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数据集成中不一致性数据相似性比较的加权算法 被引量:1

A Weight Algorithm for Similarity Comparison of Inconsistency Data in Integrating Data
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摘要 Reducing inconsistency is the key problem to improve data quality during data integration. In this paper,we first present a weighted algorithm of similarity coefficient which is superior to traditional algorithms if the sourcedata have multiple characteristic items ,all of which have to be taken into account ,especially during the complex infor-mation integration. Secondly,we apply it to the experiment of telecommunication customers integrating ,the results ofdata clustering show it has high feasibility and precision performance. Reducing inconsistency is the key problem to improve data quality during data integration. In this paper, we first present a weighted algorithm of similarity coefficient which is superior to traditional algorithms if the source data have multiple characteristic items, all of which have to be taken into account .especially during the complex information integration. Secondly,we apply it to the experiment of telecommunication customers integrating,the results of data clustering show it has high feasibility and precision performance.
出处 《计算机科学》 CSCD 北大核心 2003年第8期92-92,F004,共2页 Computer Science
关键词 数据集成 数据源 数据挖掘 数据存储 不一致性 数据相似性 加权算法 Data integration,Similarity coefficient,Weight integration, Cluster
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