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Joint Word Segmentation and Stemming for Myanmar Language Based on Conditional Random Fields
http://hdl.handle.net/20.500.12678/0000004668
http://hdl.handle.net/20.500.12678/00000046681a563b16-f74a-4573-b287-735983c45191
5322d4d5-fced-4f64-98fe-3346a3fb97e4
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173-178.pdf (406 Kb)
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Title | ||||||
Title | Joint Word Segmentation and Stemming for Myanmar Language Based on Conditional Random Fields | |||||
Language | en | |||||
Publication date | 2018-02-22 | |||||
Authors | ||||||
Oo, Yadanar | ||||||
Soe, Khin Mar | ||||||
Description | ||||||
In this paper, we describe a joint work on wordsegmentation and stemming of Myanmar sentenceswith syllabled-based tagging under ConditionalRandom Fields(CRF) framework. A manuallysegmentedcorpus was developed to train thesegmenter, and we implement it as a 7-tag syllablebasedtagging and stemming with conditional randomfields(CRF). And then, the trained CRF segmenter wascompared to a baseline approached based on longestmatching that used a dictionary extracted frommanually segmented corpus. In our approach, we canachieve comparative performances compared to 4-tagsyllable tagging approach. The experimental resultsshow that the CRF with 7-tag set and word featureimprove the stemming performance. | ||||||
Keywords | ||||||
segmentation, stemming, syllable tagging, conditional random fields | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/325 | |||||
Journal articles | ||||||
Sixteenth International Conferences on Computer Applications(ICCA 2018) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |