RW 2018 : RW2018: THE 14th INTERNATIONAL REASONING WEB SUMMER SCHOOL | Luxembourg, 22-26 Sep 2018
Call For Papers
Please find below the CFA for the 14th INTERNATIONAL REASONING WEB SUMMER SCHOOL (RW2018) to be held in Luxembourg as part of Luxembourg Logic for AI (LuxLogAI) summit.
For more information about LuxLogAI visit: https://luxlogai.uni.lu
Please feel free to distribute the CFA.
SECOND CALL FOR APPLICATIONS
THE 14th INTERNATIONAL REASONING WEB SUMMER SCHOOL - RW 2018
Luxembourg, 22 - 26 Sep 2018
The Reasoning Web Summer School 2018, as part of the annual series of summer schools, welcomes applications from Master and PhD students as well as from postdoctoral researchers, young researchers, and senior researchers wishing to learn about the research areas of Semantic Web and related sub-areas such as Linked Data, Knowledge Graphs, Ontologies, Rules, and Logic.
Participants to the summer school will have the opportunity to attend lectures, to be involved in working groups concerning small case studies or research tasks to focus on and to be presented in a final plenary session, discuss ideas and closely interact with leading researchers in the Semantic Web community and beyond.
This year’s school program will include the following topics and lecturers:
• Information Extraction for Knowledge Graph Construction - Philipp Cimiano, University of Bielefeld
• Semantic Data in the Cloud - Steffen Staab and Daniel Janke, University of Koblenz Landau
• Machine Learning with and for Knowledge Graphs - Heiko Paulheim, University of Mannheim
• Stream Reasoning - Emanuele Della Valle, Politecnico di Milano
• Learning and Reasoning in Knowledge Graphs - Daria Stepanova, Max Planck Institute
• Normative reasoning for the Semantic Web - Guido Gorvernatori, Commonwealth Scientific and Industrial Research Organisation
• Efficient SPARQL queries on very large Knowledge Graphs - Hannah Bast, University of Freiburg
• Reasoning at Scale - Jacopo Urbani, Vrije Universiteit Amsterdam
• Deep Learning for the Semantic Web - Thomas Lukasiewicz, University of Oxford
Although no specific background knowledge is required for attending the summer school, basics of Knowledge Representation and the Semantic Web (including technologies such as RDF, OWL, etc.) will be helpful for benefitting from the contents of the school. Students are also committed to a full participation for the whole duration of the school.
The registration fees for attending the RW Summer School will be 300 EUR (if your RW registration is bundled with the one for RuleML-RR) and 350 EUR (if you choose to only register for RW), respectively. This includes all lectures and teaching sessions, lunches, coffee breaks, school proceedings and a social event.
A limited number of grants will be available for selected students who would otherwise not be able to attend the summer school. As such, please ask for financial support in your application (see “Application” section) only if this is the necessary condition for you to participate in the summer school.
Students and researchers interested in participating need to submit their application by June 30, 2018 via EasyChair using the following link: https://easychair.org/conferences/?conf=rw2018.
The application should consist of a single pdf file that includes:
• A single-page CV.
• A short motivation letter of up to 300 words stating research interests and reasons for the willingness to attend the summer school.
• Necessity for a visa to enter Luxembourg (Yes or No). If required, invitation letters will be set up.
• Necessity for financial support. A limited number of travel grants will be provided, please thus ask for financial support only if this is a necessary condition for you to join the school. Please add a rough quote for your estimated expenses (travel + hotel costs) to your application in this case.
Notifications about the selection results will be sent by July 15, 2018
For any questions, please contact: email@example.com
Claudia d’Amato and Martin Theobald
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Big Data and Data Science Research Group - ILIAS Lab - Csc Research Unit
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