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| ntology-driven approach for distributed information processing in supply chain environment |
| WU Jian1, NI Yi-hua2, LV Yan2 |
| 1.Department of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; 2.Department of Engineering, Zhejiang A&F University, Linan 311300, China |
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Abstract In order to solve the semantic heterogeneity problems about business event processing of manufacturing enterprises based on massive
perception data in supply chain environment, which made it hard for integrated and efficient application, an ontology-driven method for distributed information processing was proposed. Firstly, The perception-based supply chain event ontology was presented and built, which could express enterprise business process preferably, and the conversion from heterogeneous information sources to fact triples described by unified semantics was realized by ontology mapping; then according to the event ontology, the SWRL (Semantic Web Rule Language) based event processing rules were defined and built, which could realize the enterprise decision application. Next a strategy about rule splitting and fact distribution was presented, and a distributed processing framework based on rule matching was built by using MapReduce and Rete algorithms, which could handle big data efficiently. At last, taking the result accuracy and processing efficiency as key indexes, an example based on enterprise data was comparatively analyzed to show that this method is viable.
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Published: 01 November 2014
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供应链中本体驱动的分布式信息处理
针对供应链环境下制造企业基于海量感知数据的业务处理存在语义异构,同时难以进行集成和高效应用的难题,提出一种本体驱动的分布式信息处理方法.构建基于海量感知数据的供应链事件本体,完善定义和表达企业业务处理粒度,通过本体映射实现异构信息源到统一描述事实组的转换.定义并构建基于事件本体的语义规则语言（SWRL）处理规则,实现企业决策应用.提出一种规则分解和事实分发策略,采用基于MapReduce和Rete算法相结合的分布式处理架构,实现大规模数据的高效处理.通过企业实例对比分析,结果表明,以推理结果准确性和处理效率为指标,验证了该方法的可行性.
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