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.
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