A study of abbreviations in MEDLINE abstracts.
Abbreviations are widely used in writing, and the understanding of abbreviations is important for natural language processing applications. Abbreviations are not always defined in a document and they are highly ambiguous. A knowledge base that consists of abbreviations with their associated senses and a method to resolve the ambiguities are needed. In this paper, we studied the UMLS coverage, textual variants of senses, and the ambiguity of abbreviations in MEDLINE abstracts. We restricted our study to three-letter abbreviations which were defined using parenthetical expressions. When grouping similar expansions together and representing senses using groups, we found that after ignoring senses where the total number of occurrences within the corresponding group was less than 100, 82.8% of the senses matched the UMLS, covered over 93% of occurrences that were considered, and had an average of 7.74 expansions for each sense. Abbreviations are highly ambiguous: 81.2% of the abbreviations were ambiguous, and had an average of 16.6 senses. However, after ignoring senses with occurrences of less than 5, 64.6% of the abbreviations were ambiguous, and had an average of 4.91 senses.
Liu
Hongfang
H
Computer Science Division, Graduate School and University Center, Columbia University, New York, NY, USA.
Aronson
Alan R
AR
Friedman
Carol
C
D000004:Abbreviations as Topic; D000043:Abstracting and Indexing; D016239:MEDLINE; D017432:Unified Medical Language System