New approach to the re-identification problem using neural networks

被引：0

作者：

Nin, Jordi ^{[1
]}

Torra, Vicenc ^{[1
]}

机构：

[1] CSIC, IIIA, Bellaterra 08193, Catalonia, Spain

来源：

MODELING DECISIONS FOR ARTIFICIAL INTELLIGENCE | 2006年 / 3885卷

关键词：

database integration; record linkage; re-identification algorithms; neural networks; data mining; information fusion; information privacy;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Schema and record matching are tools to integrate files or databases. Record linkage is one of the tools used to link those records that while belonging to different files correspond to the same individual. Standard record linkage methods are applied when the records of both files are described using the same variables. One of the non-standard record linkage methods corresponds to the case when files are not described using the same variables. In this paper we study record linkage for non common variables. In particular, we use a supervised approach based on neural networks. We use a neural network to find the relationships between variables. Then, we use these relationships to translate the information in the domain of one file into the domain of the other file.

引用

页码：251 / 261

页数：11

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