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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ki-Heon Kim Jae-Dong Yang Jae-Hun Choi Kyung-Ah Yang Young-Guk Ha |
| Copyright Year | 2007 |
| Abstract | In this paper, we propose a semantic inheritance/inverse-inheritance mechanism for systematic bio-ontology construction. This mechanism allows domain experts to easily manage sophisticated bio-ontologies in which biological knowledge is encoded; it automatically captures semantics inferred from the ontology structure being constructed or already constructed. Based on the captured semantics it suggests appropriate recommendation to the experts. While inheritance enables them to consistently determine the semantics of relationships between ontology concepts (or classes), inverse-inheritance allows them to incrementally refine the semantics by exploiting a huge amount of relationships between the instances of the concepts. To demonstrate the feasibility of the mechanism, we also implement an OWL(Web Ontology Language)-based graphical bio-ontology management system. In the system, the mechanism is seamlessly applied to the ontology by well defined graphic notations based on OWL. OWL is adopted to fully express the subtle semantics inherently buried in the bio-ontology. |
| Starting Page | 398 |
| Ending Page | 401 |
| File Size | 567035 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424407873 |
| ISSN | 1557170X |
| DOI | 10.1109/IEMBS.2007.4352308 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-22 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ontologies OWL Systematics Unified modeling language Biological information theory Knowledge management Graphics Databases Biological system modeling Biological processes |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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