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《Journal of Agricultural University of Hebei》 2009-04
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An improved ambiguity resolution of RMM based on long-term priotity

TIAN Zhan-xiao,HAN Xian-zhong,WANG Ke-jian (College of Information Science and Technology,Agricultural University of Hebei,Baoding 071001,China)  
In order to enhance the accuracy of chinese word segmentation,using term frequency value and single character function,the present study has made great progress on the ambiguity resolution.The experiment shows this method is able to follow the long-word-first principle,and can further detect and resolve ambiguity.The improved RMM not only has a greater advantage in speed,but also increases the accuracy.It has practical value in the aspect of ambiguity resolution to the middle and small-scale search engines which adopt mechanical method.
【Fund】: 河北省科学技术研究与发展计划项目(07213512)
【CateGory Index】: TP391.1
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