This dissertation focuses on developing and evaluating hybrid approaches for analyzing free-form text in the medical domain. This research draws on natural language processing (NLP) techniques that are used to parse and extract concepts based on a controlled vocabulary. Once important concepts are extracted, additional machine learning algorithms,…

Examines the vocabulary and communication constructs that are used by novices and domain experts to describe objects in an object identification task. Results suggest that indexing and retrieval systems should provide semantic level similarity mechanisms to allow for whole-object as well as part-wise visual analogy. The systems should also provide…

Focuses on natural language processing (NLP) in information retrieval. Defines the seven levels at which people extract meaning from text/spoken language. Discusses the stages of information processing; how an information retrieval system works; advantages to adding full NLP to information retrieval systems; and common problems with information…

The accelerating rate of data generation and resulting publications are taxing the ability of scientific investigators to stay current with the emerging literature. This problem, acute in science, is not uncommon in other areas. New approaches to managing this explosion of information are needed. While it is only possible to read one paper or…