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Entity Resolution in Healthcare

Entity Resolution in Healthcare

Copyright: © 2014 |Pages: 14
ISBN13: 9781466651982|ISBN10: 1466651989|EISBN13: 9781466651999
DOI: 10.4018/978-1-4666-5198-2.ch017
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MLA

Hongzhi Wang. "Entity Resolution in Healthcare." Innovative Techniques and Applications of Entity Resolution, IGI Global, 2014, pp.385-398. https://doi.org/10.4018/978-1-4666-5198-2.ch017

APA

H. Wang (2014). Entity Resolution in Healthcare. IGI Global. https://doi.org/10.4018/978-1-4666-5198-2.ch017

Chicago

Hongzhi Wang. "Entity Resolution in Healthcare." In Innovative Techniques and Applications of Entity Resolution. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-5198-2.ch017

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Abstract

Abbreviations are common in biomedical documents, and many are ambiguous in the sense that they have several potential expansions. Identifying the correct expansion is necessary for language understanding and important for applications such as document retrieval. Identifying the correct expansion can be viewed as a Word Sense Disambiguation (WSD) problem. Previous approaches to resolving this problem have made use of various sources of information including linguistic features of the context in which the ambiguous term is used and domain-specific resources, such as UMLS. This chapter compares a range of knowledge sources, which have been previously used, and introduce a novel one: MeSH terms. The best performance is obtained using linguistic features in combination with MeSH terms.

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