The majority of web assets cannot be understood by machines, because of the lack of available explicit and machine readable semantics. By enabling machines to understand the meaning of web media, fully automated discovery, processing, and linking become feasible. Semantic Web technologies offer the possibility to enhance web resources with explicit semantics via linking to ontologies encoded in RDF. We demand to make the content of every web asset explicit for machines with the least possible effort for any content provider. Web servers should deliver RDF descriptions for any web document on request. To achieve this, we propose a framework that enables web content providers to connect to content-wise descriptions of their web assets via simple HTTP content negotiation in connection with on-the-fly automated multimedia analysis services. We demonstrate the feasibility of our approach with a prototype implementation.
CITATION STYLE
Knuth, M., Waitelonis, J., & Sack, H. (2016). I am a machine, let me understand web media! In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9671, pp. 467–475). Springer Verlag. https://doi.org/10.1007/978-3-319-38791-8_33
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