A reference ontology for biomedical informatics: the foundational model of anatomy
Journal of Biomedical Informatics - Special issue: Unified medical language system
Ontology ranking based on the analysis of concept structures
Proceedings of the 3rd international conference on Knowledge capture
Text Mining for Biology And Biomedicine
Text Mining for Biology And Biomedicine
Knowledge-based gene symbol disambiguation
Proceedings of the 2nd international workshop on Data and text mining in bioinformatics
Modelling ontology evaluation and validation
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Alignment of biomedical ontologies using life science literature
KDLL'06 Proceedings of the 2006 international conference on Knowledge Discovery in Life Science Literature
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Ontology consolidation in bioinformatics
APCCM '10 Proceedings of the Seventh Asia-Pacific Conference on Conceptual Modelling - Volume 110
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Text mining for biomedicine requires a significant amount of domain knowledge. Much of this information is contained in biomedical ontologies. Developers of text mining applications often look for appropriate ontologies that can be integrated into their systems, rather than develop new ontologies from scratch. However, there is often a lack of documentation of the qualities of the ontologies. A number of methodologies for evaluating ontologies have been developed, but it is difficult for users by using these methods to select an ontology. In this paper, we propose a framework for selecting the most appropriate ontology for a particular text mining application. The framework comprises three components, each of which considers different aspects of requirements of text mining applications on ontologies. We also present an experiment based on the framework choosing an ontology for a gene normalization system.