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基于模糊聚类的属性匹配算法 被引量：12

An Attribute Matching Algorithm Based on Fuzzy Clustering
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摘要 提出了一种基于模糊聚类的属性匹配算法。该算法采用能综合反映属性名称相似性和语义相似性的模糊相似关系,提高了属性匹配的准确率;以等价闭包法对相似属性进行模糊聚类,得到多层次属性分类结果,更客观真实地反映了属性匹配的模糊性;同时,属性匹配过程中不需要设置匹配参数,避免了人为造成的误差。 By means of the fuzzy similarity of attribute, the attribute matching algorithm based on fuzzy clustering improves the veracity of attribute matching. It uses the equivalent closure to cluster the attributes fuzzily, and gets the multilevel attributes classified results. During the matching of the similar attributes with the fuzzy clustering, it doesn＇t need to set the parameter of clustering, and avoids the manual errors.
作者 刘青宝 金燕 邓苏 张维明
机构地区 国防科学技术大学信息系统与管理学院
出处 《模糊系统与数学》 CSCD 北大核心 2006年第6期96-102,共7页 Fuzzy Systems and Mathematics
基金 国家自然科学基金资助项目(60172012)
关键词 模糊聚类 属性匹配 数据集成 Fuzzy Clustering Attribute Matching Data Integration
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献14

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共引文献7

同被引文献95

引证文献12

二级引证文献95

模糊系统与数学
2006年 第6期

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