Abstract
Developing knowledge bases using knowledge-acquisition tools is difficult because each stage of development requires performing a distinct knowledge-acquisition task. This paper describes these different tasks and surveys current tools that perform them. It also addresses two issues confronting tools for start-to-finish development of knowledge bases. The first issue is how to support multiple stages of development. This paper describes Protos, a knowledge-acquisition tool that adjusts the training it expects and assistance it provides as its knowledge grows. The second issue is how to integrate new information into a large knowledge base. This issue is addressed in the description of a second tool, KI, that evaluates new information to determine its consequences for existing knowledge.
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© 1989 Kluwer Academic Publishers, Boston
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Bareiss, R., Porter, B.W., Murray, K.S. (1989). Supporting Start-to-Finish Development of Knowledge Bases. In: Marcus, S. (eds) Knowledge Acquisition: Selected Research and Commentary. Machine Learning, vol 92. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1531-5_4
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DOI: https://doi.org/10.1007/978-1-4613-1531-5_4
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