Re-using web information for building flexible domain knowledge

Authors:
Mohammed Abdel Razek;Claude Frasson;Marc Kaltenbach
Affiliations:
Computer Science Department and Operational Research University of Montreal, Montreal, Québec, Canada;Computer Science Department and Operational Research University of Montreal, Montreal, Québec, Canada;Computer Science Department and Operational Research University of Montreal, Montreal, Québec, Canada
Venue:
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
Year:
2003

Citing 2
Cited 0

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A context-based information agent for supporting education on the web

ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI

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Abstract

Building a knowledge base for a given domain usually involves a subject matter expert (tutor) and a knowledge engineer. Our approach is to create mechanisms and tools that allow learners to build knowledge bases through a learning session on-line. The Dominant Meaning Classification System (DMCS) was designed to automatically extract, and classify segments of information (chunks). These chunks could well automate knowledge construction, instead of depending on the analysis of tutors. We use a dominant meaning space method to classify extracted chunks. Our experiment shows that this greatly improves domain knowledge.