- From: Thierry Declerck <declerck@dfki.de>
- Date: Tue, 27 Mar 2018 18:32:53 +0200
- To: semantic-web@w3.org, PROLE@babel.ls.fi.upm.es, iiia@iiia.csic.es, sigsem@aclweb.org, machine-learning@googlegroups.com, sigir@acm.org
- Message-ID: <c4d83b86-59af-1bf5-21c4-65936f36f847@dfki.de>
Sorry for multiple postings *===========================================================* Second Call for Papers for *SemDeep-3 * ***http://www.dfki.de/semdeep-3/callforpapers.html* *Workshop on Semantic Deep Learning *collocated with COLING 2018. *===========================================================* IMPORTANT DATES ----------------------- STRICT Paper Submission Deadline: May 25, 2018 (11:50 pm CET) Notification of Acceptance: June 20, 2018 Camera-Ready Papers Due: June 30, 2018 Workshop Dates: August 20-21, 2018 Conference Dates: August 20-25, 2018 CALL FOR PAPERS ----------------------- With the experiences gained from two previous workshops on Semantic Deep Learning, we would like to take this endeavor one step further by providing a platform at COLING 2018 where researchers and professionals in computational linguistics are invited to report results and systems on the possible contributions of Deep Learning to classic problems in semantic applications, such as meaning representation, dependency parsing, semantic role labelling, word sense disambiguation, semantic relation extraction, statistical relational learning, knowledge base completion, or semantically grounded inference. There are notable examples of contributions leveraging either deep neural architectures or distributed representations learned via deep neural networks in the broad area of Semantic Web technologies. These include, among others: (lightweight) ontology learning, ontology alignment , ontology annotation, and ontology prediction. Ontologies, on the other hand, have been repeatedly utilized as background knowledge for machine learning tasks. As an example, there is a myriad of hybrid approaches for learning embeddings by jointly incorporating corpus-based evidence and semantic resources. This interplay between structured knowledge and corpus-based approaches has given way to knowledge-rich embeddings, which in turn have proven useful for tasks such as hypernym discovery , collocation discovery and classification, word sense disambiguation, and many others. We thus invite submissions that illustrate how NLP can benefit from the interaction between deep learning and Semantic Web resources and technologies. At the same time, we are interested in submissions that show how knowledge representation can assist in deep learning tasks deployed in the field of NLP and how knowledge representation systems can build on top of deep learning results, for example in the field of Neural Machine Translation (NMT). TOPICS OF INTEREST ----------------------- Structured knowledge in deep learning: - neural networks and logic rules for semantic compositionality - learning and applying knowledge graph embeddings to NLP tasks - learning semantic similarity and encoding distances as knowledge graph - ontology-based text classification - multilingual resources for neural representations of linguistics - semantic role labeling Deep reasoning and inferences: - commonsense reasoning and vector space models - reasoning with deep learning methods Learning knowledge representations with deep learning - deep learning methods for knowledge-base completion - deep learning models for learning knowledge representations from text - deep learning ontological annotations Joint tasks: - information retrieval and extraction with knowledge graphs and deep learning models - knowledge-based deep word sense disambiguation and entity linking - investigation of compatibilities and incompatibilities between deep learning and Semantic Web approaches SUBMISSION INSTRUCTIONS ----------------------- Authors are invited to submit papers describing original, unpublished work, completed or in progress. The papers should be maximally 9 pages with maximally 2 additional pages for references. The COLING 2018 templates must be used. Paper submission will be electronic in PDF format through the SoftConf conference management system. Workshop Proceedings will be published by COLING 2018. REVIEWING POLICY ---------------- Reviewing will be double-blind, so authors need to conceal their identity. The paper should not include the authors' names and affiliations, nor any acknowledgements. Limit anonymized self-references only to articles that are relevant for reviewers. WORKSHOP ORGANIZERS ---------------- Luis Espinosa Anke, Cardiff University, UK Thierry Declerck, German Research Centre for Artificial Intelligence (DFKI GmbH), Saarbrücken, Germany Dagmar Gromann, Technical University Dresden (TU Dresden), Dresden, Germany PROGRAM COMMITTEE ---------------- Kemo Adrian, Artificial Intelligence Research Institute (IIIA-CSIC), Bellaterra, Spain Luu Ahn Tuan (Institute for Infocomm Research, Singapore) Miguel Ballesteros, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA Jose Camacho-Collados, Sapienza University of Rome, Rome, Italy Gerard Casamayor, Pompeu Fabra University, Spain Stamatia Dasiopoulou, Pompeu Fabra University, Spain Maarten Grachten, Austrian Research Institute for AI, Vienna, Austria Dario Garcia-Casulla, Barcelona Supercomputing Center (BSC), Barcelona, Spain Jorge Gracia Del Río, University of Zaragoza, Spain Jindrich Helcl, Charles University, Prague, Czech Republic Dirk Hovy, Computer Science Department of the University of Copenhagen, Denmark Petya Osenova, Bulgarian Academy of Sciences, Sofia, Bulgaria Martin Riedel, Hamburg University, Germany Stephen Roller, Facebook AI Research Francesco Ronzano, Pompeu Fabra University, Barcelona, Spain Enrico Santus, The Hong Kong Polytechnic University, Hong Kong Francois Scharffe, Axon Research, New York, USA Vered Shwartz, Bar-Ilan University, Ramat Gan, Isreal Kiril Simov, Bulgarian Academy of Sciences, Sofia, Bulgaria Michael Spranger, Sony Computer Science Laboratories Inc., Tokyo, Japan Armand Vilalta, Barcelona Supercomputing Center (BSC), Barcelona, Spain Arkaitz Zubiaga, University of Warwick, Coventry, UK * * -- 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:declerck@dfki.de ------------------------------------------------------------- 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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Received on Tuesday, 27 March 2018 16:33:21 UTC