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

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 per...

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Main Authors: Mehdi, Osama A., Ibrahim, Hamidah, Affendey, Lilly Suriani, Pardede, Eric, Cao, Jinli
Format: Article
Language:English
Published: ComSIS Consortium 2018
Online Access:http://psasir.upm.edu.my/id/eprint/72675/1/Exploring%20instances%20for%20matching%20heterogeneous%20database%20schemas%20utilizing%20Google%20similarity%20and%20regular%20expression.pdf
http://psasir.upm.edu.my/id/eprint/72675/
http://www.comsis.org/archive.php?show=ppr633-1705
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Institution: Universiti Putra Malaysia
Language: English
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spelling my.upm.eprints.726752020-11-30T06:43:40Z http://psasir.upm.edu.my/id/eprint/72675/ Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression Mehdi, Osama A. Ibrahim, Hamidah Affendey, Lilly Suriani Pardede, Eric Cao, Jinli 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. ComSIS Consortium 2018-06 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/72675/1/Exploring%20instances%20for%20matching%20heterogeneous%20database%20schemas%20utilizing%20Google%20similarity%20and%20regular%20expression.pdf 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 http://www.comsis.org/archive.php?show=ppr633-1705 10.2298/CSIS170525002M
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description 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.
format Article
author Mehdi, Osama A.
Ibrahim, Hamidah
Affendey, Lilly Suriani
Pardede, Eric
Cao, Jinli
spellingShingle Mehdi, Osama A.
Ibrahim, Hamidah
Affendey, Lilly Suriani
Pardede, Eric
Cao, Jinli
Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression
author_facet Mehdi, Osama A.
Ibrahim, Hamidah
Affendey, Lilly Suriani
Pardede, Eric
Cao, Jinli
author_sort Mehdi, Osama A.
title Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression
title_short Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression
title_full Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression
title_fullStr Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression
title_full_unstemmed Exploring instances for matching heterogeneous database schemas utilizing Google similarity and regular expression
title_sort exploring instances for matching heterogeneous database schemas utilizing google similarity and regular expression
publisher ComSIS Consortium
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/72675/1/Exploring%20instances%20for%20matching%20heterogeneous%20database%20schemas%20utilizing%20Google%20similarity%20and%20regular%20expression.pdf
http://psasir.upm.edu.my/id/eprint/72675/
http://www.comsis.org/archive.php?show=ppr633-1705
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