Big data plays a relevant role in promoting both manufacturing and scientific development through industrial digitization and emerging interdisciplinary research. Semantic web technologies have also experienced great progress, and scientific communities and practitioners have contributed to the problem of big data management with ontological models, controlled vocabularies, linked datasets, data models, query languages, as well as tools for transforming big data into knowledge from which decisions can be made.
Lecture by prof. Georg Gottlob, University of Oxford at the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
Prof. Dr. Jens Lehmann, Lead Scientist for Conversational AI and Knowledge Graphs at Fraunhofer IAIS, presented an overview on current Conversational AI research.
This lecture discusses reasoning in Knowledge Graphs. Reasoning is essential to gain value from Knowledge Graphs by deriving insights and making available new implicit data from existing data. We will cover the theory and practice of reasoning in Knowledge Graphs, and provide a number of easily accessible examples based on Oxford’s Vadalog system.