Event Entry
What and Who
Biomedical Knowledge Base Construction from Text and its Applications in Knowledge-based Systems
Date, Time and Location
Abstract
comprehensive knowledge about people, events, places, etc., domain-specific KBs,
such as on health, are equally important, but are less explored. Consequently, a
comprehensive and expressive health KB that spans all aspects of biomedical
knowledge is still missing. The main goal of this thesis is to develop
principled methods for building such a KB and enabling knowledge-centric
applications. We address several challenges and make the following contributions:
- 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.
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