<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="dahlmeier-2017-challenges">
    <titleInfo>
        <title>On the Challenges of Translating NLP Research into Commercial Products</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Daniel</namePart>
        <namePart type="family">Dahlmeier</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2017-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Regina</namePart>
            <namePart type="family">Barzilay</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Min-Yen</namePart>
            <namePart type="family">Kan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Vancouver, Canada</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper highlights challenges in industrial research related to translating research in natural language processing into commercial products. While the interest in natural language processing from industry is significant, the transfer of research to commercial products is non-trivial and its challenges are often unknown to or underestimated by many researchers. I discuss current obstacles and provide suggestions for increasing the chances for translating research to commercial success based on my experience in industrial research.</abstract>
    <identifier type="citekey">dahlmeier-2017-challenges</identifier>
    <identifier type="doi">10.18653/v1/P17-2015</identifier>
    <location>
        <url>https://aclanthology.org/P17-2015</url>
    </location>
    <part>
        <date>2017-07</date>
        <extent unit="page">
            <start>92</start>
            <end>96</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T On the Challenges of Translating NLP Research into Commercial Products
%A Dahlmeier, Daniel
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F dahlmeier-2017-challenges
%X This paper highlights challenges in industrial research related to translating research in natural language processing into commercial products. While the interest in natural language processing from industry is significant, the transfer of research to commercial products is non-trivial and its challenges are often unknown to or underestimated by many researchers. I discuss current obstacles and provide suggestions for increasing the chances for translating research to commercial success based on my experience in industrial research.
%R 10.18653/v1/P17-2015
%U https://aclanthology.org/P17-2015
%U https://doi.org/10.18653/v1/P17-2015
%P 92-96

Markdown (Informal)

[On the Challenges of Translating NLP Research into Commercial Products](https://aclanthology.org/P17-2015) (Dahlmeier, ACL 2017)

• On the Challenges of Translating NLP Research into Commercial Products (Dahlmeier, ACL 2017)

ACL

• Daniel Dahlmeier. 2017. On the Challenges of Translating NLP Research into Commercial Products. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 92–96, Vancouver, Canada. Association for Computational Linguistics.