Seminar: Automatic NLP adaptation for clinical subdomains with Sublanguage Semantic Schema System
Dec 1, 2011 10:00 AM
Location: HSEB Room 4100B
Date: December 8, 2011
Time: 4:15 pm
Olga Patterson is the 2011 recipient of the John D. Morgan Award. Her presentation this week as part of our seminar series will be followed by a brief award presentation with a reception and light refreshments at 5:15 pm in the HSEB 5th Floor Atrium (by the elevators). Members of the Morgan family will be in attendance.
Domain adaptation of natural language processing systems is challenging because it requires human expertise. While manual effort is effective in creating a high quality knowledge base, it is expensive and time consuming. Clinical text adds another layer of complexity to the task due to privacy and confidentiality restrictions that hinder the ability to share training corpus among different research groups. Semantic ambiguity is a major barrier for effective and accurate concept recognition by natural language processing systems.
In my research I propose an automated domain adaptation method that utilizes Sublanguage Semantic Schema for all-word word sense disambiguation of clinical narrative. According to the sublanguage theory developed by Zellig Harris, domain-specific language is characterized by a relatively small set of semantic classes that combine into a small number of sentence types. Previous research relied on manual analysis to create language models that could be used for more effective natural language processing. Building on previous research on semantic type disambiguation, I propose a method of resolving semantic ambiguity utilizing automatically acquired semantic type disambiguation rules applied on clinical text ambiguously mapped to a standard set of concepts.
This research aims to provide an automatic method to acquire Sublanguage
Semantic Schema (S3) and apply this model to disambiguate terms that map
to more than one concept with different semantic types.
Olga Patterson is a PhD candidate at the University of Utah Department of Biomedical Informatics.