This presentation will give an overview of our ongoing work in
developing knowledge extraction methods for description logic based
ontologies. Because the stored knowledge is not only given by the axioms
stated in an ontology but also by the knowledge that can be inferred
from these axioms, knowledge extraction is a challenging problem.
Forgetting creates a compact and faithful representation of the stored
knowledge over a user-specified signature by performing inferences on
the symbols outside this signature.
After an introduction of the idea of
forgetting, an overview of our forgetting tools and some applications we
have explored, I will discuss recent collaborative work with SNOMED
International to create bespoke knowledge extraction software the
medical ontology SNOMED CT. The software creates a self-contained
subontology containing definitions of a specified set of focus concepts
which minimises the number of supporting symbols used and satisfies
SNOMED modelling guidelines. Such subontologies make it easier to reuse
and share content, assist with ontology analysis, and querying and
classification is faster. The talk will give an overview of this
research spanning several years, focussing on key ideas, findings,
practical challenges encountered and current applications.
Back to Program