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一个基于粗糙集的XML函数依赖发现算法

Rough Set Based Algorithm of Discovering Functional Dependency for XML
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摘要 数据依赖是数据库的一个重要概念。函数依赖是一种常见的数据依赖关系,是数据语义的重要组成部分。随着XML文档的大量出现,这一概念被引入到XML的领域中。本文在约束限制范围的基础上,给出了XML函数依赖的定义。引入粗糙集解决XML数据不完整的特点,给出XML函数依赖的判定定理。并且提出了一个发现XML文档中最小非平凡函数依赖的算法。该算法基于一致集的概念,通过不可分辨关系划分元组集减少求一致集的运算次数,使用逐层求精的算法来计算最小非平凡XML函数依赖集的左部。通过该算法得到的XML函数依赖的语义信息对数据存储模式设计、查询优化和更新异常检查来说是十分重要的。 Data dependency is an important concept in database research. Functional Dependency plays a fundamental role in data dependency where it provides semantics for the data. Since XML recently appear largely, XFD is introduced into XML research. On the basis of the range of constraints, XFD is redefined in XML. And we propose one algorithm that discovering minimal XFD, based on the rough set handling non-integrity data. It is based on the concept of agree sets, and the computation of agree sets can be decreased by using stripped partition tuples on indiscernibility relation. A levelwise algorithm is used for computing the left hand sides (1hs) of minimal non-trivial functional dependency. The semantics information is important to the design of XML schema, query optimization and check of update abnormity.
作者 孙伟 刘大昕
出处 《计算机科学》 CSCD 北大核心 2007年第3期92-94,共3页 Computer Science
关键词 可扩展标记语言 语义 数据依赖 XML函数依赖(XFD) 粗糙集 XML, Semantics, Data dependency, Functional dependency, Rough set
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参考文献12

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