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浅层语义分析及SPARQL在问答系统中的应用 被引量:3

Application of shallow semantic analysis and SPARQL in question answering system
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摘要 为了解决受限域问答系统中答案抽取的问题,提出了一种基于浅层语义分析的问答系统模型。该模型以自然语言为接口,利用医院信息本体,采用浅层语义分析技术,由语义块定义规则和语义块判定规则,首先生成问句向量,然后利用SPARQL查询技术,在本体中进行查询,从而得到答案。实验表明该方法可行,对自动问答系统的设计具有借鉴意义和深入研究的价值。 To solve the problem of the answer extraction of restricted-domain question answering system,a question answering system model based on shallow semantic parsing is presented.A natural language interface is provided,the ontology of the hospital information is utilized and shallow semantic parsing technology is applied in the model.According to the rules of the definition and determination of semantic chunk,the question vector is firstly generated,then SPARQL query technology is utilized,the answer is obtained by querying in the ontology.The experiments proves that it is feasible to use the method to develop a question answering system,it is valuable for further study in more depth.
作者 张巍 陈俊杰
出处 《计算机工程与应用》 CSCD 北大核心 2011年第2期118-120,共3页 Computer Engineering and Applications
基金 国家自然科学基金(No.60970059) 山西省国际科技合作计划项目(No.2009081022)~~
关键词 问答系统 浅层语义分析 自然语言处理 question answering system shallow semantic analysis nature language processing
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  • 1邱树雄,李志蜀,王娣.语义网络及其Web信息检索机制研究[J].计算机工程,2004,30(23):118-120. 被引量:13
  • 2Tim Berners-Lee,James Hendler,Ora Lassila.The semantic web[EB/OL].http://www.sciam.com,2001.
  • 3Tim Finin,James Mayfield.Information retrieval and the semantic web[EB/OL].38th Hawaii International Conference on System Sciences,2005.
  • 4Yoo J M,Myaeng S H.Universal information retrieval system in semantic web environment[EB/OL].Proceeding of NLP-KE,2005.
  • 5Hp laboratory.An introduction to RDF and the Jena RDF API[EB/OL].http://jena.sourceforge.net/tutorial/RDF_API/index.html,2005.
  • 6Stanford medical informatics.protege3.2 beta[EB/OL].http://protege.stanford.edu,2006.
  • 7W3C.SPARQL query language for RDF[EB/OL].http://www.w3.org/TR/rdf-sparq1-query/,2006.
  • 8Brill E, et al. An analysis of the AskMSR question-answering system[ A]. Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing[ C]. USA: Association computational linguistics,2002.257- 264.
  • 9Dragomir R, et al. Mining the Web for answers to natural language questions[A] .Proceedings of International Conference on Information and Knowledge Management [C]. New York: Association for Computing Machinery,2001. 143 - 150.
  • 10Li X, Roth D. Learning question classifiers: The role of semantic information [ J ]. Natural Language Engineering, 2006,12(3):229-249.

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