Handling Sparse Data by Successive Abstraction

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dc.creatorSamuelsson, Christer
dc.date1996-05-29
dc.date.accessioned2026-07-07T09:10:20Z
dc.date.available2026-07-07T09:10:20Z
dc.descriptionA general, practical method for handling sparse data that avoids held-out data and iterative reestimation is derived from first principles. It has been tested on a part-of-speech tagging task and outperformed (deleted) interpolation with context-independent weights, even when the latter used a globally optimal parameter setting determined a posteriori.
dc.description6 pages, uuencoded, gzipped PostScript
dc.identifierhttps://arxiv.org/abs/cmp-lg/9605034
dc.identifierhttp://arxiv.org/abs/cmp-lg/9605034
dc.identifierColing 96
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151320
dc.subjectComputation and Language
dc.titleHandling Sparse Data by Successive Abstraction
dc.typetext

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