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基于近似匹配模型的XML元数据检索
引用本文:欧阳柳波,李学勇,杨贯中,李国徽. 基于近似匹配模型的XML元数据检索[J]. 计算机应用, 2005, 25(4): 820-823. DOI: 10.3724/SP.J.1087.2005.0820
作者姓名:欧阳柳波  李学勇  杨贯中  李国徽
作者单位:湖南大学,软件学院,湖南,长沙,410082;长沙大学,数学与信息科学系,湖南,长沙,410003;华中科技大学,计算机科学与技术学院,湖北,武汉,430074
基金项目:国家自然科学基金资助项目(60203017),国家科技基础性研究专项资金资助项目(2001DEA20016-02-04)
摘    要:将无序标签树匹配分解为树结构匹配和标签语义匹配,采用树结构匹配和语义匹配相结 合的方法,对传统树匹配算法进行了改进,提出了近似匹配概念,并针对元数据XML描述的结构化特 征,设计了一种基于三层近似匹配模型的元数据检索方法。这种检索方法可根据用户的不同需求有 效地调节元数据的查准率和查全率。最后构造了基于近似匹配模型的元数据查询系统原型,实验证 明近似匹配模型在元数据检索应用中具有可行性和高效性。

关 键 词:可扩展标记语言  元数据检索  近似匹配  查全率  查准率
文章编号:1001-9081(2005)04-0820-04

XML metadata retrieval based an approximately matching model
OUYANG Liu-Bo,LI Xue-Yong,YANG Guang-zhong,LI Guo-hui. XML metadata retrieval based an approximately matching model[J]. Journal of Computer Applications, 2005, 25(4): 820-823. DOI: 10.3724/SP.J.1087.2005.0820
Authors:OUYANG Liu-Bo  LI Xue-Yong  YANG Guang-zhong  LI Guo-hui
Affiliation:1.Software College,Hunan University,Changsha Hunan 410082,China; 2.Department of Mathmatics and Information Science,Changsha University,Changsha Hunan 410003,China; 3.College of Computer Science and Technology,Huazhong University of Science and Technology,Wuhan Hubei 430074,China
Abstract:This thesis took apart the unordered label tree matching into tree structure matching and tree label semantic matching. By combined with the tree structure matching and semantic matching, the thesis changed the traditional tree matching algorithms into approximately matching, and a metadata retrieval method based on three-level tree approximately matching model was put forward. According to this new retrieval method, the accuracy and recall rates would be adjusted by different requirement of users. In the end, this thesis brought forward the retrieval process of XML-oriented metadata, and gave out the applied design of metadata approximately match. The results of experiments prove that the approximately matching model is feasible and efficient in the application of retrieval XML metadata.
Keywords:XML  metadata retrieval  approximately matching  retrieval recall rate  retrieval accuracy rate
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