UPM Institutional Repository

Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression


Citation

Mehdi, Osama A. and Ibrahim, Hamidah and Affendey, Lilly Suriani and Pardede, Eric and Cao, Jinli (2018) Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression. Computer Science and Information Systems, 15 (2). 295 - 320. ISSN 1820-0214; ESSN: 2406-1018

Abstract

Instance based schema matching aims to identify correspondences between different schema attributes. Several approaches have been proposed to discover these correspondences in which instances including those with numeric values are treated as strings. This prevents discovering common patterns or performing statistical computation between numeric instances. Consequently, this causes unidentified matches for numeric instances which further effect the results. In this paper, we propose an approach for addressing the problem of finding matches between schemas of semantically and syntactically related attributes. Since we only fully exploit the instances of the schemas, we rely on strategies that combine the strength of Google as a web semantic and regular expression as pattern recognition. To demonstrate the accuracy of our approach, we have conducted an experimental evaluation using real world datasets. The results show that our approach is able to find 1-1 matches with high accuracy in the range of 93% - 99%. Furthermore, our proposed approach outperformed the previous approaches using a sample of instances.


Download File

[img] Text
Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression.pdf

Download (48kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.2298/CSIS170525002M
Publisher: ComSIS Consortium
Keywords: Schema matching; Instance based schema matching; Google similarity; Regular expression
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 30 Nov 2020 06:43
Last Modified: 30 Nov 2020 06:43
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.2298/CSIS170525002M
URI: http://psasir.upm.edu.my/id/eprint/72675
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item