[open-linguistics] SemDeep-4 at ISWC Deadline Extension

Thierry Declerck declerck at dfki.de
Sat Jun 2 10:33:22 UTC 2018

Dear colleagues,

Please be informed that we extended the deadline of the 4th Workshop on 
Semantic Deep Learning (SemDeep-4) collocated with ISWC to June 4.

Kind regards,
Thierry, Dagmar, Luis



Monterey, California

Semantic Web (SW) Technologies and Deep Learning (DL) share the goal of 
creating intelligent artifacts. Both disciplines have had a remarkable 
impact in data and knowledge analysis, as well as knowledge 
representation, and in fact constitute two complementary directions for 
modeling expressible linguistic phenomena and solving semantically 
complex problems. In this context, and following the main foundations 
set in past editions, SemDeep-4 aims to bring together SW and DL 
research as well as industrial communities.

SemDeep is interested in contributions of DL to classic problems in 
semantic applications, such as: (semi-automated) ontology learning, 
ontology alignment, ontology annotation, duplicate recognition, ontology 
prediction, knowledge base completion, relation extraction, and 
semantically grounded inference, among many others. At the same time, we 
invite contributions that analyse the interaction of SW technologies and 
resources with DL architectures, such as knowledge-based embeddings, 
collocation discovery and classification, or lexical entailment, to name 
only a few. This workshop seeks to provide an
invigorating environment where semantically challenging problems which 
to both Semantic Web and Computational Linguistics communities are 
addressed and

We invite submissions on any approach combining Semantic Web 
technologies and
Deep Learning and suggest the following topics.

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 
   *   ontology-based text classification
   *   multilingual resources for neural representations of linguistics
   *   semantic role labeling

Reasoning and inferences and deep learning

   *   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 ontology learning
   *   deep learning models for learning knowledge representations from text
   *   deep learning ontological annotations

Website: http://www.dfki.de/semdeep-4/


*Firm* Submission deadline: June 4, 2018
Notification of acceptance: June 27, 2018
Camera-ready version: July 20, 2018
Workshop dates: October 8-9, 2018


We invite three types of submissions:

   1.  Long papers with new results (max. 12 pages)

   2.  Short papers presenting innovative not fully empirically 
validated ideas
or position papers (max. 4 pages)

   3.  Short descriptions of systems that participate in the demo jam 
(max. 4

All papers need to follow the LCNS formatting guidelines. The demo jam 
the format of system demonstrations where the theoretical background may be
explained in the presentation slot and the functioning of the system is
showcased in a 5 minute demo.


Luis Espinosa Anke, Cardiff University, UK
Thierry Declerck, DFKI GmbH, Germany
Dagmar Gromann, Technical University Dresden, Germany


Stephan Baier, Ludwig Maximilian University, Munich, Germany
Michael Cochez, RWTH University Aachen, Germany
Brigitte Grau, LIMSI, CNRS, Orsay, France
Wei Hu, Nanjing University, China
Rezaul Karim, RWTH University Aachen, Germany
Stratos Kontopoulos, Multimedia Knowledge \& Social Media Analytics 
Thessanloniki, Greece
Brigitte Krenn, Austrian Research Institute for AI, Vienna, Austria
Jose Moreno, Universite Paul Sabatier, IRIT, Toulouse, France
Luis Nieto Piña, University of Goteborg, Goteburg, Sweden
Sergio Oramas, Universitat Pompeu Fabra, Barcelona, Spain
Alessandro Raganato, Sapienza University of Rome, Rome, Italy
Simon Razniewksi, Max-Planck-Institute, Germany

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