About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
IBM J. Res. Dev
Paper
Enhancing a biomedical information extraction system with dictionary mining and context disambiguation
Abstract
Journals and conference proceedings represent the dominant mechanisms for reporting new biomedical results. The unstructured nature of such publications makes it difficult to utilize data mining or automated knowledge discovery techniques. Annotation (or markup) of these unstructured documents represents the first step in making these documents machine-analyzable. Often, however, the use of similar (or the same) labels for different entities and the use of different labels for the same entity makes entity extraction difficult in biomedical literature. In this paper we present a system called BioAnnotator for identifying and classifying biological terms in documents. BioAnnotator uses domain-based dictionary lookup for recognizing known terms and a rule engine for discovering new terms. We explain how the system uses a biomedical dictionary to learn extraction patterns for the rule engine and how it disambiguates biological terms that belong to multiple semantic classes. © Copyright 2004 by International Business Machines Corporation.