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<!DOCTYPE html>
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<title>NLP4RE'20</title>
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NLP4RE'20
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Home
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<b>Keynote & Program</b>
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<div id="start" class="jumbotron">
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<h2 style="text-align:left;color:#fff;margin-top:20px;margin-bottom:10px;">Third Workshop
Natural Language Processing for Requirements Engineering
</h2>
<p class="lead">REFSQ'20 Workshop, June 23rd (Online) </p>
</div>
</div>
<div class="col-md-6">
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<div class="container start">
<div class="row">
<div class="col-xs-8">
<h2>Keynote</h2>
<p style="clear:both">NLP4RE will feature a keynote from <a
href="https://logological.org/"><strong>Tristan Miller</strong></a> from The Austrian Research
Institute for Artificial Intelligence discussing the recent research advances on natural language
ambiguity from an NLP perspective to inspire the RE community with new future directions.</p>
<p>
<strong>Don't shun the pun: On the requirements and constraints for preserving ambiguity in the (machine) translation of humour</strong>
</p>
<p>How do we know when a translation is good? This seemingly simple
question has long dogged human practitioners of translation, and has
arguably taken on even greater importance in today's world of fully
automatic, end-to-end machine translation systems. Much of the
difficulty in assessing translation quality is that different
translations of the same text may be made for different purposes, each
of which entails a unique set of requirements and constraints. This
difficulty is compounded by ambiguities in the source text, which must
be identified and then preserved or eliminated according to the needs of
the translation and the (apparent) intent of the source text. In this
talk, I survey the state of the art in linguistics, computational
linguistics, translation, and machine translation as it relates to the
notion of linguistic ambiguity in general, and intentional humorous
ambiguity in particular. I describe the various constraints and
requirements of different types of translations and provide examples of
how various automatic and interactive techniques from natural language
processing can be used to detect and then resolve or preserve linguistic
ambiguities according to these constraints and requirements. In the
vein of the "Translator's Amanuensis" proposed by Martin Kay, I outline
some specific proposals concerning how the hitherto disparate work in
the aforementioned fields can be connected with a view to producing
"machine-in-the-loop" computer-assisted translation (CAT) tools to
assist human translators in selecting and implementing pun translation
strategies in furtherance of the translation requirements. Throughout
the talk, I will attempt to draw links with how this research relates to
the requirements engineering community.
</p>
<div class="thumbnail" style="border:none; background:white;">
<div class="col-xs-3 image-container">
<img src="img/tristanmiller.jpg" style="height:150px; margin-left:15px;" />
</div>
<div class="col-xs-9">
<p style="margin-left: 0px;"><strong>Biography.</strong> Tristan Miller is is a computational
linguist working mainly in the area of lexical semantics. His research interests include
word sense disambiguation, lexical substitution, and computational detection, and
interpretation of humour. Since 2019 Tristan has been working as a research scientist in the
Language and Interaction Technologies Group of the Austrian Research Institute for
Artificial intelligence (OFAI), where he heads the project Computational Pun-derstanding:
Computer-Assisted Translation of Humorous Wordplay. </p>
</div>
</div>
<br />
<h2>Accepted Papers</h2>
<ul>
<li>
Monica Arrabito, Alessandro Fantechi, Stefania Gnesi and Laura Semini. <i>A comparison of NLP Tools for RE to extract Variation Points</i>
</li>
<li>
Kenji Mori, Naoko Okubo, Yasushi Ueda, Masafumi Katahira and Toshiyuki Amagasa. <i>Toward Latent Knowledge Extraction Based on the Correlation of Heterogeneous Text Data Related to Space System Development </i>
</li>
<li>
Olivia Kenney and Matt Cooper. <i> QVscribe for Practical and Effective NLP4RE</i>
</li>
<li>
Long Wang, Hiroyuki Nakagawa and Tatsuhiro Tsuchiya. <i> Opinion Analysis and Organization of Mobile Application User Reviews</i>
</li>
<li>
Manlio Bacco, Gianluca Brunori, Felice Dell'Orletta and Alessio Ferrari. <i>Using NLP to Support Terminology Extraction and Domain Scoping: Report on the H2020 DESIRA Project</i>
</li>
<li>
Bert de Brock. <i>On System Sequence Descriptions </i>
</li>
<li>
Vaibhav Jain, Ruchika Malhotra, Sanskar Jain and Nishant Tanwar. <i>Cross-Domain Ambiguity Detection using Linear Transformation of Word Embedding Spaces</i>
</li>
</ul>
<br />
<h2>Program</h2>
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<table class="tg">
<thead>
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<th class="tg-j6zm">TIME (UTC+2)</th>
<th class="tg-bobw">TITLE</th>
</tr>
</thead>
<tbody>
<tr>
<td class="tg-7zrl">12:45 - 12:50</td>
<td class="tg-7zrl">Welcome and Intro</td>
</tr>
<tr>
<td class="tg-amwm" colspan="2">SESSION 1</td>
</tr>
<tr>
<td class="tg-7zrl">12:50 - 13.05</td>
<td class="tg-7zrl"><span style="font-weight:normal;font-style:normal;text-decoration:none">Toward Latent Knowledge Extraction Based on the Correlation of Heterogeneous Text Data Related to Space System Development</span></td>
</tr>
<tr>
<td class="tg-11x7">13.05 - 13.20</td>
<td class="tg-11x7"><span style="font-weight:normal;font-style:normal;text-decoration:none">Opinion Analysis and Organization of Mobile Application User Reviews</span></td>
</tr>
<tr>
<td class="tg-7zrl">13.20 - 13.35</td>
<td class="tg-7zrl"><span style="font-weight:normal;font-style:normal;text-decoration:none">Cross-Domain Ambiguity Detection using Linear Transformation of Word Embedding Spaces</span></td>
</tr>
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<td class="tg-11x7">13.35 - 13.45</td>
<td class="tg-11x7"><span style="font-weight:normal;font-style:normal;text-decoration:none">Using NLP to Support Terminology Extraction and Domain Scoping: Report on the H2020 DESIRA Project</span></td>
</tr>
<tr>
<td class="tg-7zrl">13.45 - 14.00</td>
<td class="tg-7zrl">Fun activity 😀</td>
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<td class="tg-7zrl">14:00 - 14:15</td>
<td class="tg-7zrl">BREAK</td>
</tr>
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<td class="tg-amwm" colspan="2">SESSION 2</td>
</tr>
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<td class="tg-7zrl">14:15 - 14:30</td>
<td class="tg-7zrl"><span style="font-weight:normal;font-style:normal;text-decoration:none">A comparison of NLP Tools for RE to extract Variation Points</span></td>
</tr>
<tr>
<td class="tg-11x7">14:30 - 14:40</td>
<td class="tg-11x7"> QVscribe for Practical and Effective NLP4RE</td>
</tr>
<tr>
<td class="tg-7zrl">14:40 - 14:55</td>
<td class="tg-7zrl"><span style="font-weight:normal;font-style:normal;text-decoration:none">On System Sequence Descriptions</span></td>
</tr>
<tr>
<td class="tg-11x7">14:55 - 15:15</td>
<td class="tg-11x7">Fun activity 😀</td>
</tr>
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<td class="tg-7zrl">15:15 - 15:30</td>
<td class="tg-7zrl">BREAK</td>
</tr>
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<td class="tg-amwm" colspan="2">SESSION 3</td>
</tr>
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<td class="tg-7zrl">15:30 - 16:15</td>
<td class="tg-7zrl">Keynote by Tristan Miller</td>
</tr>
<tr>
<td class="tg-11x7">16:15 - 16:30</td>
<td class="tg-11x7">Fun activity 😀</td>
</tr>
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<td class="tg-7zrl">16:30 - 16:45</td>
<td class="tg-7zrl">Discussion and wrap up</td>
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<div class="panel panel-default">
<div class="panel-heading">
<b>Important dates</b>
</div>
<div class="panel-body">
<i>Papers submission</i>: <strike>January 17th</strike> <b>January 24th</b>
<br />
<i>Authors notification</i>: February 7th
<br />
<i>Camera Ready</i>: February 28th
<br>
<i>Workshop</i>: June 23rd
<br />
</div>
</div>
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<div class="panel-heading">
<b>Workshop organizers</b>
</div>
<div class="panel-body">
Sallam Abualhaija
<small class="text-muted">University of Luxembourg (Luxembourg)</small>
<br />
Davide Fucci
<small class="text-muted">Blekinge Institute of Technlogy (Sweden)</small>
<br /> Fabiano Dalpiaz
<small class="text-muted">Utrecht University (The Netherlands)</small>
<br /> Xavier Franch
<small class="text-muted">Universitat Politècnica de Barcelona (Spain)</small>
</div>
</div>
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href="https://twitter.com/NLP4RE?ref_src=twsrc%5Etfw">Tweets by NLP4RE</a>
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