Duplicate Data Detection Using GNN

被引：0

作者：

Lu, Hanrong ^{[1
]}

Chen, Xin ^{[1
]}

Lan, Xuhui ^{[1
]}

Zheng, Feng ^{[1
]}

机构：

[1] Air Force Early Warning Acad, Dept Early Warning Intelligence, Wuhan, Peoples R China

来源：

PROCEEDINGS OF 2016 IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA 2016) | 2016年

关键词：

record detection; data cleaning; neural network; genetic algorithm; GNN; NETWORK; PERFORMANCE;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In some applications like data warehousing, data mining or information integration data must be cleaned as a preprocessing step to ensure the quality of data and the performance of applications. An essential work in data cleaning is duplicate record detection. Existing detection methods apply to different data models and record types. Certain difficulties with those studies are still to be overcome. This paper proposes a genetic neural network based approach to duplicate record detection. The topology and weight vector of a neural network are firstly optimized by a genetic algorithm for the given data set before it is used to perform the detection. The method can enhance the detection accuracy and alleviate the many problems with previous works.

引用

页码：167 / 170

页数：4

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