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dc.identifier.urihttp://hdl.handle.net/11401/77251
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeThesis
dcterms.abstractThis paper is an attempt at describing the priority of skimming in enhancing the lives of the visually impaired and dyslexic. The paper distinguishes summarization from skimming. It speaks of skimming a given blob of text. And with it, arises some unique challenges. So, the paper tries to tackle these challenges by enhancing and speeding up the algorithm. The algorithm breaks down the input into smaller and compact skimmed results, which when used as the input to the algorithm completely fastens the algorithm with a tremendous decrease in run time. The ways of creating the compact skimmed version of the text are described in the paper, at the same time comparing and contrasting the differences between those ways. The paper finally describes the fastest algorithm, its origin and the way to derive the shortest skimmed version to input to the final algorithm.
dcterms.available2017-09-20T16:52:17Z
dcterms.contributorRamakrishnan, IVen_US
dcterms.contributorFodor, Paulen_US
dcterms.contributorBorodin, Yevgen.en_US
dcterms.creatorSatpute, Aaswad Anil
dcterms.dateAccepted2017-09-20T16:52:17Z
dcterms.dateSubmitted2017-09-20T16:52:17Z
dcterms.descriptionDepartment of Computer Scienceen_US
dcterms.extent23 pg.en_US
dcterms.formatMonograph
dcterms.formatApplication/PDFen_US
dcterms.identifierhttp://hdl.handle.net/11401/77251
dcterms.issued2016-12-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2017-09-20T16:52:17Z (GMT). No. of bitstreams: 1 Satpute_grad.sunysb_0771M_13060.pdf: 312057 bytes, checksum: e1776636a81a69d8e17372384c10c445 (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectNatural Language Processing, Skimming
dcterms.subjectComputer science
dcterms.titleEfficient Skimming of Text
dcterms.typeThesis


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