DC Field | Value | Language |
---|---|---|
dc.contributor.author | Han, YS | ko |
dc.contributor.author | Choi, Key-Sun | ko |
dc.date.accessioned | 2013-03-03T07:50:16Z | - |
dc.date.available | 2013-03-03T07:50:16Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 1996-09 | - |
dc.identifier.citation | COMPUTATIONAL LINGUISTICS, v.22, no.3, pp.421 - 429 | - |
dc.identifier.issn | 0891-2017 | - |
dc.identifier.uri | http://hdl.handle.net/10203/77850 | - |
dc.description.abstract | A Probabilistic Recursive Transition Network is an elevated version of a Recursive Transition Network used to model and process context-free languages in stochastic parameters. We present a re-estimation algorithm for training probabilistic parameters, and show how efficiently it can be implemented using charts. The complexity of the Outside algorithm we present is O(N(4)G(3)) where N is the input size and G is the number of states. This complexity cart be significantly overcome when the redundant computations are avoided. Experiments on the Penn tree corpus show that re-estimation can be done more efficiently with charts. | - |
dc.language | English | - |
dc.publisher | MIT PRESS | - |
dc.title | A chart re-estimation algorithm for a probabilistic recursive transition network | - |
dc.type | Article | - |
dc.identifier.wosid | A1996VT54000007 | - |
dc.identifier.scopusid | 2-s2.0-1542635064 | - |
dc.type.rims | ART | - |
dc.citation.volume | 22 | - |
dc.citation.issue | 3 | - |
dc.citation.beginningpage | 421 | - |
dc.citation.endingpage | 429 | - |
dc.citation.publicationname | COMPUTATIONAL LINGUISTICS | - |
dc.contributor.localauthor | Choi, Key-Sun | - |
dc.contributor.nonIdAuthor | Han, YS | - |
dc.type.journalArticle | Article | - |
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