Unsupervised Dependency Parsing for Myanmar Language using Part-of-Speech Information

dc.contributor.author	Aye, Hnin Thu Zar
dc.contributor.author	Pa, Win Pa
dc.contributor.author	Thu, Ye Kyaw
dc.date.accessioned	2019-07-03T08:25:06Z
dc.date.available	2019-07-03T08:25:06Z
dc.date.issued	2018-02-22
dc.identifier.uri	http://onlineresource.ucsy.edu.mm/handle/123456789/341
dc.description.abstract	In this paper, we present the preliminary experiments of unsupervised dependency parsing on raw segmented and part-of-speech (POS) tagged corpus of Myanmar language. This experiment is aimed to support building treebank and get ann-otated corpus with dependency structures of My-anmar words. The referenced word dependency schemes are also explained. We present the expr-imental results on trees of unsupervised parsed annotated corpus in terms of unlabeled and labe-led attachment scores (UAS and LAS) by UDPi-pe 89.79 % and 85.56% for test and 98.25% and 97.89% for trained data respectively.	en_US
dc.language.iso	en	en_US
dc.publisher	Sixteenth International Conferences on Computer Applications(ICCA 2018)	en_US
dc.title	Unsupervised Dependency Parsing for Myanmar Language using Part-of-Speech Information	en_US
dc.type	Article	en_US