Pattern-matching rules for the recognition of natural language dialogue expressions.

[摘要] Man-machine dialogues using everyday conversational English present problems for computer processing of natural language. Grammar-based parsers which perform a word-by-word, parts-of-speech analysis are too fragile to operate satisfactorily in real time intervieus allowing unrestricted English. In constructing a simulation of paranoid thought processes, we designed an algorithm capable of handling the linguistic expressions used by interviewers in teletyped diagnostic psychiatric interviews. The algorithm uses pattern-matching rules which attempt to characterize the input expressions by progressively transforming them into patterns uhich match, completely or fuzzily, abstract stored patterns. The power of this approach lies in its ability to ignore recognized and unrecognized words and still grasp the meaning of the message. The methods utilized are general and could serve any "host" system uhich takes natural language input.

[学科分类] 计算机科学（综合）