Natural Language Processing :: essays research papers

indwelling Language Processing     There reach been high hopes for Natural Language Processing. NaturalLanguage Processing, withal known simply as NLP, is part of the broader field ofArtificial Intelligence, the effort towards making machines think. Computers mayappear intelligent as they crunch numbers and care for information with blazingspeed. In truth, computers are nothing but dumb slaves who only understand on oroff and are limited to carry instructions. But since the invention of thecomputer, scientists have been attempting to make computers not only appearintelligent but be intelligent. A truly intelligent computer would not belimited to rigid computer language commands, but instead be able to process andunderstand the English language. This is the concept behind Natural LanguageProcessing.     The phases a message would go through during NLP would consist ofmessage, syntax, semantics, pragmatics, and intended centre. (M. A. Fisc her,1987) Syntax is the grammatical structure. Semantics is the literal meaning.Pragmatics is world knowledge, knowledge of the context, and a flummox of thesender. When syntax, semantics, and pragmatics are applied, accurate NaturalLanguage Processing will exist.     Alan Turing predicted of NLP in 1950 (Daniel Crevier, 1994, page 9)     "I believe that in about fifty years beat it will be possible toprogram computers .... to make them play the imitation game so well that anaverage interrogator will not have more than than 70 per cent chance of making theright identification after five minutes of questioning."     But in 1950, the current computer technology was limited. Because ofthese limitations, NLP programs of that day focused on exploiting the strengthsthe computers did have. For example, a program called SYNTHEX tried to determinethe meaning of sentences by flavour up each word in its encyclopedia. Anot herearly approach was Noam Chomskys at MIT. He believed that language could beanalyzed without any reference to semantics or pragmatics, just by simplylooking at the syntax. Both of these techniques did not work. Scientistsrealized that their Artificial Intelligence programs did not think like peopledo and since people are much more intelligent than those programs they decidedto make their programs think more closely like a person would. So in the late1950s, scientists shifted from stressful to exploit the capabilities of computersto trying to emulate the human brain. (Daniel Crevier, 1994)     Ross Quillian at Carnegie Mellon wanted to try to program theassociative aspects of human memory to create better NLP programs. (DanielCrevier, 1994) Quillians idea was to determine the meaning of a word by thewords around it. For example, look at these sentences After the strike, the