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00200	
00300	                      ABSTRACT
00400	
00500		Man-machine dialogues using  everday  conversational  English
00600	present   difficult  problems  for  computer  processing  of  natural
00700	language.    Grammar-based  parsers  which  perform  a  word-by-word,
00800	parts-of-speech analysis are too fragile to operate satisfactorily in
00900	real time interviews allowing unrestricted English. In constructing a
01000	simulation  of  paranoid  thought processes, we designed an algorithm
01100	capable of handling the linguistic expressions used  by  interviewers
01200	in  teletyped  diagnostic psychiatric interviews.  The algorithm uses
01300	pattern-matching  rules  which  attempt  to  characterize  the  input
01400	expressions  by  progressively  transforming them into patterns which
01500	match, completely or fuzzily, abstract stored patterns. The power  of
01600	this   approach   lies  in  its  ability  to  ignore  recognized  and
01700	unrecognized words and still grasp the meaning of the  message.   The
01800	methods  utilized are general and could serve any "host" system which
01900	takes natural language input.