Automatic knowledge base construction from unstructured text - Sequeira, José Francisco Rodrigues (2017)
Taking into account the overwhelming number of biomedical publications being produced, the effort required for a user to efficiently explore those publications in order to establish relationships between a wide range of concepts is staggering. This dissertation presents GRACE, a web-based platform that provides an advanced graphical exploration interface that allows users to traverse the biomedical domain in order to find explicit and latent associations between annotated biomedical concepts belonging to a variety of semantic types (e.g., Genes, Proteins, Disorders, Procedures and Anatomy). The knowledge base utilized is a collection of MEDLINE articles with English abstracts. These annotations are then stored in an efficient data storage that allows for complex queries and high-performance data delivery. Concept relationship are inferred through statistical analysis, applying association measures to annotated terms. These processes grant the graphical interface the ability to create, in real-time, a data visualization in the form of a graph for the exploration of these biomedical concept relationships.