ADAM: another database of abbreviations in MEDLINE
Bioinformatics
A system for finding biological entities that satisfy certain conditions from texts
Proceedings of the 17th ACM conference on Information and knowledge management
A task-specific query and document representation for medical records search
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Learning to combine representations for medical records search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Inferring conceptual relationships to improve medical records search
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
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Expanding a query with acronyms or their corresponding 'long-forms' has not been shown to provide consistent improvements in the biomedical IR literature. The major open issue with expanding acronyms in a query is their inherent ambiguity, as an acronym can refer to multiple long-forms. At the same time, a long-form identified in a query can be expanded with its acronym(s); however, some of these may be also ambiguous and lead to poor retrieval performance. In this work, we propose the use of the EMIM (Expected Mutual Information Measure) between a long-form and its abbreviated acronym to measure ambiguity. We experiment with expanding both acronyms and long-forms identified in the queries from the adhoc task of the TREC 2004 Genomics track. Our preliminary analysis shows the potential of both acronym and long-form expansions for biomedical IR.