The Accuracy of Neural Networks in Eliminating Data Duplication Problem During Data Integration Process

摘要

Data integration is an important subject in database research and has now become a necessity to many organizations. There are a number of important issues related to data integration, such as the difference in platforms in which data resources are integrated, the difference in database schema structures, and data cleaning, among others. One of these interesting issues is the data duplication problem. Data duplication problems have resulted in a significant amount of lost revenue in terms of disgruntled customers, incomplete sales orders, and other dilemmas. A proposed solution to data duplication problems is the use of neural networks. In this paper, a neural network is trained to identify duplicate records in a given data source.