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    WORD SEGMENTATION AND PART-OF-SPEECH TAGGING FOR THAI LANGUAGE USING MINIMUM TEXT AND CONDITIONAL RANDOM FIELD 

    Kannikar Paripremkul; Kannikar Paripremkul; Ohm Sornil; โอม ศรนิล; National Institute of Development Administration. School of Applied Statistics; Ohm Sornil; โอม ศรนิล (National Institute of Development Administration, 13/8/2021)

    Thai word segmentation and Part-of-Speech (POS) tagging is still a very active research area. However, previous studies mostly focus on rule-based models or generative models such as the Hidden Markov Model (HMM), which may not suitable for segmenting an unknown word. In this research, we present a novel technique to deal with the problem of word segmentation for a language without explicit word boundary delimiters, like Thai, Chinese, or Korean. This research proposes a machine learning model called the Conditional Random Field (CRF) to segment ...