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作 者:赵慧含 刘鹏[2,3] Zhao Huihan;Liu Peng(School of Information&Control Engineering,China University of Mining&Technology,Xuzhou Jiangsu 221116,China;Internet of Things Perception Mine Research Centre,China University of Mining&Technology,Xuzhou Jiangsu 221008,China;National&Local Joint Engineering Laboratory of Internet Application Technology on Mine,Xuzhou Jiangsu 221008,China)
机构地区:[1]中国矿业大学信息与控制工程学院,江苏徐州221116 [2]中国矿业大学物联网(感知矿山)研究中心,江苏徐州221008 [3]矿山互联网应用技术国家地方联合工程实验室,江苏徐州221008
出 处:《计算机应用研究》2018年第4期1076-1079,1095,共5页Application Research of Computers
基 金:国家重点研发计划资助项目(2017YFC0804401;2017YFC0804409)
摘 要:随着语义网的快速发展,语义数据也高速增长,传统单机推理系统无法满足推理需求,而已有的并行推理算法在推理完备性和稳定性上存在明显不足。为此提出的基于Spark的并行推理算法(PROS)从以下三点进行了优化:通过分析OWL Horst规则依赖关系,结合数据的分类结果将规则分为四类;四类规则分别设计了区域最优的规则执行顺序,进一步提高了并行推理的执行效率;将same As规则考虑到迭代中,显著提高了算法的推理能力。实验结果表明,相比已有并行推理算法,PROS并行推理算法在保证推理完备性和稳定性上表现更加出色,推理效率亦有小幅提高;同时PROS相比单机推理算法大大缩短了推理时间,处理大规模数据展现出了优良的并行扩展性。With the rapid development of semantic Web,the amount of semantic data increases rapidly,which results in poor efficiency of single-node reasoning systems.On the other side,although efficient in reasoning time,the existing parallel reasoning algorithms generally show unsatisfactory reasoning integrity and stability.This paper proposed an improved parallel reasoning schema,named as PROS,which included three major optimizations as follows.Firstly,by analyzing the mutual dependencies,it divided the OWL Horst rules into four classes.Secondly,it designed locally optimal strategies for the four classes of rules,which furtherly improved the reasoning efficiency.Thirdly,it took the sameAs rules into iteration so as to boost reasoning ability of PROS.The experimental results indicate that the proposed PROS outperforms in reasoning integrity and stability compared to existing parallel reasoning algorithms.Meanwhile the PROS greatly reduces the reasoning time compared to single-node implementation and shows good expansibility.
关 键 词:语义推理 网络本体语言 OWL Horst规则 并行化 SPARK
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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