Abstract
This paper introduces StreamJess, a Stream Reasoning system that layers on top of a state of the art query processing system such as C-SPARQL to enable closed-world, non-monotonic and time-aware reasoning with Jess rules. The system is validated in the water quality monitoring domain by demonstrating water bodies’ classification and pollution sources investigation.
Author supplied keywords
Cite
CITATION STYLE
Jajaga, E., Ahmedi, L., & Ahmedi, F. (2017). StreamJess: Enabling jess for stream data reasoning and the water domain case. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10180 LNAI, pp. 127–130). Springer Verlag. https://doi.org/10.1007/978-3-319-58694-6_15
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
