Please use this identifier to cite or link to this item: http://ir.inflibnet.ac.in/handle/1944/501
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dc.contributor.authorIngle, Mayaen_US
dc.contributor.authorChandwani, Men_US
dc.date.accessioned2005-05-10T09:50:32Zen_US
dc.date.accessioned2010-04-08T08:47:54Z-
dc.date.available2005-05-10T09:50:32Zen_US
dc.date.available2010-04-08T08:47:54Z-
dc.date.issued2005-02-02en_US
dc.identifier.isbn81-902079-0-3en_US
dc.identifier.urihttp://hdl.handle.net/1944/501en_US
dc.description.abstractIn this paper, we first present a memoized parsing method for reducing the efforts of computation in parsing the strings/ sentences of a formal’ natural language. We then discuss the statistical parsing that extracts the maximum/ most likelihood parse amongst the several parses of a string/ sentence in formal and natural domain as the most appropriate representative in disambiguation process. We integrate the statistical and memoized parsing together to achieve an efficient parsing technique. This integrated approach allows us to obtain the memoized-most-likelihood parse. Memoized-most-likelihood parse has an additional performance strength in the sense that it is highly useful further in parsing semantics.en_US
dc.format.extent219917 bytesen_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherINFLIBNET Centreen_US
dc.subjectNatural Language Processingen_US
dc.subjectDisambiguationen_US
dc.subjectStatistical Parsingen_US
dc.subjectCharacter Recognitionen_US
dc.titlePerformance of Memoized- Most- Likelihood Parsing in Disambiguation Processen_US
dc.typeArticleen_US
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