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Exploiting BioPortal as Background Knowledge in Ontology Alignment.pdf (1.41 MB)
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Exploiting BioPortal as Background Knowledge in Ontology Alignment
Author Info
Chen, Xi
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=miami1407331095
Abstract Details
Year and Degree
2014, Master of Science, Miami University, Computer Science and Software Engineering.
Abstract
Ontology alignment (OA) is the process of taking as input two ontologies and producing mappings between the source concepts and the target concepts. Over the last few years, OA systems have made only minor improvements. To improve performance, some OA systems have included a semi-automatic matching approach which incorporates user interaction to assess low confidence mappings. This research investigates replacing the human expert with an automated expert or “oracle” that relies on specialized knowledge sources in the biomedical domain, BioPortal. BioPortal provides access to different resources including a wide variety of ontologies, classes within ontologies and mappings between the classes of different ontologies. A leading OA system LogMap has been used to evaluate the automated expert on the anatomy and Large Biomed Track of the Ontology Alignment Evaluation Initiative (OAEI). The experimental results are reported and show that the automated expert has a positive impact in the Large Biomed Track with four out of six of the track’s matching tasks having better OA standard performance measure for F-measure. In the Anatomy Track, using the automated expert improves the OA standard performance measure for precision. However, to the detriment of the recall measure, the result is a slight improvement in the F-measure.
Committee
Valerie Cross (Advisor)
Ernesto Jimenez-Ruiz (Committee Member)
Dhananjai Rao (Committee Member)
Pages
63 p.
Subject Headings
Computer Science
Keywords
ontology alignment, ontology matching, human expert, automated expert, semi-automatic matching, user interaction, knowledge source, biomedical, BioPortal, LogMap, background knowledge, perfect oracle, error rate
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Citations
Chen, X. (2014).
Exploiting BioPortal as Background Knowledge in Ontology Alignment
[Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1407331095
APA Style (7th edition)
Chen, Xi.
Exploiting BioPortal as Background Knowledge in Ontology Alignment.
2014. Miami University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=miami1407331095.
MLA Style (8th edition)
Chen, Xi. "Exploiting BioPortal as Background Knowledge in Ontology Alignment." Master's thesis, Miami University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=miami1407331095
Chicago Manual of Style (17th edition)
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Document number:
miami1407331095
Download Count:
375
Copyright Info
© 2014, all rights reserved.
This open access ETD is published by Miami University and OhioLINK.