The Quest for Parallel Reasoning on the Semantic Web [chapter]

Peiqiang Li, Yi Zeng, Spyros Kotoulas, Jacopo Urbani, Ning Zhong
2009 Lecture Notes in Computer Science  
Traditional reasoning tools for the Semantic Web cannot cope with Web scale data. One major direction to improve performance is parallelization. This article surveys existing studies, basic ideas and mechanisms for parallel reasoning, and introduces three major parallel applications on the Semantic Web: LarKC, MaRVIN, and Reasoning-Hadoop. Furthermore, this paper lays the ground for parallelizing unified search and reasoning at Web scale.
doi:10.1007/978-3-642-04875-3_45 fatcat:t2m72we4yncvhdvplyf52er54q