<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="fauceglia-etal-2019-automatic">
    <titleInfo>
        <title>Automatic Taxonomy Induction and Expansion</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Nicolas</namePart>
        <namePart type="given">Rodolfo</namePart>
        <namePart type="family">Fauceglia</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Alfio</namePart>
        <namePart type="family">Gliozzo</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sarthak</namePart>
        <namePart type="family">Dash</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Md.</namePart>
        <namePart type="given">Faisal</namePart>
        <namePart type="given">Mahbub</namePart>
        <namePart type="family">Chowdhury</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Nandana</namePart>
        <namePart type="family">Mihindukulasooriya</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Sebastian</namePart>
            <namePart type="family">Padó</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ruihong</namePart>
            <namePart type="family">Huang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Hong Kong, China</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>The Knowledge Graph Induction Service (KGIS) is an end-to-end knowledge induction system. One of its main capabilities is to automatically induce taxonomies from input documents using a hybrid approach that takes advantage of linguistic patterns, semantic web and neural networks. KGIS allows the user to semi-automatically curate and expand the induced taxonomy through a component called Smart SpreadSheet by exploiting distributional semantics. In this paper, we describe these taxonomy induction and expansion features of KGIS. A screencast video demonstrating the system is available in https://ibm.box.com/v/emnlp-2019-demo .</abstract>
    <identifier type="citekey">fauceglia-etal-2019-automatic</identifier>
    <identifier type="doi">10.18653/v1/D19-3005</identifier>
    <location>
        <url>https://aclanthology.org/D19-3005</url>
    </location>
    <part>
        <date>2019-11</date>
        <extent unit="page">
            <start>25</start>
            <end>30</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Automatic Taxonomy Induction and Expansion
%A Fauceglia, Nicolas Rodolfo
%A Gliozzo, Alfio
%A Dash, Sarthak
%A Chowdhury, Md. Faisal Mahbub
%A Mihindukulasooriya, Nandana
%Y Padó, Sebastian
%Y Huang, Ruihong
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F fauceglia-etal-2019-automatic
%X The Knowledge Graph Induction Service (KGIS) is an end-to-end knowledge induction system. One of its main capabilities is to automatically induce taxonomies from input documents using a hybrid approach that takes advantage of linguistic patterns, semantic web and neural networks. KGIS allows the user to semi-automatically curate and expand the induced taxonomy through a component called Smart SpreadSheet by exploiting distributional semantics. In this paper, we describe these taxonomy induction and expansion features of KGIS. A screencast video demonstrating the system is available in https://ibm.box.com/v/emnlp-2019-demo .
%R 10.18653/v1/D19-3005
%U https://aclanthology.org/D19-3005
%U https://doi.org/10.18653/v1/D19-3005
%P 25-30

Markdown (Informal)

[Automatic Taxonomy Induction and Expansion](https://aclanthology.org/D19-3005) (Fauceglia et al., EMNLP-IJCNLP 2019)

• Automatic Taxonomy Induction and Expansion (Fauceglia et al., EMNLP-IJCNLP 2019)

ACL

• Nicolas Rodolfo Fauceglia, Alfio Gliozzo, Sarthak Dash, Md. Faisal Mahbub Chowdhury, and Nandana Mihindukulasooriya. 2019. Automatic Taxonomy Induction and Expansion. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, pages 25–30, Hong Kong, China. Association for Computational Linguistics.