Abstract
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.
Original language | English |
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Journal | CEUR Workshop Proceedings |
Volume | 2003 |
State | Published - 2017 |
Event | 12th International Workshop on Neural-Symbolic Learning and Reasoning, NeSy 2017 - London, United Kingdom Duration: Jul 17 2017 → Jul 18 2017 |
ASJC Scopus Subject Areas
- General Computer Science
Keywords
- Neural networks
- Conceptual apporaches
- Input-output behavior
- New applications
- Proof of concept
- Semantic Web Technology
- Structured data
- Trained neural networks
- Semantic Web
Disciplines
- Computer Sciences