<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">International Workshop on Deep Learning for Knowledge Graphs (DL4KG)</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class="">Web: <span class="c4" style="text-decoration-skip-ink: none; color: rgb(17, 85, 204); text-decoration: underline;"><a class="c6" href="https://www.google.com/url?q=https://alammehwish.github.io/dl4kg-eswc/&sa=D&ust=1548668013583000" style="color: inherit; text-decoration: inherit;">https://alammehwish.github.io/dl4kg-eswc/</a></span> <span class="c0" style="vertical-align: baseline; font-size: 11pt;"> </span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">In conjunction with ESWC 2019, 2nd-6th June 2019, Portorož, Slovenia</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Workshop Overview</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">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.</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">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.</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">This workshop, in the wake of other similar efforts at previous Semantic Web conferences such as ESWC2018 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.</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Topics of Interest</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Topics of interest for this first workshop on Deep Learning for Knowledge Graphs and Semantic Technologies, include but are not limited to the following fields and problems:</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- New approaches for the combination of Deep Learning and Knowledge Graphs:</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Methods for generating Knowledge Graph (node) embeddings</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Scalability issues</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Temporal Knowledge Graph Embeddings</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Novel approaches</span></div><p class="c1 c7 c5" style="margin: 0px 0px 0px 72pt; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Applications of the combination of Deep Learning and Knowledge Graphs:</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Recommender Systems leveraging Knowledge Graphs</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Link Prediction and completing KGs</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Ontology Learning and Matching exploiting Knowledge Graph-Based Embeddings</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Knowledge Graph-Based Sentiment Analysis</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Natural Language Understanding/Machine Reading</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Question Answering exploiting Knowledge Graphs and Deep Learning</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Entity Linking</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Trend Prediction based on Knowledge Graphs Embeddings</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Domain-Specific Knowledge Graphs (e.g., Scholarly, Biomedical, Musical)</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; text-indent: 36pt; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Applying knowledge graph embeddings to real world scenarios.</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">------------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Important Dates</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">------------------------------------------------------------------------------------</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class="">- <span class="c0" style="vertical-align: baseline; font-size: 11pt;">Friday March 1st, 2019: Full, Short and Position paper submission deadline<br class="">- Friday March 29th, 2019: Notification of Acceptance<br class="">- Friday April 12th, 2019: Camera-ready paper due<br class="">- Sunday June 2nd, 2019: ESWC 2019 Workshop day<br class=""></span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Submissions</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Papers must comply with the LNCS style and can fall in one of the following categories:</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Full research papers (8-10 pages)</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Short research papers (4-6 pages)</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Position papers (2 pages)</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Submissions will be sent via EasyChair:</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c4" style="text-decoration-skip-ink: none; color: rgb(17, 85, 204); text-decoration: underline;"><a class="c6" href="https://www.google.com/url?q=https://easychair.org/conferences/?conf%3Ddl4kg2019&sa=D&ust=1548668013589000" style="color: inherit; text-decoration: inherit;">https://easychair.org/conferences/?conf=dl4kg2019</a></span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">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.</span></div><p class="c1 c5" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; height: 11pt; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">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.</span></div><p class="c1" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"> </span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">Organization</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">---------------------------------------------------------------------------------</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Mehwish Alam, ST Lab, CNR Rome, Italy</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Davide Buscaldi, LIPN, Université Paris 13, France</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Michael Cochez, Fraunhofer Institute for Applied Information Technology FIT, Germany</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Francesco Osborne, Knowledge Media Institute, (KMi), The Open University, UK</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Diego Reforgiato Recupero, University of Cagliari, Italy</span></div><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class=""><span class="c0" style="vertical-align: baseline; font-size: 11pt;">- Harald Sack, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Germany</span></div><p class="c1" style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;"><span class="c0" style="vertical-align: baseline; font-size: 11pt;"></span></p><div style="margin: 0px; font-size: 11pt; font-family: Arial; padding-top: 0pt; padding-bottom: 0pt; line-height: 1.15; orphans: 2; widows: 2; font-variant-ligatures: normal;" class="">More information about DL4KG 2019 is available at: <span class="c4" style="text-decoration-skip-ink: none; color: rgb(17, 85, 204); text-decoration: underline;"><a class="c6" href="https://www.google.com/url?q=https://alammehwish.github.io/dl4kg-eswc/&sa=D&ust=1548668013592000" style="color: inherit; text-decoration: inherit;">https://alammehwish.github.io/dl4kg-eswc/</a></span><span class="c0" style="vertical-align: baseline; font-size: 11pt;"> </span></div></body></html>