摘要
为解决传统推理引擎在进行大规模OWL本体数据的SWRL规则推理时存在的计算性能和可扩展性不足等问题,提出了云计算环境下的SWRL规则分布式推理框架CloudSWRL。根据SWRL规则语义,并以Hadoop开源云计算框架为基础,设计了OWL本体在HBase分布式数据库中的存储策略,定义了SWRL规则解析模型和相关推理中间数据模型,提出了在DL-safe限制下基于MapReduce的SWRL规则分布式推理算法。实验结果表明,在对大规模OWL本体进行SWRL规则推理时,CloudSWRL框架在计算性能和可扩展性方面均优于传统推理引擎。
With the explosion of semantic web technologies, large amounts of OWl. ontologies are common place. Conventional rule engines inevitably meet the bottleneck of computing performance and sealability. A cloud computing based SWRL distributed reasoning framework named CloudSWRL is proposed. Based on the Hadoop open-source framework and SWRL semantics, the storage schema for OWL ontologies is designed to implement efficient data retrieving from HBase. Some novel data models for SWRL rules and intermediate data are defined. At last, a MapReduce paradigm based distributed SWRL reasoning algorithm is proposed under DL-safe restriction. An experiment on a simulation environment shows our framework is more efficient and sealable than conventional rule engines when reasoning over large-scale of OWL data.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第2期56-62,84,共8页
Journal of Chongqing University
基金
国家自然科学基金重点资助项目(91118005)
国家自然科学基金青年科学基金资助项目(51005260)
重庆市自然科学基金重点项目(CSTC-2011BA2022)
