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基于启发式规则的SPARQL本体查询
引用本文:谭立威,邵志清,张欢欢,蒋宇一,胡芳槐.基于启发式规则的SPARQL本体查询[J].医学教育探索,2016(6):851-857.
作者姓名:谭立威  邵志清  张欢欢  蒋宇一  胡芳槐
作者单位:华东理工大学信息科学与工程学院, 上海 200237,华东理工大学信息科学与工程学院, 上海 200237,华东理工大学信息科学与工程学院, 上海 200237,华东理工大学信息科学与工程学院, 上海 200237,华东理工大学信息科学与工程学院, 上海 200237
基金项目:国家高技术研究发展“863”计划(2015AA020107)
摘    要:提出了基于启发式规则的SPARQL查询。用语言技术平台(LTP)解析出问句的依存分析树(DPT),然后对问句集的依存分析树进行统计和分析,总结出用于查询三元组抽取的启发式规则,利用这些规则去掉无意义的查询三元组,合并和重组意义不完整的查询三元组。查询三元组经过类映射、实例映射和属性映射得到本体三元组,形成SPARQL查询。用户在B/S结构的查询界面中提交中文自然语言问句,得到中间结果和问句结果。实验结果表明了该方法的有效性。

关 键 词:自然语言问句  依存分析树  三元组映射  SPARQL查询
收稿时间:2016/1/13 0:00:00

SPARQL Ontology Query Based on Heuristic Rules
TAN Li-wei,SHAO Zhi-qing,ZHANG Huan-huan,JIANG Yu-yi and HU Fang-huai.SPARQL Ontology Query Based on Heuristic Rules[J].Researches in Medical Education,2016(6):851-857.
Authors:TAN Li-wei  SHAO Zhi-qing  ZHANG Huan-huan  JIANG Yu-yi and HU Fang-huai
Institution:School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China,School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China,School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China,School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China and School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
Abstract:This paper proposes an SPARQL ontology query based on heuristic rules.In the proposed method,LTP (Language Technology Platform) is utilized to parse a question to dependency parsing tree (DPT).Heuristic query triple extraction rules are formed according to the statistic and analysis of DPTs of question set.Query triple(s) are extracted accurately by deleting meaningless query triple(s) and recombining incomplete query triple(s) based on these rules.Query triple(s) are mapped to ontology triple(s) by means of three kinds of mapping:class mapping,instance mapping and property mapping.And then,SPARQL query is obtained.Intermediate results and answer will be presented to users when they submit a Chinese natural language question in the query interface.The experiment shows that the presented method is effective.
Keywords:natural language question  dependency parsing tree  triple mapping  SPARQL query
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