A Know-Center paper by authors Stefan Klampfl and Roman Kern from the Knowledge Discovery Team has won multiple awards at the „Semantic Publishing Challenge“ which took place as part of the ESCW 2016 conference. The paper not only received an award for the „Most Innovative Approach“, it was also nominated for the "Best ESWC 2016 Challenge Paper" and ultimately reached third place in the overall ranking of „Best-Performing Tools“.
The European Semantic Web Conference (ESWC) is Europe’s most important conference on semantic web technologies. This year, the A-rated conference was held from May 29 to June 2, 2016 near Heraklion, Greece (Crete).
As part of the ESWC 2016, the “Semantic Publishing Challenge 2016” took place, where the Know-Center Paper “Reconstructing the Logical Structure of a Scientific Publication using Machine Learning” by Stefan Klampfl and Roman Kern was presented in the form of a short presentation and a poster.
The aim of this challenge was to automatically extract specific information about the context and the internal structure of scientific publications from PDF (e.g. authors, affiliations, section headings, captions of tables and figures) and provide the results in the form of a linked data set. A training and evaluation data set of PDF documents as well as the SPARQL queries to be executed and the target format were provided for participants.
The Know-Center contribution builds on its own contribution to the previous edition of this challenge and also on existing work in the field of PDF extraction, which has been carried out in previous research projects (CODE) at the Know-Center.
Ultimately, the paper of the Know-Center authors was awarded not only the award for the “Most Innovative Approach”, but also reached 3rd place in the overall ranking “Best Performing Tools” of the Semantic Publishing Challenge 2016. In addition, the paper was also nominated for the “Best ESWC 2016 challenge Paper”.
Congratulations to this great success!
Stefan Klampfl and Roman Kern. Reconstructing the Logical Structure of a Scientific Publication using Machine Learning. In The Semantic Web: ESWC 2016 Challenges. Volume editors: Harald Sack, Stefan Dietze, Anna Tordai, Christoph Lange