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<p class="western" style="margin-bottom: 0cm; line-height: 100%">Sorry
for multiple postings<br>
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<div> <b>===========================================================</b></div>
<div>Second Call for Papers for </div>
<div><b> SemDeep-3 </b></div>
<div><b> </b><a
data-is-link="http://www.dfki.de/semdeep-3/callforpapers.html"
class="textEditor-link"
href="http://www.dfki.de/semdeep-3/callforpapers.html"
rel="noreferrer nofollow" target="_blank"><b>http://www.dfki.de/semdeep-3/callforpapers.html</b></a></div>
<div> </div>
<div> <b>Workshop on Semantic Deep Learning </b>collocated with
COLING 2018. </div>
<div> </div>
<div> <b>===========================================================</b></div>
<div> </div>
<div> IMPORTANT DATES</div>
<div> -----------------------</div>
<div> STRICT Paper Submission Deadline: May 25, 2018 (11:50 pm CET)</div>
<div> Notification of Acceptance: June 20, 2018</div>
<div> Camera-Ready Papers Due: June 30, 2018</div>
<div> Workshop Dates: August 20-21, 2018</div>
<div> Conference Dates: August 20-25, 2018</div>
<div> </div>
<div> CALL FOR PAPERS </div>
<div> -----------------------</div>
<div> With the experiences gained from two previous workshops on
Semantic Deep Learning, </div>
<div> we would like to take this endeavor one step further by
providing a platform at COLING 2018 </div>
<div> where researchers and professionals in computational
linguistics are invited to report results and </div>
<div> systems on the possible contributions of Deep Learning to
classic problems in semantic applications, </div>
<div> such as meaning representation, dependency parsing, semantic
role labelling, word sense </div>
<div> disambiguation, semantic relation extraction, statistical
relational learning, knowledge base </div>
<div> completion, or semantically grounded inference. </div>
<div> </div>
<div> There are notable examples of contributions leveraging either
deep neural architectures or distributed </div>
<div> representations learned via deep neural networks in the broad
area of Semantic Web technologies. </div>
<div> These include, among others: (lightweight) ontology learning,
ontology alignment , ontology annotation, </div>
<div> and ontology prediction. Ontologies, on the other hand, have
been repeatedly utilized as background </div>
<div> knowledge for machine learning tasks. As an example, there is
a myriad of hybrid approaches for </div>
<div> learning embeddings by jointly incorporating corpus-based
evidence and semantic resources. </div>
<div> This interplay between structured knowledge and corpus-based
approaches has given way to </div>
<div> knowledge-rich embeddings, which in turn have proven useful
for tasks such as hypernym discovery , </div>
<div> collocation discovery and classification, word sense
disambiguation, and many others.</div>
<div> </div>
<div> We thus invite submissions that illustrate how NLP can benefit
from the interaction between deep learning </div>
<div> and Semantic Web resources and technologies. At the same time,
we are interested in submissions that </div>
<div> show how knowledge representation can assist in deep learning
tasks deployed in the field of NLP </div>
<div> and how knowledge representation systems can build on top of
deep learning results, for example </div>
<div> in the field of Neural Machine Translation (NMT). </div>
<div> </div>
<div> TOPICS OF INTEREST</div>
<div> -----------------------</div>
<div> Structured knowledge in deep learning:</div>
<div> - neural networks and logic rules for semantic
compositionality</div>
<div> - learning and applying knowledge graph embeddings to NLP
tasks</div>
<div> - learning semantic similarity and encoding distances as
knowledge graph</div>
<div> - ontology-based text classification</div>
<div> - multilingual resources for neural representations of
linguistics</div>
<div> - semantic role labeling</div>
<div> </div>
<div> Deep reasoning and inferences:</div>
<div> - commonsense reasoning and vector space models</div>
<div> - reasoning with deep learning methods </div>
<div> </div>
<div> Learning knowledge representations with deep learning</div>
<div> - deep learning methods for knowledge-base completion</div>
<div> - deep learning models for learning knowledge representations
from text</div>
<div> - deep learning ontological annotations </div>
<div> </div>
<div> Joint tasks:</div>
<div> - information retrieval and extraction with knowledge graphs
and deep learning models</div>
<div> - knowledge-based deep word sense disambiguation and entity
linking</div>
<div> - investigation of compatibilities and incompatibilities
between deep learning and Semantic Web approaches</div>
<div> </div>
<div> SUBMISSION INSTRUCTIONS</div>
<div> -----------------------</div>
<div> Authors are invited to submit papers describing original,
unpublished</div>
<div> work, completed or in progress. The papers should be maximally
9</div>
<div> pages with maximally 2 additional pages for references. </div>
<div> </div>
<div> The COLING 2018 templates must be used. Paper submission will
be </div>
<div> electronic in PDF format through the SoftConf conference
management system.</div>
<div> Workshop Proceedings will be published by COLING 2018. </div>
<div> </div>
<div> REVIEWING POLICY</div>
<div> ----------------</div>
<div> Reviewing will be double-blind, so authors need to conceal
their</div>
<div> identity. The paper should not include the authors' names and
affiliations, nor any acknowledgements. Limit anonymized</div>
<div> self-references only to articles that are relevant for
reviewers.</div>
<div> </div>
<div> WORKSHOP ORGANIZERS</div>
<div> ----------------</div>
<div> Luis Espinosa Anke, Cardiff University, UK</div>
<div> Thierry Declerck, German Research Centre for Artificial
Intelligence (DFKI GmbH), Saarbrücken, Germany</div>
<div> Dagmar Gromann, Technical University Dresden (TU Dresden),
Dresden, Germany</div>
<div> </div>
<div> PROGRAM COMMITTEE</div>
<div> ----------------</div>
<div> Kemo Adrian, Artificial Intelligence Research Institute
(IIIA-CSIC), Bellaterra, Spain</div>
<div> Luu Ahn Tuan (Institute for Infocomm Research, Singapore)</div>
<div> Miguel Ballesteros, IBM T.J. Watson Research Center, Yorktown
Heights, NY, USA</div>
<div> Jose Camacho-Collados, Sapienza University of Rome, Rome,
Italy</div>
<div> Gerard Casamayor, Pompeu Fabra University, Spain</div>
<div> Stamatia Dasiopoulou, Pompeu Fabra University, Spain</div>
<div> Maarten Grachten, Austrian Research Institute for AI, Vienna,
Austria</div>
<div> Dario Garcia-Casulla, Barcelona Supercomputing Center (BSC),
Barcelona, Spain</div>
<div> Jorge Gracia Del Río, University of Zaragoza, Spain</div>
<div> Jindrich Helcl, Charles University, Prague, Czech Republic</div>
<div> Dirk Hovy, Computer Science Department of the University of
Copenhagen, Denmark</div>
<div> Petya Osenova, Bulgarian Academy of Sciences, Sofia, Bulgaria</div>
<div> Martin Riedel, Hamburg University, Germany</div>
<div> Stephen Roller, Facebook AI Research</div>
<div> Francesco Ronzano, Pompeu Fabra University, Barcelona, Spain</div>
<div> Enrico Santus, The Hong Kong Polytechnic University, Hong Kong</div>
<div> Francois Scharffe, Axon Research, New York, USA</div>
<div> Vered Shwartz, Bar-Ilan University, Ramat Gan, Isreal</div>
<div> Kiril Simov, Bulgarian Academy of Sciences, Sofia, Bulgaria</div>
<div> Michael Spranger, Sony Computer Science Laboratories Inc.,
Tokyo, Japan</div>
<div> Armand Vilalta, Barcelona Supercomputing Center (BSC),
Barcelona, Spain</div>
<div> Arkaitz Zubiaga, University of Warwick, Coventry, UK</div>
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<pre class="moz-signature" cols="72">--
Thierry Declerck,
Senior Consultant at DFKI GmbH, Language Technology Lab
Stuhlsatzenhausweg, 3
D-66123 Saarbruecken
Phone: +49 681 / 857 75-53 58
Fax: +49 681 / 857 75-53 38
email: <a class="moz-txt-link-abbreviated" href="mailto:declerck@dfki.de">declerck@dfki.de</a>
-------------------------------------------------------------
Deutsches Forschungszentrum fuer Kuenstliche Intelligenz GmbH
Firmensitz: Trippstadter Strasse 122, D-67663 Kaiserslautern
Geschaeftsfuehrung:
Prof. Dr. Dr. h.c. mult. Wolfgang Wahlster (Vorsitzender)
Dr. Walter Olthoff
Vorsitzender des Aufsichtsrats:
Prof. Dr. h.c. Hans A. Aukes
Amtsgericht Kaiserslautern, HRB 2313
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