Workshop at ESWC 2019 on
Deep Learning for Knowledge Graphs
More Details!


Over the past years there has been a rapid growth in the use and the importance of Knowledge Graphs (KGs) along with their application to many important tasks. KGs are large networks of real-world entities described in terms of their semantic types and their relationships to each other. On the other hand, Deep Learning methods have also become an important area of research, achieving some important breakthrough in various research fields, especially Natural Language Processing (NLP) and Image Recognition.

In order to pursue more advanced methodologies, it has become critical that the communities related to Deep Learning, Knowledge Graphs, and NLP join their forces in order to develop more effective algorithms and applications. This workshop, in the wake of other similar efforts at previous Semantic Web conferences such as ESWC2018 as DL4KGs and ISWC2018, aims to reinforce the relationships between these communities and foster inter-disciplinary research in the areas of KG, Deep Learning, and Natural Language Processing.

Topics of Interest

New approaches for combining Deep Learning and Knowledge Graphs
  • Methods for generating Knowledge Graph (node) embeddings
  • Scalability issues
  • Temporal Knowledge Graph Embeddings
  • Novel approaches
Applications of combining Deep Learning and Knowledge Graphs
  • Recommender Systems leveraging Knowledge Graphs
  • Link Prediction and completing KGs
  • Ontology Learning and Matching exploiting Knowledge Graph-Based Embeddings
  • Knowledge Graph-Based Sentiment Analysis
  • Natural Language Understanding/Machine Reading
  • Question Answering exploiting Knowledge Graphs and Deep Learning
  • Entity Linking
  • Trend Prediction based on Knowledge Graphs Embeddings
  • Domain Specific Knowledge Graphs (e.g., Scholarly, Biomedical, Musical)
  • Applying knowledge graph embeddings to real world scenarios.

Submission Details

Papers must comply with the LNCS style
Papers are submitted in PDF format via the workshop’s EasyChair submission pages

Submissions can fall in one of the following categories:
  • Full research papers (8-10 pages)
  • Short research papers (4-6 pages)
  • Position papers (2 pages)

Accepted papers (after blind review of at least 3 experts) will be published by CEUR–WS. The best paper (according to the reviewers’ rate) will be published within the main conference proceedings.

At least one of the authors of the accepted papers must register for the workshop (pre-conference only option) to be included into the workshop proceedings.

Important Dates

  • Friday March 1st, 2019  Friday March 7th, 2019 Friday March 15th, 2019: Full, Short and Position paper submission deadline
  • Friday March 29th, 2019 Friday April 5th, 2019: Notification of Acceptance
  • Friday April 12th, 2019 Friday April 19th, 2019: Camera-ready paper due
  • Sunday June 2nd, 2019: ESWC 2019 Workshop day

Keynote Speaker

Volker Tresp

Siemens, Munich, Germany


Smart Perception with Deep Learning and Knowledge Graphs



Short Biography

Volker Tresp is Distinguished Research Scientist at Siemens Corporate Technology and Professor at the Ludwig Maximilian University in Munich. He received his Ph.D. degree from Yale University in 1989 and joined Siemens the same year. At Siemens he has been the head of various research teams in machine learning, data analytics and knowledge representation. He filed more than 70 patent applications, published more than 150 scientific articles, and was inventor of the year of Siemens in 1996. The company Panoratio is a spin-off out of his team. At the Ludwig Maximilian University he teaches an annual course on Machine Learning. His research focus in recent years has been “Machine Learning and Deep Learning with Information Networks” for modelling Knowledge Graphs, medical decision processes, perception, and cognitive memory functions.

Workshop Program and Proceedings


Organizing Committee

Mehwish Alam

ST-Lab, CNR, Rome, Italy

Davide Buscaldi

Labortoire d'Informatique Paris Nord (LIPN), Paris, France

Michael Cochez

Fraunhofer Institute for Applied Information Technology FIT, Germany

Francesco Osborne

Knowledge Media Institute (KMi), The Open University, UK

Diego Reforgiato Recupero

University of Cagliari, Cagliari, Italy

Harald Sack

FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Germany

Program Committee

  • Erik Cambria, Nanyang Technological University, Singapore.
  • Sergio Consoli, Joint Research Centre, Italy.
  • Philippe Cudré-Mauroux, University of Fribourg, Switzerland.
  • Danilo Dessi', University of Cagliari, Italy.
  • Stefan Dietze, L3S Hannover, Germany.
  • Mauro Dragoni, Fondazione Bruno Kessler.
  • Aldo Gangemi, University of Bologna, Italy.
  • Luis Galarraga, INRIA, Rennes, France.
  • Pascal Hitzler, Wright State University, USA.
  • Maria Koutraki, FIZ-Karlsruhe, Karlsruhe Institute of Technology (KIT), Germany.
  • Gerard de Melo, Rutgers University, USA.
  • Amedeo Napoli, LORIA, CNRS, France.
  • Andrea Nuzzolese, , National Council of Research, Italy.
  • Valentina Presutti, National Council of Research, Italy.
  • Achim Rettinger, AIFB-KIT, Germany.%to confirm
  • Petar Ristoski, IBM research, USA.
  • Roberto Saia, University of Cagliari, Italy.
  • Fabian Suchanek, Telecom ParisTech University, France.
  • Veronika Thost, IBM Research, USA.
  • Volker Tresp, Siemens AG, Germany.
  • Max Welling, University of Amsterdam, Netherlands.