<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="londhe-etal-2016-time">
    <titleInfo>
        <title>Time-Independent and Language-Independent Extraction of Multiword Expressions From Twitter</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Nikhil</namePart>
        <namePart type="family">Londhe</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Rohini</namePart>
        <namePart type="family">Srihari</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Vishrawas</namePart>
        <namePart type="family">Gopalakrishnan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>The COLING 2016 Organizing Committee</publisher>
            <place>
                <placeTerm type="text">Osaka, Japan</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Multiword Expressions (MWEs) are crucial lexico-semantic units in any language. However, most work on MWEs has been focused on standard monolingual corpora. In this work, we examine MWE usage on Twitter - an inherently multilingual medium with an extremely short average text length that is often replete with grammatical errors. In this work we present a new graph based, language agnostic method for automatically extracting MWEs from tweets. We show how our method outperforms standard Association Measures. We also present a novel unsupervised evaluation technique to ascertain the accuracy of MWE extraction.</abstract>
    <identifier type="citekey">londhe-etal-2016-time</identifier>
    <location>
        <url>https://aclanthology.org/C16-1214</url>
    </location>
    <part>
        <date>2016-12</date>
        <extent unit="page">
            <start>2269</start>
            <end>2278</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Time-Independent and Language-Independent Extraction of Multiword Expressions From Twitter
%A Londhe, Nikhil
%A Srihari, Rohini
%A Gopalakrishnan, Vishrawas
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F londhe-etal-2016-time
%X Multiword Expressions (MWEs) are crucial lexico-semantic units in any language. However, most work on MWEs has been focused on standard monolingual corpora. In this work, we examine MWE usage on Twitter - an inherently multilingual medium with an extremely short average text length that is often replete with grammatical errors. In this work we present a new graph based, language agnostic method for automatically extracting MWEs from tweets. We show how our method outperforms standard Association Measures. We also present a novel unsupervised evaluation technique to ascertain the accuracy of MWE extraction.
%U https://aclanthology.org/C16-1214
%P 2269-2278

Markdown (Informal)

[Time-Independent and Language-Independent Extraction of Multiword Expressions From Twitter](https://aclanthology.org/C16-1214) (Londhe et al., COLING 2016)

• Time-Independent and Language-Independent Extraction of Multiword Expressions From Twitter (Londhe et al., COLING 2016)

ACL

• Nikhil Londhe, Rohini Srihari, and Vishrawas Gopalakrishnan. 2016. Time-Independent and Language-Independent Extraction of Multiword Expressions From Twitter. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2269–2278, Osaka, Japan. The COLING 2016 Organizing Committee.