Improving Accuracy by Combining Rule-Based and Case-Based Reasoning.

Abstract

An architecture is presented for combining rule based and case based reasoning. The architecture is intended for domains that are understood reasonably well, but still imperfectly. It uses a set of rules, which are taken to be only approximately correct, to obtain a preliminary answer for a given problem; it then draws analogies from cases to handle exceptions to the rules. Having rules together with cases not only increases the architecture's domain coverage, it also allows innovative ways of doing case-based reasoning: the same rules that are used for rule-based reasoning are also used by the case-based component to do case indexing and case adaptation. The architecture was applied to the task of name pronunciation, and, with minimal knowledge engineering, was found to perform almost at the level of the best commercial systems. Moreover, its accuracy was found to exceed what it could have achieved with rules or cases alone, thus demonstrating the accuracy improvement afforded by combining rule-based and case-based reasoning.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1995
Accession Number
ADA315313

Entities

People

  • Andrew R. Golding
  • Paul Simon Rosenbloom

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Cognitive Science
  • Computational Science
  • Computers
  • Dictionaries
  • Engineering
  • Expert Systems
  • Grammars
  • Information Science
  • Language
  • Law
  • Linguistics
  • Machine Learning
  • Reasoning
  • Rule Based Systems
  • Test Sets

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence