Concept Based Knowledge Discovery from Biomedical Literature
type: CreativeWork
description: This thesis describes and introduces novel methods for knowledge discovery and presents a software system that is able to extract information from biomedical literature, review interesting connections between various biomedical concepts and in so doing, generates new hypotheses. The experimental results obtained by using methods described in this thesis, are compared to currently published results obtained by other methods and a number of case studies are described. This thesis shows how the technology, resented can be integrated with the researchers own knowledge, experimentation and observations for optimal progression of scientific research.
abstract: This thesis describes and introduces novel methods for knowledge discovery and presents a software system that is able to extract information from biomedical literature, review interesting connections between various biomedical concepts and in so doing, generates new hypotheses. The experimental results obtained by using methods described in this thesis, are compared to currently published results obtained by other methods and a number of case studies are described. This thesis shows how the technology, resented can be integrated with the researchers own knowledge, experimentation and observations for optimal progression of scientific research.
author: Radovanovic, Aleksandar.
keywords: Bioinformatics, Text mining, PubMed, Entity recognition, Information extraction, Relation Extraction, Levenshtein distance, Supervised classification, Natural Language Processing, Machine learning
date published: 2009
date modified: 2026-07-24T06:00:34Z
provider: University of the Western Cape
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of the Western Cape