Measuring semantic similarity between biomedical concepts within multiple ontologies
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
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We describe a term relation frequency (TRF) method for finding comprehensive documents in a rapidly growing academic discipline. The method enables us to organize knowledge into a single document based on terminology. The method is based on the classification of documents into comprehensive, central, peripheral, and independent classes according to the commonality and exclusiveness of terminology. Being able to find the documents quickly is helpful for our understanding of the discipline. Multiple-meaning technical terms such as "coordination" play a key role in rapidly growing academic disciplines such as coordination science. Visual representation of the multiple-meaning terms helps us to identify quickly and easily how the terms are used. With TRF and visualization methods, we can identify documents that explain a technical term comprehensively. We can also identify a change in the subject of a discipline according to when the comprehensive documents are written. We show that the observed change matches our understanding of the topic of the field "coordination science." The methods discussed here are promising to help us quickly understand and advance research in rapidly growing academic disciplines such as coordination science.