<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gelles-dunham-2024-multi">
    <titleInfo>
        <title>Multi-Label Field Classification for Scientific Documents using Expert and Crowd-sourced Knowledge</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Rebecca</namePart>
        <namePart type="family">Gelles</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>2024-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the First Workshop on Advancing Natural Language Processing for Wikipedia</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Lucie</namePart>
            <namePart type="family">Lucie-Aimée</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Angela</namePart>
            <namePart type="family">Fan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Tajuddeen</namePart>
            <namePart type="family">Gwadabe</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Isaac</namePart>
            <namePart type="family">Johnson</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Fabio</namePart>
            <namePart type="family">Petroni</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Daniel</namePart>
            <namePart type="family">van Strien</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Miami, Florida, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Taxonomies of scientific research seek to describe complex domains of activity that are overlapping and dynamic. We address this challenge by combining knowledge curated by the Wikipedia community with the input of subject-matter experts to identify, define, and validate a system of 1,110 granular fields of study for use in multi-label classification of scientific publications. The result is capable of categorizing research across subfields of artificial intelligence, computer security, semiconductors, genetics, virology, immunology, neuroscience, biotechnology, and bioinformatics. We then develop and evaluate a solution for zero-shot classification of publications in terms of these fields.</abstract>
    <identifier type="citekey">gelles-dunham-2024-multi</identifier>
    <location>
        <url>https://aclanthology.org/2024.wikinlp-1.7</url>
    </location>
    <part>
        <date>2024-11</date>
        <extent unit="page">
            <start>14</start>
            <end>20</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Multi-Label Field Classification for Scientific Documents using Expert and Crowd-sourced Knowledge
%A Gelles, Rebecca
%A Dunham, James
%Y Lucie-Aimée, Lucie
%Y Fan, Angela
%Y Gwadabe, Tajuddeen
%Y Johnson, Isaac
%Y Petroni, Fabio
%Y van Strien, Daniel
%S Proceedings of the First Workshop on Advancing Natural Language Processing for Wikipedia
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F gelles-dunham-2024-multi
%X Taxonomies of scientific research seek to describe complex domains of activity that are overlapping and dynamic. We address this challenge by combining knowledge curated by the Wikipedia community with the input of subject-matter experts to identify, define, and validate a system of 1,110 granular fields of study for use in multi-label classification of scientific publications. The result is capable of categorizing research across subfields of artificial intelligence, computer security, semiconductors, genetics, virology, immunology, neuroscience, biotechnology, and bioinformatics. We then develop and evaluate a solution for zero-shot classification of publications in terms of these fields.
%U https://aclanthology.org/2024.wikinlp-1.7
%P 14-20

Markdown (Informal)

[Multi-Label Field Classification for Scientific Documents using Expert and Crowd-sourced Knowledge](https://aclanthology.org/2024.wikinlp-1.7) (Gelles & Dunham, WikiNLP 2024)

• Multi-Label Field Classification for Scientific Documents using Expert and Crowd-sourced Knowledge (Gelles & Dunham, WikiNLP 2024)

ACL

• Rebecca Gelles and James Dunham. 2024. Multi-Label Field Classification for Scientific Documents using Expert and Crowd-sourced Knowledge. In Proceedings of the First Workshop on Advancing Natural Language Processing for Wikipedia, pages 14–20, Miami, Florida, USA. Association for Computational Linguistics.