CRF-based Named Entity Recognition for Myanmar Language

Mo, Hsu Myat; Nwet, Khin Thandar; Soe, Khin Mar

dc.contributor.author	Mo, Hsu Myat
dc.contributor.author	Nwet, Khin Thandar
dc.contributor.author	Soe, Khin Mar
dc.date.accessioned	2019-07-11T04:34:32Z
dc.date.available	2019-07-11T04:34:32Z
dc.date.issued	2016-10-21
dc.identifier.isbn	978-3-319-48489-1
dc.identifier.uri	http://onlineresource.ucsy.edu.mm/handle/123456789/727
dc.description	This work is partly supported by the ASEAN IVO Project “Open Collaboration for Developing and Using Asian Language Treebank”.	en_US
dc.description.abstract	Named Entity recognition (NER) is a subtask of information extraction and information retrieval that automatically identify proper nouns in texts and classify into predefined categories of name types. This paper introduces the effort on identification and classification of Named Entities in written Myanmar scripts in a statistical way. A statistical approach for NER of Myanmar Language using one of the supervised machine learning approaches called Conditional Random Fields (CRF) has been proposed for this task.	en_US
dc.language.iso	en	en_US
dc.publisher	The Tenth International Conference on Genetic and Evolutionary Computing (ICGEC 2016)	en_US
dc.relation.ispartofseries	Advances in Intelligent Systems and Computing;Vol. 536
dc.subject	Named Entity Recognition	en_US
dc.subject	Myanmar Language	en_US
dc.subject	CRF	en_US
dc.title	CRF-based Named Entity Recognition for Myanmar Language	en_US
dc.type	Article	en_US