Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering (Extended Version)

dc.contributor.author Tu, Kewei
dc.contributor.author Honavar, Vasant
dc.contributor.department Computer Science
dc.date 2018-02-13T23:50:23.000
dc.date.accessioned 2020-06-30T01:55:57Z
dc.date.available 2020-06-30T01:55:57Z
dc.date.issued 2008-01-01
dc.description.abstract <p>This paper presents PCFG-BCL, an unsupervised algorithm that learns a probabilistic context-free grammar (PCFG) from positive samples. The algorithm acquires rules of an unknown PCFG through iterative biclustering of bigrams in the training corpus. Our analysis shows that this procedure uses a greedy approach to adding rules such that each set of rules that is added to the grammar results in the largest increase in the posterior of the grammar given the training corpus. Results of our experiments on several benchmark datasets show that PCFG-BCL is competitive with existing methods for unsupervised CFG learning.</p>
dc.identifier archive/lib.dr.iastate.edu/cs_techreports/227/
dc.identifier.articleid 1241
dc.identifier.contextkey 5463155
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath cs_techreports/227
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/20047
dc.source.bitstream archive/lib.dr.iastate.edu/cs_techreports/227/gl_ext_v1.5.pdf|||Fri Jan 14 22:44:11 UTC 2022
dc.subject.disciplines Artificial Intelligence and Robotics
dc.title Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering (Extended Version)
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
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