BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection
The biomedical sciences is one of the few domains where ontologies are widely being developed to facilitate information retrieval and knowledge sharing, but there still remains the problem that applications using different ontologies cannot share knowledge without explicit references between overlap...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | English |
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2013
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| Online Access: | https://hdl.handle.net/10356/105389 http://hdl.handle.net/10220/17512 |
| _version_ | 1826115937344946176 |
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| author | Chua, Watson Wei Khong Kim, Jung-jae |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Chua, Watson Wei Khong Kim, Jung-jae |
| author_sort | Chua, Watson Wei Khong |
| collection | NTU |
| description | The biomedical sciences is one of the few domains where ontologies are widely being developed to facilitate information retrieval and knowledge sharing, but there still remains the problem that applications using different ontologies cannot share knowledge without explicit references between overlapping concepts. Ontology alignment is the task of identifying such equivalence relations between concepts across ontologies. Its application to the biomedical domain should address two open issues: (1) determining the equivalence of concept-pairs which have overlapping terms in their names, and (2) the high run-time required to align large ontologies which are typical in the biomedical domain. To address them, we present a novel approach, named the Biomedical Ontologies Alignment Technique (BOAT), which is state-of-the-art in terms of F-measure, precision and speed. A key feature of BOAT is that it considers the informativeness of each component word in the concept labels, which has significant impact on biomedical ontologies, resulting in a 12.2% increase in F-measure. Another important feature of BOAT is that it selects for comparison only concept pairs that show high likelihoods of equivalence, based on the similarity of their annotations. BOAT’s F-measure of 0.88 for the alignment of the mouse and human anatomy ontologies is on par with that of another state-of-the-art matcher, AgreementMaker, while taking a shorter time. |
| first_indexed | 2024-10-01T04:03:16Z |
| format | Journal Article |
| id | ntu-10356/105389 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:03:16Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1053892020-05-28T07:17:20Z BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection Chua, Watson Wei Khong Kim, Jung-jae School of Computer Engineering DRNTU::Engineering::Computer science and engineering The biomedical sciences is one of the few domains where ontologies are widely being developed to facilitate information retrieval and knowledge sharing, but there still remains the problem that applications using different ontologies cannot share knowledge without explicit references between overlapping concepts. Ontology alignment is the task of identifying such equivalence relations between concepts across ontologies. Its application to the biomedical domain should address two open issues: (1) determining the equivalence of concept-pairs which have overlapping terms in their names, and (2) the high run-time required to align large ontologies which are typical in the biomedical domain. To address them, we present a novel approach, named the Biomedical Ontologies Alignment Technique (BOAT), which is state-of-the-art in terms of F-measure, precision and speed. A key feature of BOAT is that it considers the informativeness of each component word in the concept labels, which has significant impact on biomedical ontologies, resulting in a 12.2% increase in F-measure. Another important feature of BOAT is that it selects for comparison only concept pairs that show high likelihoods of equivalence, based on the similarity of their annotations. BOAT’s F-measure of 0.88 for the alignment of the mouse and human anatomy ontologies is on par with that of another state-of-the-art matcher, AgreementMaker, while taking a shorter time. 2013-11-08T07:13:05Z 2019-12-06T21:50:28Z 2013-11-08T07:13:05Z 2019-12-06T21:50:28Z 2011 2011 Journal Article Chua, W. W. K., & Kim, J.-j. (2012). BOAT: Automatic alignment of biomedical ontologies using term informativeness and candidate selection. Journal of Biomedical Informatics, 45(2), 337-349. https://hdl.handle.net/10356/105389 http://hdl.handle.net/10220/17512 10.1016/j.jbi.2011.11.010 en Journal of biomedical informatics |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Chua, Watson Wei Khong Kim, Jung-jae BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection |
| title | BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection |
| title_full | BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection |
| title_fullStr | BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection |
| title_full_unstemmed | BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection |
| title_short | BOAT : automatic alignment of biomedical ontologies using term informativeness and candidate selection |
| title_sort | boat automatic alignment of biomedical ontologies using term informativeness and candidate selection |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/105389 http://hdl.handle.net/10220/17512 |
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