"Units of Meaning" in Medical Documents: A Natural Language Processing Perspective
Joseph R. Barr, Dimitri Popolov · International Journal of Semantic Computing · 2014
This paper discusses principles for the design of natural language processing (NLP) systems to automatically extract data from doctor's notes, laboratory results and other medical documents in free-form text. We argue that rather than searching for "atom units of meaning" in the text and then trying to generalize them into a broader set of documents through increasingly complicated system of rules, an NLP practitioner should take concepts as a whole and as a meaningful unit of text. This simplifies the rules and makes NLP system easier to maintain and adapt. The departure point is purely practical; however, a deeper investigation of typical problems with the implementation of such systems leads us to a discussion of broader linguistic theories underlying the NLP practices, such as metaphors theories and models of human communication.