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Neurosymbolic Artificial Intelligence (other common spellings: Neural-Symbolic, Neuro-Symbolic) concerns the combination of artificial neural networks (including deep learning) with symbolic methods, e.g. from logic based knowledge representation and reasoning in artificial intelligence. We list pointers to some of the work on this issue which the Data Semantics Lab is pursuing.
We contribute to fundations and applications of knowledge graphs. Touching their complete life cycle. This includes schema design (which is detailed on a seperate page), general principles and processes for graph design, deployment of large-scale graphs in application areas including the geo-sciences, digital humanities, and agricultural themes, as well as methods and applications for graph integration and schema alignment.
We conduct research concerning the theory and application of logic-based knowledge representation. This includes logic-based knowledge representation for knowledge graphs, ontologies, and more generally the semantic web. Below pointers on some of the main themes we are interested in.
