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Successful approaches to developing knowledge acquisition tools use
expectations of what the user has to add or may want to add, based on how new
knowledge fits within a knowledge base that already exists. When a knowledge
base is first created or undergoes significant extensions and changes, these
tools cannot provide much support. We present an approach to creating
expectations when a new knowledge base is built, and describes a knowledge
acquisition tool that we implemented using this approach that supports users
in creating problem-solving knowledge. As the knowledge base grows, the
knowledge acquisition tool derives more frequent and more reliable
expectations that result from enforcing constraints in the knowledge
representation system, looking for missing pieces of knowledge in the
knowledge base, and working out incrementally the inter-dependencies among the
different components of the knowledge base. Our preliminary evaluations show
a thirty percent time savings during knowledge acquisition. Moreover, by
providing tools to support the initial phases of knowledge base development
many mistakes are detected early on and even avoided altogether. We believe
that our approach contributes to improving the quality of the knowledge
acquisition process and of the resulting knowledge-based systems as well.
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