The Center for Education and Research in Information Assurance and Security (CERIAS)

The Center for Education and Research in
Information Assurance and Security (CERIAS)
Center for Education and Research in Information Assurance and Security

SEMINT: A tool for identifying attribute correspondences in heterogeneous databases using neural networks

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Author

Christopher Clifton

Tech report number

CERIAS TR 2001-78

Entry type

article

Abstract

One step in interoperating among heterogeneous databases is semantic integration: Identifying relationships between attributes or classes in different database schemas. SEMantic INTegrator (SEMINT) is a tool based on neural networks to assist in identifying attribute correspondences in heterogeneous databases. SEMINT supports access to a variety of database systems and utilizes both schema information and data contents to produce rules for matching corresponding attributes automatically. This paper provides theoretical background and implementation details of SEMINT. Experimental results from large and complex real databases are presented. We discuss the effectiveness of SEMINT and our experiences with attribute correspondence identification in various environments.

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Date

2000 – 04

URL

http://www.sciencedirect.com/s ... cc8402c910192c5e71d78864f

Address

Amsterdam

Journal

Data and Knowlege Engineering

Key alpha

Clifton

Number

1

Pages

49-84

Publisher

Elsevier Science

Volume

33

Publication Date

2001-04-01

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