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Issue No. 06 - December (1994 vol. 9)
ISSN: 1541-1672
pp: 38-45
<p>Accuracy is critical when multiple databases are merged into a single system, because an error in a single record could lead to multiple mismatches. Address normalization is fairly common in database merging. We have developed a system to accurately and efficiently normalize mailing addresses. However, our system differs from other neural network architectures. Its key ingredients are an address dictionary and a scoring system. The scoring system is based on analog neural network systems, but the address dictionary follows a digital approach. The two key processes in our system are learning and address normalization. Learning is further split into dictionary creation updating and system parameters training.</p>

M. C. Chuah and W. S. Wong, "A Hybrid Approach to Address Normalization," in IEEE Intelligent Systems, vol. 9, no. , pp. 38-45, 1994.
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