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Evaluating large-scale biomedical ontology matching over parallel platforms


Amin, MB and Khan, WA and Hussain, S and Bui, D-M and Banos, O and Kang, BH and Lee, S, Evaluating large-scale biomedical ontology matching over parallel platforms, IETE Technical Review, 33, (4) pp. 415-427. ISSN 0256-4602 (2016) [Refereed Article]

Copyright Statement

2016 IETE

DOI: doi:10.1080/02564602.2015.1117399


Biomedical systems have been using ontology matching as a primary technique for heterogeneity resolution. However, the natural intricacy and vastness of biomedical data have compelled biomedical ontologies to become large-scale and complex; consequently, biomedical ontology matching has become a computationally intensive task. Our parallel heterogeneity resolution system, i.e., SPHeRe, is built to cater the performance needs of ontology matching by exploiting the parallelism-enabled multicore nature of today's desktop PC and cloud infrastructure. In this paper, we present the execution and evaluation results of SPHeRe over large-scale biomedical ontologies. We evaluate our system by integrating it with the interoperability engine of a clinical decision support system (CDSS), which generates matching requests for large-scale NCI, FMA, and SNOMED-CT biomedical ontologies. Results demonstrate that our methodology provides an impressive performance speedup of 4.8 and 9.5 times over a quad-core desktop PC and a four virtual machine (VM) cloud platform, respectively.

Item Details

Item Type:Refereed Article
Keywords:biomedical informatics, multithreading, biomedical ontologies, ontology matching, parallel processing, parallel programming, semantic web
Research Division:Information and Computing Sciences
Research Group:Software engineering
Research Field:Software architecture
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Amin, MB (Dr Muhammad Bilal Amin)
UTAS Author:Kang, BH (Professor Byeong Kang)
ID Code:106687
Year Published:2016 (online first 2015)
Web of Science® Times Cited:7
Deposited By:Information and Communication Technology
Deposited On:2016-02-17
Last Modified:2022-08-18

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