COURSE DESCRIPTION
Theory Outline
- Knowledge representation and reasoning systems. Knowledge representation and reasoning methods. Architecture of knowledge systems. Development of knowledge systems.
- Introduction to semantic web. Structured Web Documents in XML. Describing Web Resources in RDF. Web Ontology Language: OWL. Logic and Inference: Rules (Rule markup in XML).
- Decision support systems in the web. Intelligence and knowledge systems in the web (web and logic programming). Web Intelligence techniques. Web Inference Engines. Semantics and Ontology Engineering.
Lab Outline
- Learning an open source knowledge system shell like Pyke, CLIPS, JESS, etc.
- Development of knowledge systems. Knowledge acquisition from experts. Construction of a knowledge system/an expert system.
- Learning of the ontology development system Protégé and the inference engine Pellet.
- Development of web applications (Data integration, Information retrieval, Portals, e-Learning, Web Services, etc).
- Development of knowledge systems for the web either in Pellet, or in Prolog or in Java, or in a knowledge system shell like Pyke, Clips, Jess, etc.
RECOMMENDED BIBLIOGRAPHY
- Grigoris Antoniou and Frank van Harmelen, A Semantic Web Primer, The MIT Press, 2004, ISBN: 0-262-01210-3.
- S.L. Kendal, M. Creen, An Introduction to Knowledge Engineering, Springer, 2007, ISBN 13: 978-1-84628-475-5.
- M. Sasikumar, S. Ramani, S. Muthu Raman, KSR Anjaneyulu, R. Chandrasenkar, A Practical Introduction to Rule Based Expert Systems, Narosa Publishing House, 2007.
PREREQUISITE KNOWLEDGE
- Propositional and predicate logic.
Programming in Prolog.
Knowledge representation and reasoning.
Uncertain knowledge and reasoning.
Implementation of knowledge representation and reasoning methods in Prolog.