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Automatic Myanmar Text Summarization System

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dc.contributor.author Soe, Khin Mar
dc.contributor.author Htay, Hla Hla
dc.contributor.author Kyaw, Win Thuzar
dc.date.accessioned 2019-07-03T03:38:17Z
dc.date.available 2019-07-03T03:38:17Z
dc.date.issued 2014-02-17
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/156
dc.description.abstract Automatic text summarization is used as a tool to help people in reducing the time spent manually extracting the main ideas from text documents. If the natural disaster news is provided as the summary form including important and relevant information, people in management level can make comparisons and intelligent decisions quickly without exhausting energy by manually extracting the salient points. Moreover, for a normal user, automatic summary report of the disaster news makes them clear perception and fully awareness of the effects of the natural disaster by inspecting death toll and damage of the natural hazards. Therefore, this paper proposes Automatic Myanmar Text Summarization framework that is based on Information Extraction and practical implementation of this framework in summarizing natural disaster news which are in seven types: Earthquake, Flood, Landslide, Forest Fire, Tornado, Storm and Volcanic Eruption described in Myanmar Language. The two main components of the proposed framework, Myanmar Word Segmentation model based on Conditional Random Fields (CRFs) and Information Extraction Model using CRFs approach are also introduced. en_US
dc.language.iso en en_US
dc.publisher Twelfth International Conference On Computer Applications (ICCA 2014) en_US
dc.subject Automatic Text Summarization en_US
dc.subject Conditional Random Fields en_US
dc.title Automatic Myanmar Text Summarization System en_US
dc.type Article en_US


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