Evidential support logic, FRIL and case based reasoning

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Abstract
Knowledge representation for expert systems and decision support systems is often in the form of rules and answering queries is performed by backward and forward reasoning. Case based reasoning is an alternative to this. In its most basic form, a query is answered by reference with data given as part of the query to similar cases in a data base. In this article we will use a mixture of case based reasoning and rule inference methods. Rules will represent generalizations of information relevant to prototypical cases. the prototypical cases are chosen from a database of examples. Partial matchings of features in a rule are used to infer a conclusion even when information to evaluate the body of the rule is incomplete. Features are given importance weights and inferred conclusions from various rules are combined using mass assignment theory © 1993 John Wiley & Sons, Inc.

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