Abstract
This chapter discusses a number of differences between traditional database retrieval and the retrieval problems that arise from the large knowledge bases of rules that occur in many expert systems applications. It outlines several principles and techniques applicable to these problems, including a basic principle of factoring. In particular, conceptually factored, taxonomic representation systems such as KL-ONE appear to be well suited to such applications. Such knowledge structures can be used to perform a kind of abstract “parsing” of a situation, using the patterns and schemata of the knowledge base as a “grammar.” The way in which elements of the knowledge base are accessed in this process differs substantially from the way in which elements of a traditional database are accessed. To handle large knowledge bases of rule-like information, it will be necessary to combine insights of knowledge representation research with those of database organization and retrieval.
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© 1986 Springer-Verlag New York Inc.
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Woods, W.A. (1986). Knowledge Base Retrieval. In: Brodie, M.L., Mylopoulos, J. (eds) On Knowledge Base Management Systems. Topics in Information Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4980-1_18
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DOI: https://doi.org/10.1007/978-1-4612-4980-1_18
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