages](https://aclanthology.org/2022.sdp-1.12) (Toney & Dunham, sdp 2022)
ACL