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http://hdl.handle.net/10609/151505
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DC Field | Value | Language |
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dc.contributor.author | Arun Kumar, Rajappan Nair | - |
dc.contributor.author | Padró, Lluís | - |
dc.contributor.author | Oliver, Antoni | - |
dc.date.accessioned | 2024-11-11T13:53:13Z | - |
dc.date.available | 2024-11-11T13:53:13Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Kumar, A. [Mokhtar], Padró, L. [Lluís] & Oliver, A. [Antoni]. (2016). Unsupervised learning of agglutinated morphology using nested Pitman-Yor process based morpheme induction algorithm. A Y. Lu, W. Chen, M. Zhang, M. Dong & B. Ma (ed.). 2015 International Conference on Asian Language Processing (IALP) (p. 45-48). Los Alamitos, CA: IEEE Computer Society | - |
dc.identifier.uri | http://hdl.handle.net/10609/151505 | - |
dc.description.abstract | In this paper we describe a method of morphologically segment highly agglutinating and inflectional languages from the Dravidian family. We use the nested Pitman-Yor process to segment long agglutinated words into their basic components, and use a corpus based morpheme induction algorithm to perform morpheme segmentation. We test our method on two languages, Malayalam and Kannada and compare the results with Morfessor-baseline. | en |
dc.format.mimetype | application/pdf | ca |
dc.language.iso | eng | en |
dc.publisher | IEEE | - |
dc.relation.ispartof | IALP 2015: 19th International Conference on Asian Language Processing: Suzhow, China 24-25 Octubre de 2015 | ca |
dc.rights | CC BY-NC-ND | - |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | - |
dc.subject | Nested Pitman-Yor Process | en |
dc.subject | agglutinated morphology | en |
dc.subject | Indian languages | ca |
dc.title | Unsupervised learning of agglutinated morphology using Nested Pitman-Yor Process based Morpheme Induction Algorithm | ca |
dc.type | info:eu-repo/semantics/conferenceObject | ca |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.gir.id | CO/0000003972 | - |
Appears in Collections: | Conferencias |
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kumar_ieee_Unsupervised.pdf | 1,9 MB | Adobe PDF | ![]() View/Open |
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