Discovery Browsing with Semantic Predications and Graph Theory

Bartlomiej Wilkowski, Marcelo Fiszman, Christopher M. Miller, Dimitar Hristovski, Sivaram Arabandi, Graciela Rosemblat, Thomas C. Rindflesch

AbstractWe present an extension to literature-based discovery that goes beyond making discoveries to a principled way of
navigating through selected aspects of some biomedical domain. The method is a type of "discovery browsing" that
guides the user through the research literature on a specified phenomenon. Poorly understood relationships may be
explored through novel points of view, and potentially interesting relationships need not be known ahead of time. In
a process of "cooperative reciprocity" the user iteratively focuses system output, thus controlling the large number
of relationships often generated in literature-based discovery systems. The underlying technology exploits SemRep
semantic predications represented as a graph of interconnected nodes (predication arguments) and edges (predicates).
The system suggests paths in this graph, which represent chains of relationships. The methodology is illustrated with
depressive disorder and focuses on the interaction of inflammation, circadian phenomena, and the neurotransmitter
norepinephrine. Insight provided may contribute to enhanced understanding of the pathophysiology, treatment, and
prevention of this disorder.
Keywordsliterature-based discovery, semantic predications, graph theory, semantics, ontology
TypeConference paper [Submitted]
ConferenceAMIA 2011
Year2011    Month March
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing

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