Semantic classification of attributes for integrating heterogeneous relational databases with artificial neural networks

Author

Zárate, José Asunción Enríquez ; Cervantes, Jair ; Espinosa, Adrian Trueba ; Rosas, Rosa María Valdovinos ; Sanchez, Luis Márquez

Author_Institution

Univ. UAEM, Valle de Chalco, Mexico

fYear

2011

fDate

26-28 Oct. 2011

Firstpage

1

Lastpage

5

Abstract

One of the major problems in heterogeneous databases integration with different scheme and management system, is the data tautology, which involves an issue of semantics in the content mainly from the names and addresses at the time of normalizing the database, this problem is tackled in this article, by means of a neural network to classify the data. The results show that can be proper classification of up to 84% with these results may normalize the database and properly solve the problem generated by the database integration..

Keywords

neural nets; pattern classification; relational databases; artificial neural network; attribute semantic classification; data tautology; database integration; heterogeneous relational database; Accuracy; Biological neural networks; Databases; Encoding; Numerical models; Semantics; Training data; Heterogeneous database system; neural networks; semantic;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering Computing Science and Automatic Control (CCE), 2011 8th International Conference on

Conference_Location

Merida City

Print_ISBN

978-1-4577-1011-7

Type

conf

DOI

10.1109/ICEEE.2011.6106628

Filename

6106628