University of Hradec Kralove
Data originating from the Web, sensor readings and social media result in increasingly huge datasets. The so called Big Data comes with new scientific and technological challenges while creating new opportunities, hence the increasing interest in academia and industry. Traditionally, logic programming has focused on complex knowledge structures/programs, so the question arises whether and how it can work in the face of Big Data. In this paper, the authors examine how the well-founded semantics can process huge amounts of data through mass parallelization. More specifically, they propose and evaluate a parallel approach using the MapReduce framework.