Mathematical and Experimental Investigation of Ontological Similarity Measures and Their Use in Biomedical Domains

MATHEMATICAL AND EXPERIMENTAL INVESTIGATION OF ONTOLOGICAL SIMILARITY MEASURES AND THEIR USE IN BIOMEDICAL DOMAINS by Xinran Yu Similarity measurement is an important notion. In the context of ontologies, similarity measures are used to determine how similar one concept is to another. Because graph models have been used to represent ontologies, a variety of algorithms have been proposed for calculating the similarity between the graph nodes which represent ontological concepts. This thesis overviews existing ontological similarity measures and investigates mathematically and experimentally a wide range of these measures. The objective is not to assess performance to a gold-standard of similarity judgment but to develop a better understanding of the relationships among these measures through comparing their results when applied to the Gene Ontology. The experimental results show that some ontological similarity measures, especially information content-based measures, are highly correlated. The results of experiments comparing corpus-based to ontology-based information content measures for the Gene Ontology support previous experimental results using WordNet which demonstrated little difference between the two approaches. MATHEMATICAL AND EXPERIMENTAL INVESTIGATION OF ONTOLOGICAL SIMILARITY MEASURES AND THEIR USE IN BIOMEDICAL DOMAINS

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