[DL] CFP: 4th Workshop on Semantic Deep Learning (SemDeep-4) at ISWC 2018

[Luis Espinosa-Anke]

CALL FOR PAPERS OF THE

4TH WORKSHOP ON SEMANTIC DEEP LEARNING (SemDeep-4) @ ISWC 2018

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 appeal to both Semantic Web and Computational Linguistic communities are addressed and discussed.


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 graph

  *   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/


IMPORTANT DATES

*Firm* Submission deadline: June 1, 2018

Notification of acceptance: June 27, 2018

Camera-ready version: July 20, 2018

Workshop dates: October 8-9, 2018

SUBMISSION INSTRUCTIONS

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 pages)

All papers need to follow the LCNS formatting guidelines. The demo jam takes 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.


ORGANIZING COMMITTEE

Luis Espinosa Anke, Cardiff University, UK

Thierry Declerck, DFKI GmbH, Germany

Dagmar Gromann, Technical University Dresden, Germany


PROGRAM COMMITTEE

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 Laboratory, 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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