【摘要】 目前各省市各部门分别拥有各自专用的专家信息系统,分别管理所在地区和所属领域的专家信息,其形式各异且专家信息分布异构.针对实际应用中共享专家信息困难,基于关键字查询信息效率不高等问题,提出基于语义的专家信息系统解决方案.采用5W1H分析法归纳领域本体中概念和关系,建立基于5W1H的专家本体概念模型并生成专家领域本体,实现了专家语义信息统一建模.构建系统的四层体系结构,研究语义推理规则的定义方法,设计了基于语义的规则推理算法和基于SPAR-QL的语义信息查询算法,实现了系统基于语义的信息查询和推理等功能.实验表明,基于语义的专家信息查询在查全率、查准率优于基于关键字的查询.更多还原

【Abstract】 Currently,different provinces and distinct departments have their own different expert information systems with distributed and heterogeneous expert information,so expert information sharing is difficult and expert information retrieval based on keywords is inefficient in the practical applications.According to the above issues,this paper presents the implementation schema for the semantic-based expert information system.The concepts and relations in the expert domain are summarized by the 5W1H analysis method,and conceptual model of expert ontology based on 5W1H is created to model expert information based on semantic.Four-layered system structure for the system is built,and semantic reasoning rules are also defined.The algorithm of semantic rule reasoning and algorithm of semantic information retrieval by SPARQL are designed,to realize the function of reasoning and information retrieval based on semantic.The experimental results show that the expert information retrieval based on semantic has got improvement on information retrieval recall.更多还原