Artificial Intelligence Tutorial
The Artificial Intelligence Tutorials (AIT) 2010 is a world class tutorial session organised by
MIMOS berhad on 26th and 27th July 2010. In this event, we are privileged to have EIGHT invited
experts on Artificial Intelligence (AI), specialised in Semantic Technology from USA, Austria,
Germany, Hong Kong, France, and Malaysia. The purpose of the tutorials is to promote world class
research and development in AI. The tutorials are organized jointly by MIMOS BERHAD and the Center
of Excellence in Semantic Technology and Augmented Reality (CoE-STAR, UNIMAS). It will be co-located
with
the 2nd Malaysian Joint Conference on Artificial
Intelligence (MJCAI 2010) ,
the Semantic Technology
And Knowledge Engineering Conference (STAKE 2010)a and
the International Conference on Conceptual Structures(ICCS 2010) at Damai Beach Resort, Kuching,
Sarawak, Malaysia.
Prof. John Sowa
Bio-Data:
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Everything implemented on a computer has semantics that is meaningful to the implementers and the users.
Problems arise when different systems and the data they process have different semantics. More problems
arise when the users and implementers make different assumptions about the semantics. Similar problems
arise as systems evolve over time with updates, revisions, extensions, and connections to independently
developed systems. Computer systems have been successfully interacting across long distance networks for
over forty years. But a tight integration, even of local systems, is hard to achieve because of the
difficulty of ensuring that all components will interpret the same data in the same way. Further complications
are created by different notations and conventions in databases, knowledge bases, the Semantic Web,
folksonomies, and legacy systems that have no explicit semantic notations. Finally, even the most precisely
defined and integrated semantic systems must interact with people who have little or no knowledge of the
precise definitions and little time, desire, or ability to learn them.
This tutorial will use examples and case studies to illustrate these problems, various ways of addressing them,
and the challenges for the future. Following are the topics covered:
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Examples of semantic systems and their methods for representing and using logic and ontology
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Aligning and relating different ontologies expressed in the same notation or different notations
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Methods of communication and control among loosely coupled systems and more tightly integrated systems
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Diagrams and controlled natural languages for expressing formal ontologies in humanly readable forms
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Methods for extracting the implicit ontologies and terminologies from legacy systems and documents that
have no semantic annotations
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Supporting interoperability among heterogeneous systems with different semantic representations, including
systems with no explicit semantics
John F. Sowa is the President and a Co-founder of VivoMind Intelligence, Inc. Earlier, he spent thirty years
working on research and development projects at IBM. He has a B.S. in mathematics from MIT, an M.A. in applied
mathematics from Harvard, and a Ph.D. in computer science from the Vrije Universiteit Brussel. He is a fellow
of the American Association for Artificial Intelligence, and he has published many books and articles on
knowledge representation, ontology, and related topics in artificial intelligence. With his colleagues at
VivoMind, he has been developing novel methods for using conceptual graphs and other logic-based languages
for analyzing and relating structured and unstructured knowledge sources.
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