Template-Driven Automatic Myanmar Text Summarization using Conditional Random Fields

dc.contributor.author	Kyaw, Win Thuzar
dc.contributor.author	Thein, Ni Lar
dc.contributor.author	Htay, Hla Hla
dc.date.accessioned	2019-09-25T14:10:16Z
dc.date.available	2019-09-25T14:10:16Z
dc.date.issued	2012-02-28
dc.identifier.uri	http://onlineresource.ucsy.edu.mm/handle/123456789/2280
dc.description.abstract	By providing information as the summary, the reader can save time and can easily absorb the main concepts of the articles which are described in digital form. Therefore, automatic text summarization, the process of compressing the documents into the compact style by means of a computer, plays an important role. In this paper, Template-Driven Automatic Myanmar Text Summarization using Conditional Random Fields (CRFs) is introduced for Myanmar news articles in natural disaster domain collected from official Myanmar Newspaper. CRFs are undirected graphical models which can be used to segment and label natural language text. CRF model is mainly used for information extraction in this work.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Tenth International Conference On Computer Applications (ICCA 2012)	en_US
dc.subject	automatic text summarization	en_US
dc.subject	conditional random fields (CRFs)	en_US
dc.title	Template-Driven Automatic Myanmar Text Summarization using Conditional Random Fields	en_US
dc.type	Article	en_US