semantics, unique challenges arise when we handle the fuzzy information. We identify these key chal- lenges, and propose a solution for tackling each of ...
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 ...
Large scale fuzzy pD∗ reasoning using mapreduce. In Proc. of ISWC'. 11, 405–420. Tappolet, J., and Bernstein, A. 2009. Applied temporal rdf: Efficient ...
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* ...
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* ...
Large Scale Fuzzy pD * Reasoning Using MapReduce | Request PDF
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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 ...
This is the first work to investigate how MapReduce can be applied to solve the scalability issue of fuzzy reasoning in OWL, and the running time of the ...
Apr 16, 2012 · The MapReduce framework has proved to be very efficient for data-intensive tasks. Earlier work has successfully applied MapReduce for large ...
Nov 25, 2011 · Earlier work has tried to use MapReduce for large scale reasoning for pD∗ semantics and has shown promising results. In this paper, we move ...
Apr 13, 2012 · MapReduce framework to tackle large scale reasoning in fuzzy. OWL. The only work that tried to deal with large scale fuzzy ontologies was ...