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The workshop ‘Knowledge Representation & Representation Learning (KR4L)’ will be held in conjunction with the 24th European Conference on Artificial Intelligence (ECAI 2020). There currently is a perceived disconnect between the areas of Representation Learning (RL) and Knowledge Representation and Reasoning (KRR). Most of the research is currently concentrated on one area or the other, yet arguably representation learning is central to make use of knowledge representation and reasoning techniques in modern, scalable AI applications. This is particularly the case, but not restricted to, the area of Knowledge Graphs. We welcome submission of research contributions.

Call for Topics:

Important Dates:

Senior Committee:


Publicity Chair:


Session 1:

12:00 - 12:15 Plenary Talk and Opening Emanuel Sallinger, TU Wien and University of Oxford
12:15 - 12:30 Paper Presentation Traversing Knowledge Graphs with Good Old (and New) Joins
12:30 - 12:45 Paper Presentation Cluster Discovery from Sensor Data Incorporating Expert Knowledge
12:45 - 13:00 Panel Discussion 1 Emerging Topics in Academia and Industry

Session 2:

13:15-13:30 Invited Talk Adriano Vlad, University of Oxford
13:30-13:45 Paper Presentation The Effect of Rule Injection in Leakage Free Dataset
13:45-14:00 Paper Presentation A Performance Strategy: Multiple Slices of a KGE Model in Low Dimensions

Session 3:

14:15-14:30 Paper Presentation Blockchains as Knowledge Graphs–Blockchains for Knowledge Graphs (Vision Paper)
14:30-14:45 Paper Presentation An Evolutionary Algorithm for Rule Learning over Knowledge Graphs
14:45-15:00 Panel Discussion 2 and Closing Future Directions - Looking Ahead


All papers must represent unpublished work that is not currently under review. Papers will be evaluated according to their significance, originality, technical content, style, clarity, and relevance to the workshop. Papers have to be submitted through EasyChair

Paper Type:

KR4L welcomes the submission of research results and application papers dealing with the aforementioned topics. We encourage theoretical, methodological, empirical and applications papers. We appreciate the submission of papers incorporating links to datasets and other material used for evaluation as well as to live demos and software source code. We invite four kinds of submissions: full research papers (minimum 8 pages, maximum 12 pages) position papers (minimum 4 pages, maximum 6 pages) demo/poster papers (minimum 4 pages, maximum 6 pages) All the aforementioned limits include references.

Submission Template:

Authors are required to follow the LNCS template

Accepted papers will be published at ceur-ws

Programme Committee of KR4L