Towards the development of a conceptual distance metric for the UMLS
Journal of Biomedical Informatics
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Measures of semantic similarity and relatedness in the biomedical domain
Journal of Biomedical Informatics
Measuring concept relatedness using language models
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Methodological Review: Empirical distributional semantics: Methods and biomedical applications
Journal of Biomedical Informatics
Computing Knowledge-Based Semantic Similarity from the Web: An Application to the Biomedical Domain
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Parameterized concept weighting in verbose queries
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Exploiting medical hierarchies for concept-based information retrieval
Proceedings of the Seventeenth Australasian Document Computing Symposium
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Measures of semantic similarity between medical concepts are central to a number of techniques in medical informatics, including query expansion in medical information retrieval. Previous work has mainly considered thesaurus-based path measures of semantic similarity and has not compared different corpus-driven approaches in depth. We evaluate the effectiveness of eight common corpus-driven measures in capturing semantic relatedness and compare these against human judged concept pairs assessed by medical professionals. Our results show that certain corpus-driven measures correlate strongly (approx 0.8) with human judgements. An important finding is that performance was significantly affected by the choice of corpus used in priming the measure, i.e., used as evidence from which corpus-driven similarities are drawn. This paper provides guidelines for the implementation of semantic similarity measures for medical informatics and concludes with implications for medical information retrieval.