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, Dagmar
EXTENDED DEADLINE OF THE
4TH WORKSHOP ON SEMANTIC DEEP LEARNING (SemDeep-4) @ ISWC 2018
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 Linguistics 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/ <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 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.
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 Laboratory, Thessanloniki, Greece Brigitte Krenn, Austrian Research Institute for AI, Vienna, Austria Jose Moreno, Universite Paul Sabatier, IRIT, Toulouse, France Luis Nieto Piņa, 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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