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Journal Publication
Research Title A hybrid approach to Lao word segmentation using longest syllable level matching with named entities recognition 
Date of Distribution 17 May 2013 
     Title of the Conference Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013 10th International Conference on 
     Organiser ECTI 
     Conference Place Maritime Park & Spa Resort 
     Province/State Krabi, Thailand 
     Conference Date 15 May 2013 
     To 17 May 2013 
Proceeding Paper
     Volume 2013 
     Issue 978-1-4799-0546-1 
     Page 1 - 5 
     Abstract The Lao language is written without words delimiter which makes it extremely difficult to process. The development of automatic word segmentation for natural language processing for the Lao language is an essential but challenging task. This paper proposes a longest syllable level match with named entities recognition approach for Lao word segmentation. Syllables were first extracted from the input text and then longest matching was applied. This is one of the techniques in the Dictionary Based approach with named entities recognition being used to combine them to form the words. The performance result obtained from this approach, in precision and recall, was 85.21% and 92.36%, respectively. 
555020271-2 Mr. AROUNYADETH SRITHIRATH [Main Author]
Science Master's Degree

Peer Review Status มีผู้ประเมินอิสระ 
Level of Conference นานาชาติ 
Type of Proceeding Abstract 
Type of Presentation Oral 
Part of thesis true 
Presentation awarding false 
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