How much is enough?: Data requirements for statistical NLP

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dc.creatorLauer, Mark
dc.date1995-09-07
dc.date.accessioned2026-07-07T09:10:00Z
dc.date.available2026-07-07T09:10:00Z
dc.descriptionIn this paper I explore a number of issues in the analysis of data requirements for statistical NLP systems. A preliminary framework for viewing such systems is proposed and a sample of existing works are compared within this framework. The first steps toward a theory of data requirements are made by establishing some results relevant to bounding the expected error rate of a class of simplified statistical language learners as a function of the volume of training data.
dc.description9 pages
dc.identifierhttps://arxiv.org/abs/cmp-lg/9509001
dc.identifierhttp://arxiv.org/abs/cmp-lg/9509001
dc.identifier2nd Conference of the Pacific Association for Computational Linguistics, Brisbane, Australia
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151234
dc.subjectComputation and Language
dc.titleHow much is enough?: Data requirements for statistical NLP
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