Poster – Paper 523

An Adaptive Framework for RDF Stream Reasoning

Qiong Li, Xiaowang Zhang, Zhiyong Feng and Guohui Xiao


clock_event October 23, 2017, Poster and Demo Reception, 18:30-21:20
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In this paper, we propose an adaptive framework for RDF stream reasoning (PRSPR) in order to obtain more meaningful and valuable information, which is an extension of our previous work. Moreover, our work is a kind of plug-in framework which makes it more adaptive and flexible. Within this framework, not only can we apply all kinds of SPARQL query engines to process RDF streams, but also simultaneously support various inference engines for RDFS/OWL for stream reasoning. Finally, we experimentally evaluate the performance of PRSPR on YABench. The experiments show that PRSPR can still maintain the high performance with SPARQL query engines in RDF stream reasoning although there are some slight differences among them.

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