<html>
  <head>

    <meta http-equiv="content-type" content="text/html; charset=utf-8">
  </head>
  <body text="#000000" bgcolor="#FFFFFF">
    <p>
    </p>
    <p class="western" style="margin-bottom: 0cm; line-height: 100%"><font
        color="#000000"><font face="Times New Roman, serif"><span
            lang="en-US"><b>===========================================================<br>
              <br>
              SemDeep-3
              <br>
            </b></span></font></font><a
        href="http://www.dfki.de/semdeep-3/callforpapers.html"><font
          face="Times New Roman, serif"><span lang="en-US"><b>http://www.dfki.de/semdeep-3/callforpapers.html</b></span></font></a></p>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><br>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><font color="#000000"><font
        face="Times New Roman, serif"><span lang="en-US"><b>Workshop
            on Semantic Deep Learning </b></span></font></font><font
      color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US">collocated
          with </span></font></font><a href="http://coling2018.org/"
      target="_blank"><font face="Times New Roman, serif"><span
          lang="en-US">COLING</span></font></a><font color="#000000"><font
        face="Times New Roman, serif"><span lang="en-US">
          2018.
        </span></font></font><br>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><font color="#000000"><font
        face="Times New Roman, serif"><span lang="en-US"></span></font></font><br>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><font color="#000000"><font
        face="Times New Roman, serif"><span lang="en-US"></span></font></font><font
      color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"><b>===========================================================</b></span></font></font><font
      color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><br>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><font color="#000000"><font
        face="Times New Roman, serif"><span lang="en-US"></span></font></font><br>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><font color="#000000"><font
        face="Times New Roman, serif"><span lang="en-US">IMPORTANT
          DATES</span></font></font><br>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font><font color="#000000"><font
        face="Times New Roman, serif"><span lang="en-US">-----------------------</span></font></font><br>
    <font color="#000000"><font face="Times New Roman, serif"><span
          lang="en-US"></span></font></font>
    <p class="western" style="margin-bottom: 0cm; line-height: 100%"><font
        color="#000000"><font face="Times New Roman, serif"><span
            lang="en-US">
            STRICT Paper Submission
            Deadline: </span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US">May
            25, 2018</span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US">
            (11:50 pm CET)<br>
            Notification of Acceptance: </span></font></font><font
        color="#000000"><font face="Times New Roman, serif"><span
            lang="en-US">June
            20, 2018</span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US"><br>
            Camera-Ready
            Papers Due: </span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US">June
            30, 2018</span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US"><br>
            Workshop
            Dates: </span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US">August
            20</span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US">-21,
            2018<br>
            Conference Dates: August 20-25, 2018<br>
            <br>
            CALL FOR
            PAPERS <br>
            -----------------------<br>
            With the experiences gained
            from two previous workshops on Semantic Deep Learning, <br>
            we would
            like to take this endeavor one step further by providing a
            platform
            at COLING 2018 <br>
            where researchers and professionals in
            computational linguistics are invited to report results and
            <br>
            systems
            on the possible contributions of Deep Learning to classic
            problems in
            semantic applications, <br>
            such as meaning representation,
            dependency parsing, semantic role labelling, word sense
            <br>
            disambiguation, semantic relation extraction, statistical
            relational learning, knowledge base <br>
            completion, or semantically
            grounded inference. <br>
            <br>
            There are notable examples of
            contributions leveraging either deep neural architectures or
            distributed <br>
            representations learned via deep neural networks in
            the broad area of Semantic Web technologies. <br>
            These include,
            among others: (lightweight) ontology learning, ontology
            alignment ,
            ontology annotation, <br>
            and ontology prediction. Ontologies, on
            the other hand, have been repeatedly utilized as background
            <br>
            knowledge for machine learning tasks. As an example, there
            is a
            myriad of hybrid approaches for <br>
            learning embeddings by jointly
            incorporating corpus-based evidence and semantic resources.
            <br>
            This
            interplay between structured knowledge and corpus-based
            approaches
            has given way to <br>
            knowledge-rich embeddings, which in turn have
            proven useful for tasks such as hypernym discovery , <br>
            collocation
            discovery and classification, word sense disambiguation, and
            many
            others.<br>
            <br>
            We thus invite submissions that illustrate how NLP
            can benefit from the interaction between deep learning <br>
            and
            Semantic Web resources and technologies. At the same time,
            we are
            interested in submissions that <br>
            show how knowledge
            representation can assist in deep learning tasks deployed in
            the
            field of NLP <br>
            and how knowledge representation systems can build
            on top of deep learning results, for example <br>
            in the field of
            Neural Machine Translation (NMT). <br>
            <br>
            TOPICS OF
            INTEREST<br>
            -----------------------<br>
            Structured knowledge in
            deep learning:<br>
            - neural networks and logic rules for semantic
            compositionality<br>
            - learning and applying knowledge graph
            embeddings to NLP tasks<br>
            - learning semantic similarity and
            encoding distances as knowledge graph<br>
            - ontology-based text
            classification<br>
            - multilingual resources for neural
            representations of linguistics<br>
            - semantic role labeling<br>
            <br>
            Deep
            reasoning and inferences:<br>
            - commonsense reasoning and vector
            space models<br>
            - reasoning with deep learning methods <br>
            <br>
            Learning
            knowledge representations with deep learning<br>
            -  deep
            learning methods for knowledge-base completion<br>
            - deep learning
            models for learning knowledge representations from text<br>
            - deep
            learning ontological annotations <br>
            <br>
            Joint tasks:<br>
            - 
            information retrieval and extraction with knowledge graphs
            and deep
            learning models<br>
            - knowledge-based deep word sense disambiguation
            and entity linking<br>
            - investigation of compatibilities and
            incompatibilities between deep learning and Semantic Web
            approaches<br>
            <br>
            SUBMISSION
            INSTRUCTIONS<br>
            -----------------------<br>
            Authors are invited to
            submit papers describing original, unpublished<br>
            work, completed
            or in progress. The papers should be maximally 9<br>
            pages with
            maximally 2 additional pages for references. <br>
            <br>
            The COLING
            2018 templates must be used. Paper submission will be <br>
            electronic
            in PDF format through the SoftConf conference management
            system.<br>
            Workshop Proceedings will be published by COLING 2018.
            <br>
            <br>
            REVIEWING POLICY<br>
            ----------------<br>
            Reviewing
            will be double-blind, so authors need to conceal their<br>
            identity.
            The paper should not include the authors' names and
            affiliations, nor
            any acknowledgements. Limit anonymized<br>
            self-references only to
            articles that are relevant for reviewers.<br>
            <br>
            WORKSHOP
            ORGANIZERS<br>
            ----------------<br>
            Luis Espinosa Anke, Cardiff
            University, UK<br>
            Thierry Declerck, German Research Centre for
            Artificial Intelligence (DFKI GmbH), Saarbrücken, Germany<br>
            Dagmar
            Gromann, Technical University Dresden (TU Dresden), Dresden,
            Germany<br>
            <br>
            PROGRAM COMMITTEE<br>
            ----------------<br>
            Kemo
            Adrian, Artificial Intelligence Research Institute
            (IIIA-CSIC),
            Bellaterra, Spain<br>
            Luu Ahn Tuan (Institute for Infocomm Research,
            Singapore)<br>
            Miguel Ballesteros, IBM T.J. Watson Research Center,
            Yorktown Heights, NY, USA<br>
            Jose Camacho-Collados, Sapienza
            University of Rome, Rome, Italy<br>
            Gerard Casamayor, Pompeu Fabra
            University, Spain<br>
            Stamatia Dasiopoulou, Pompeu Fabra University,
            Spain<br>
            Maarten Grachten, Austrian Research Institute for AI,
            Vienna, Austria<br>
            Dario Garcia-Casulla, Barcelona Supercomputing
            Center (BSC), Barcelona, Spain<br>
            Jorge Gracia Del R´ıo,
            Ontology Engineering Group, UPM, Spain<br>
            Jindrich Helcl, Charles
            University, Prague, Czech Republic<br>
            Dirk Hovy, Computer Science
            Department of the University of Copenhagen, Denmark<br>
            Petya
            Osenova, Bulgarian Academy of Sciences, Sofia</span></font></font><font
        color="#000000"><font face="Times New Roman, serif"><span
            lang="en-US">,
            Bulgaria<br>
            Martin Riedel, Hamburg University, Germany<br>
            Stephen
            Roller, Facebook AI Research<br>
            Francesco Ronzano, Pompeu Fabra
            University, Barcelona, Spain<br>
            Enrico Santus, The Hong Kong
            Polytechnic University, Hong Kong<br>
            Francois Scharffe, Axon
            Research, New York, USA<br>
            Vered Shwartz, Bar-Ilan University,
            Ramat Gan, Isreal<br>
            Kiril Simov, Bulgarian Academy of Sciences,
            Sofia</span></font></font><font color="#000000"><font
          face="Times New Roman, serif"><span lang="en-US">,
            Bulgaria<br>
            Michael Spranger, Sony Computer Science Laboratories
            Inc., Tokyo, Japan<br>
            Armand Vilalta, Barcelona Supercomputing
            Center (BSC), Barcelona, Spain<br>
            Arkaitz Zubiaga, University of
            Warwick, Coventry, UK</span></font></font></p>
    <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
-------------------------------------------------------------</pre>
  </body>
</html>