What is it about?
In this work, we present yet another incremental solution that is able to outperform existing approaches by using a sophisticated aggregation method based on fuzzy logic.
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Why is it important?
Results show us that our strategy is able to consistently beat existing approaches when solving well-known biomedical benchmark data sets.
Perspectives
Semantic similarity measurement of biomedical nomenclature aims to determine the likeness between two biomedical expressions that use different lexicographies for representing the same real biomedical concept. There are many semantic similarity measures for trying to address this issue, many of them have represented an incremental improvement over the previous ones.
Dr Jorge Martinez-Gil
Software Competence Center Hagenberg GmbH
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This page is a summary of: Accurate Semantic Similarity Measurement of Biomedical Nomenclature by Means of Fuzzy Logic, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, April 2016, World Scientific Pub Co Pte Lt,
DOI: 10.1142/s0218488516500148.
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