Abstract
A central problem of many branches of artificial intelligence (AI) research is that ofunderstanding natural language (NL). Many attempts have been made to model understanding with computer systems that demonstrate competence at such tasks as question answering, paraphrasing, and following commands. The system to be described in this paper combines some of these language functions in a single, general process based on the creation of an associative memory net as a result of experience. The author has written a large, interactive computer program that accepts unsegmented input strings of natural language from a human trainer and, after processing each string, outputs a natural language response. The processing of the string may involve transforming it to some other form in the same or another language, or answering an input question based on information previously learned by the program.
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Jordan, S.R. A natural language understander based on a freely associated learned memory net. International Journal of Computer and Information Sciences 6, 9–25 (1977). https://doi.org/10.1007/BF00991480
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DOI: https://doi.org/10.1007/BF00991480