Mongolian Word Segmentation Based on Statistical Language Model
HOU Hong-Xu1,2,3, LIU Qun1, Nasanurtu2, Murengaowa2, LI Jin-Tao1
1.Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190 2.School of Computer Science, Inner Mongolia University, Huhhot 010021 3.Graduate University of Chinese Academy of Sciences, Beijing 100190
Abstract：Based on the analysis of Mongolian segmentation technique and the rules used as the foundation of word segmentation, a hybrid word segmentation method is proposed. It uses Mongolian statistical language model to eliminate the ambiguity in Mongolian word segmentation. A POS language model and a Skip-N language model are used, and an experiment system is thus created. The experimental results are better than those of the system based on rules.
侯宏旭，刘群，那顺乌日图，牧仁高娃，李锦涛. 基于统计语言模型的蒙古文词切分*[J]. 模式识别与人工智能, 2009, 22(1): 108-112.
HOU Hong-Xu, LIU Qun, Nasanurtu, Murengaowa, LI Jin-Tao. Mongolian Word Segmentation Based on Statistical Language Model. , 2009, 22(1): 108-112.
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2009, Vol. 22 
