- To construct a health KB,
we devise a largely automated and scalable pattern-based knowledge extraction
method covering a spectrum of different text genres and distilling a wide
variety of facts from different biomedical areas.
- To consider higher-arity relations, crucial for proper
knowledge representation in advanced domain such as health, we generalize
the fact-pattern duality paradigm of previous methods. A key novelty is the
integration of facts with missing arguments by extending our framework to
partial patterns and facts by reasoning over the composability of partial
facts.
- To demonstrate the benefits of a health KB, we devise systems for
entity-aware search and analytics and for entity-relationship-oriented
exploration.
Extensive experiments and use-case studies demonstrate the viability of the
proposed approaches.