Explaining Trained Neural Networks with Semantic Web Technologies: First Steps
Md Kamruzzaman Sarker, Ning Xie, Derek Doran, Michael L. Raymer, Pascal Hitzler · arXiv (Cornell University) · 2017
The ever increasing prevalence of publicly available structured data on the World Wide Web enables new applications in a variety of domains. In this paper, we provide a conceptual approach that leverages such data in order to explain the input-output behavior of trained artificial neural networks. We apply existing Semantic Web technologies in order to provide an experimental proof of concept.