Large Scale Fuzzy pD * Reasoning Using MapReduce [chapter]

Chang Liu, Guilin Qi, Haofen Wang, Yong Yu
2011 Lecture Notes in Computer Science  
The MapReduce framework has proved to be very efficient for data-intensive tasks. Earlier work has tried to use MapReduce for large scale reasoning for pD * semantics and has shown promising results. In this paper, we move a step forward to consider scalable reasoning on top of semantic data under fuzzy pD * semantics (i.e., an extension of OWL pD * semantics with fuzzy vagueness). To the best of our knowledge, this is the first work to investigate how MapReduce can help to solve the
more » ... issue of fuzzy OWL reasoning. While most of the optimizations used by the existing MapReduce framework for pD * semantics are also applicable for fuzzy pD * semantics, unique challenges arise when we handle the fuzzy information. We identify these key challenges, and propose a solution for tackling each of them. Furthermore, we implement a prototype system for the evaluation purpose. The experimental results show that the running time of our system is comparable with that of WebPIE, the state-of-the-art inference engine for scalable reasoning in pD * semantics.
doi:10.1007/978-3-642-25073-6_26 fatcat:f5zqayakbrgmtmrbbvixssb3se