Show simple item record

dc.contributor.authorCan, Burcu
dc.contributor.authorManandhar, Suresh
dc.date.accessioned2020-09-04T13:37:50Z
dc.date.available2020-09-04T13:37:50Z
dc.date.issued2014-12-31
dc.identifier.citationCan B., Manandhar S. (2014) Methods and Algorithms for Unsupervised Learning of Morphology. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54906-9_15en
dc.identifier.isbn9783642549069en
dc.identifier.issn0302-9743en
dc.identifier.doi10.1007/978-3-642-54906-9_15en
dc.identifier.urihttp://hdl.handle.net/2436/623596
dc.descriptionThis is an accepted manuscript of a chapter published by Springer in Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8403 in 2014 available online: https://doi.org/10.1007/978-3-642-54906-9_15 The accepted version of the publication may differ from the final published version.en
dc.description.abstractThis paper is a survey of methods and algorithms for unsupervised learning of morphology. We provide a description of the methods and algorithms used for morphological segmentation from a computational linguistics point of view. We survey morphological segmentation methods covering methods based on MDL (minimum description length), MLE (maximum likelihood estimation), MAP (maximum a posteriori), parametric and non-parametric Bayesian approaches. A review of the evaluation schemes for unsupervised morphological segmentation is also provided along with a summary of evaluation results on the Morpho Challenge evaluations.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofseriesLecture Notes in Computer Science, vol 8403en
dc.relation.urlhttps://link.springer.com/chapter/10.1007/978-3-642-54906-9_15en
dc.subjectunsupervised learningen
dc.subjectprobabilistic modelsen
dc.subjectmorphological segmentationen
dc.subjectmachine learning of morphologyen
dc.titleMethods and algorithms for unsupervised learning of morphologyen
dc.typeConference contributionen
dc.identifier.eissn1611-3349
dc.date.updated2020-08-26T08:19:52Z
rioxxterms.funderUniversity of Yorken
rioxxterms.identifier.projectUOW04092020BCen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2020-09-04en
dc.source.volume8403
dc.source.beginpage177
dc.source.endpage205
dc.description.versionPublished version
refterms.dateFCD2020-09-04T13:37:20Z
refterms.versionFCDAM
refterms.dateFOA2020-09-04T13:37:51Z


Files in this item

Thumbnail
Name:
Can_Methods_and_algorithms_2014.pdf
Size:
863.4Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record

https://creativecommons.org/licenses/by-nc-nd/4.0/
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/