Please use this identifier to cite or link to this item: http://hdl.handle.net/1880/46584
Title: A PRINCIPLED ANALOGICAL TOOL BASED ON EVALUATIONS OF PARTIAL CORRESPONDENCES OVER CONCEPTUAL GRAPHS
Authors: Leishman, Deborah
Keywords: Computer Science
Issue Date: 1-May-1989
Abstract: Analogy is one reasoning method used extensively and effectively by humans. Because analogy is so widely used, it is felt that giving computers this ability will make them more useful in supporting and emulating human reasoning. This thesis describes the development of a principled Analogical Tool which deals with this issue. The Analogical Tool results from instantiation of a general framework for analogy. This framework is based on analysis of previous work and characterizes analogies as common generalizations. Using conceptual graphs [Sowa, 1984] as the knowledge representation scheme for the general framework, the tool forms analogies and supports analogical inferencing based on them. Analogy formation in the tool derives minimal common generalizations as preferred "stronger" analogies. This formation is under the control of four formation evaluations and two ordering evaluations. The formation evaluations operate to determine how and what parts of the analogues are generalized and the ordering evaluations partially order the generalizations. Analogical inferencing based on the tool proceeds by hypothesizing new information in a target analogue based on information in a similar source analogue. This inferencing results in extension of the target analogue and formation of a new minimal common generalization. Testing of the Analogical Tool on examples of analogy taken from significant research, shows that the tool compares well with other systems. Examples range from simple analogy formation, through schema abstraction to metaphor understanding. Further critical evaluation of the tool shows limitations arise due to relevancy issues. These relevancy limitations are intrinsic to systems using inference based on similarity. An extensibility principle is introduced to deal with some relevancy limitations in inferencing based on the tool. Other relevancy issues are dealt with by the introduction of determination rules from Russell [1987].
URI: http://hdl.handle.net/1880/46584
Appears in Collections:Technical Reports

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