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Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/99603
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dc.titleText compression via alphabet re-representation
dc.contributor.authorLong, Philip M.
dc.contributor.authorNatsev, Apostol I.
dc.contributor.authorVitter, Jeffrey Scott
dc.date.accessioned2014-10-27T06:05:45Z
dc.date.available2014-10-27T06:05:45Z
dc.date.issued1997
dc.identifier.citationLong, Philip M.,Natsev, Apostol I.,Vitter, Jeffrey Scott (1997). Text compression via alphabet re-representation. Data Compression Conference Proceedings : 161-170. ScholarBank@NUS Repository.
dc.identifier.issn10680314
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/99603
dc.description.abstractWe consider re-representing the alphabet so that a representation of a character reflects its properties as a predictor of future text. This enables us to use an estimator from a restricted class to map contexts to predictions of upcoming characters. We describe an algorithm that uses this idea in conjunction with neural networks. The performance of this implementation is compared to other compression methods, such as UNIX compress, gzip, PPMC, and an alternative neural network approach.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentINFORMATION SYSTEMS & COMPUTER SCIENCE
dc.description.sourcetitleData Compression Conference Proceedings
dc.description.page161-170
dc.description.codenDDCCF
dc.identifier.isiutNOT_IN_WOS
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