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Mimicking human language processing features using fuzzy syntax-semantics analyzer and semantic interpreter

The main aim of this dissertation has been to mimic natural language processing capabilities of human beings in a natural language processing system. The design and the development of the Syntax-Semantics analyzer (SS-analyzer) and the use of fuzzy in various language processing stages form the main crux of this dissertation. / The SS-analyzer is made up of two main modules: the syntax module and the semantics module. The SS-analyzer processes the input natural language sentences in an incremental fashion. The syntax and the semantics analyzer work in a coordinated manner to extract the meaning out of the input natural language sentences. This extracted meaning is then represented in a fuzzy relational representation structure. / The semantic interpreter complements the SS-analyzer in determining the meaning of input sentences when they are grammatically incorrect or do not make sense semantically. If the SS-analyzer is unable to determine the meaning of the input sentences, the semantic interpreter uses the contextual knowledge to determine the meaning. A prototype natural language processing system has been developed to test these theories. / Source: Dissertation Abstracts International, Volume: 53-09, Section: B, page: 4783. / Major Professor: L. J. Kohout. / Thesis (Ph.D.)--The Florida State University, 1992.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76737
ContributorsNagarajan, Sujatha., Florida State University
Source SetsFlorida State University
LanguageEnglish
Detected LanguageEnglish
TypeText
Format202 p.
RightsOn campus use only.
RelationDissertation Abstracts International

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