[CfP] Workshop on Semantic Deep Learning

First Call for Papers for the ESWC Workshop on Semantic Deep Learning (SemDeep-17) 

*** DEADLINE Friday 3 March 2017 ALL submissions*** 

Scope: 

Semantic Deep Learning aims to bring together Semantic Web and deep learning methods, technologies, and resources. Semantic Web and deep learning research share the goal of creating intelligent artefacts that emulate human capacities, such as reasoning, validating, and predicting. Both fields have been considerably impacting data and knowledge analysis as well as representation. 

Deep learning represents a set of machine learning algorithms that learn data representations by means of transformations with multiple processing layers. This algorithmic set has frequently been applied to feature learning, such as morphological tagging or speaker verification. Semantic Web technologies and knowledge representation boost the re-use and sharing of knowledge in a structured and machine-readable fashion. Semantic resources, such as WikiData or BabelNet, and methods have been successfully applied to semantic data mining. 

Machine learning has been successfully applied to (semi-automated) ontology learning, ontology alignment, ontology annotation, duplicate recognition, and ontology prediction. Ontologies have been repeatedly utilized as input to machine learning tasks and as background knowledge to guide such tasks. Hybrid approaches, such as knowledge graph embeddings, hold the potential of improving the effectiveness of knowledge-related tasks. This workshop offers a platform for discussing such hybrid approaches and for fostering future collaborations between those two fields. 

Workshop Topics: 

Topics of interest for papers, posters, and software demonstrations of original and unpublished work include, but are not limited to: 

- learning and applying knowledge graph embeddings 
- deep learning and Semantic Web technologies for entity disambiguation 
- deep learning technologies for ontology learning 
- embedding-based relation prediction 
- ontology matching and alignment using deep learning 
- word embeddings for learning annotations 
- ontology-based clustering 
- ontology-based classification 
- Deep Structured Semantic Models (DSSM) for the Semantic Web 
- deep learning and semantic data for 
o Machine Translation, 
o Question & Answering, 
o Information Extraction 

Accepted Submissions: 

Full papers (max. 12 pages): mature research work that has been subject to evaluation 
Posters/demos (max. 4 pages): early results, working demos, software, services and platforms 

Submission Procedure: 

Submissions should not exceed 12 pages and are to be formatted according to the Springer LNCS template . Papers should be submitted in PDF format to EasyChair . 

Important dates: 

Paper submission deadline: Friday March 3, 2017 - 23:59 Hawaii Time 
Notifications: Friday March 31, 2017 
Camera-ready version: Thursday April 13, 2017 - 23:59 Hawaii Time 
Workshop camera-ready proceedings due: May 1, 2017 - 23:59 Hawaii Time 
Workshop days: May 28 or 29, 2017 

Location: 

Semantic Deep Learning ( http://semdeep.iiia.csic.es/ ) is a workshop collocated with the European Semantic Web Conference ( http://2017.eswc-conferences.org/ ) and will take place in Portoroz, Slovenia on 28 May or 29 May 2017 . 

Organizing Committee: 

Georg Heigold, DFKI GmbH, Germany 
Dagmar Gromann, Artificial Intelligence Research Institute (IIIA - CSIC), Spain 
Thierry Declerck, Saarland University & DFKI GmbH, Germany 

Program Committee: 

Arkaitz Zubiaga, University of Warwick, UK 
Brigitte Krenn, Austrian Research Institute for AI, Vienna, Austria 
Felix Sasaki, W3C & DFKI GmbH; Berlin, Germany 
John McCrae, Insight Centre for Data Analytics, Galway, Ireland 
Jonathan Dehdari, DFKI GmbH, Germany 
Laura Tolosi-Halacheva, Ontotext, Sofia, Bulgaria 
Leon Derczynski, University of Sheffield, UK 
Luis Espinosa Anke, TALN-DTIC, Universitat Pompeu Fabra, Spain 
Martin Riedl, Language Technology Group, U. Hamburg, Germany 
Octavia-Maria Șulea, Computational Linguistics, Saarland University 
Sándor Darányi,University of Borås, Sweden 
Stratos Kontopoulos, Multimedia Knowledge & Social Media Analytics Laboratory, Thessanloniki, Greece 
Enrico Santus Aversano, The Hong Kong Polytechnic University, Hong Kong 
Michael Spranger, Sony Computer Science Laboratories Inc., Tokyo, Japan 
Vered Shwartz, Bar-Ilan University, Ramat Gan, Isreal