Measures of semantic similarity and relatedness in the biomedical domain
Journal of Biomedical Informatics
A Survey of Automatic Query Expansion in Information Retrieval
ACM Computing Surveys (CSUR)
An evaluation of corpus-driven measures of medical concept similarity for information retrieval
Proceedings of the 21st ACM international conference on Information and knowledge management
Exploiting semantics for improving clinical information retrieval
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
The seventeenth australasian document computing symposium
ACM SIGIR Forum
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Search technologies are critical to enable clinical staff to rapidly and effectively access patient information contained in free-text medical records. Medical search is challenging as terms in the query are often general but those in relevant documents are very specific, leading to granularity mismatch. In this paper we propose to tackle granularity mismatch by exploiting subsumption relationships defined in formal medical domain knowledge resources. In symbolic reasoning, a subsumption (or 'is-a') relationship is a parent-child relationship where one concept is a subset of another concept. Subsumed concepts are included in the retrieval function. In addition, we investigate a number of initial methods for combining weights of query concepts and those of subsumed concepts. Subsumption relationships were found to provide strong indication of relevant information; their inclusion in retrieval functions yields performance improvements. This result motivates the development of formal models of relationships between medical concepts for retrieval purposes.