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From: marcel@uiucdcs.UUCP
Newsgroups: net.ai
Subject: Re: metaphors - (nf)
Message-ID: <32300025@uiucdcs.UUCP>
Date: Wed, 18-Apr-84 12:22:00 EST
Article-I.D.: uiucdcs.32300025
Posted: Wed Apr 18 12:22:00 1984
Date-Received: Fri, 20-Apr-84 01:51:01 EST
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Nf-ID: #R:sri-arpa:-1221400:uiucdcs:32300025:000:1294
Nf-From: uiucdcs!marcel    Apr 18 11:22:00 1984

#R:sri-arpa:-1221400:uiucdcs:32300025:000:1294
uiucdcs!marcel    Apr 18 11:22:00 1984

You might like to think about partial matching as a step toward analogical
or metaphorical reasoning. Try the following:

Fox, MS and Mostow, DJ  Maximal consistent interpretations of errorful data in
	hierarchically modelled domains. IJCAI-77, 165ff.
Kline, PJ  The superiority of relative criteria in partial matching and
	generalization. IJCAI-81, 296ff

Perhaps also check the growing literature on abductive reasoning, hypothesis
formation, disambiguation, categorization, diagnosis, etc. Some papers I found
most interesting:

Carbonell, JR and Collins, AM  Natural semantics in Artificial Intelligence.
	IJCAI-73, 344ff. { the SCHOLAR system }
Collins, A  et al   Reasoning from incomplete knowledge. In BOBROW & COLLINS's
	book "Representation and Understanding", Academic Press, NY (1975).
	{ more on SCHOLAR }
Pople, HE  On the mechanization of abductive logic. IJCAI-73, 147ff



In NL research the role of expectations has become important to expedite
disambiguation. Includes use of attention focusing. Some very well-known work
at Yale on this. See eg papers by Riesbeck and Schank in the book by Waterman
& Hayes-Roth ('78), and by Schank & DeJong in Machine Intelligence 9. Lots of
other work too. Happy wading!

					Marcel Schoppers
					{ ihnp4 | pur-ee } ! uiucdcs ! marcel