 |
| |
Adam Pease, CEO,
Articulate Software |
|
|
|
Adam Pease is CEO of
Articulate Software. He has led research in ontology, linguistics
and formal inference, including development of the Suggested
Upper Merged Ontology (SUMO) the Controlled English to Logic
Translation (CELT) system, the Core Plan Representation (CPR),
and the Sigma knowledge engineering environment. He led integration
teams for the DARPA High Performance Knowledge Bases and DARPA
Quorum programs and project teams participating in the ARDA
Novel Intelligence For Massive Data (NIMD) project, DARPA Agent
Markup Language (DAML), and other projects for the DoD community.
Sharing research under open licenses, in order to achieve the
widest possible dissemination and technology transfer has been
a core element of his research program and his products have
been downloaded by thousands of people around the world. He
has chaired several workshops at the national conference of
the American Association for Artificial Intelligence and International
Joint Conference on Artificial Intelligence, and published
over 30 papers. He is a member of the board of the Global WordNet
Association. |
|
|
| |
 Presentation
The Role of Ontologies
This talk will discuss applications of the Suggested Upper Merged Ontology
(SUMO) to semantic integration. SUMO is the largest formal, open source ontology
available today, with 20,000 terms and 60,000 axioms covering upper level
concepts and a range of domains. It has been mapped to all of the WordNet
English lexicon to support language understanding applications.
Reuse of information is as critical as reuse of software
libraries. Having precise definitions for terms in an ontology
is also crucial to realize the advantages touted for the
semantic web. This talk discusses upper ontologies and the
value of ontology reuse, as well as the requirements and
benefits for formal definitions of terms in an ontology.
A range of current applications of SUMO are described along
with a roadmap for applying SUMO to new domains
 return
to program |
|
|
|
|
|
