LinkingLOD: interlinking knowledge bases

In LinkingLOD we will research and develop new Link Discovery methods, in particular methods which will use property semantics, link quality improvements as well as active learning to produce results beyond the state of the art. In addition to that, the resulting methods will be integrated into a Link Discovery framework.

  • duration: 2 years
  • funded by German Research Foundation (Deutsche Forschungsgemeinschaft DFG)

Publications

by (Editors: ) [BibTex of ]

News

SANSA 0.2 (Semantic Analytics Stack) Released ( 2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann)

2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann

The AKSW and Smart Data Analytics groups are happy to announce SANSA 0.2 – the second release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.2 (Semantic Analytics Stack) Released"

AKSW at ESWC 2017 ( 2017-06-12T10:53:35+02:00 Christopher Schulz)

2017-06-12T10:53:35+02:00 Christopher Schulz

Hello Community! The ESWC 2017 just ended and we give a short report of the course at the conference, especially regarding the AKSW-Group. Our members Dr. Muhammad Saleem, Dr. Mohamed Ahmed Sherif, Claus Stadler, Michael Röder, Prof. Dr. Read more about "AKSW at ESWC 2017"

Four papers accepted at WI 2017 ( 2017-06-10T15:01:31+02:00 Christopher Schulz)

2017-06-10T15:01:31+02:00 Christopher Schulz

Hello Community! We proudly announce that The International Conference on Web Intelligence (WI) accepted four papers by our group. The WI takes place in Leipzig between the 23th – 26th of August. Read more about "Four papers accepted at WI 2017"

AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data. ( 2017-05-26T13:51:11+02:00 by Diego Moussallem)

2017-05-26T13:51:11+02:00 by Diego Moussallem

At the AKSW Colloquium, on Monday 29th of May 2017, 3 PM, Diego Moussallem will present two papers related to his topic. First paper titled “Using BabelNet to Improve OOV Coverage in SMT” of Du et al. Read more about "AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data."

SML-Bench 0.2 Released ( 2017-05-11T13:01:45+02:00 by Patrick Westphal)

2017-05-11T13:01:45+02:00 by Patrick Westphal

Dear all, we are happy to announce the 0.2 release of SML-Bench, our Structured Machine Learning benchmark framework. SML-Bench provides full benchmarking scenarios for inductive supervised machine learning covering different knowledge representation languages like OWL and Prolog. Read more about "SML-Bench 0.2 Released"