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广西师范大学学报(自然科学版) ›› 2010, Vol. 28 ›› Issue (3): 122-125.
赵涛涛1, 洪宇1, 华震威2, 赵明明1, 姚建民1,2
ZHAO Tao-tao1, HONG Yu1, HUA Zhen-wei2, ZHAO Ming-ming1, YAO Jian-min1,2
摘要: 由于Tri-training半监督学习方法对分类算法和样本类型要求比较宽松,并且算法运行速度较快,故采用其进行中文短语的翻译自由度的计算,实验结果表明,Tri-training半监督学习方法能够较大程度地提高短语翻译自由度计算的准确性,对翻译自由度计算有较好的学习效果。
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[1] | 陆广泉, 谢扬才, 刘星, 张师超. 一种基于KNN的半监督分类改进算法[J]. 广西师范大学学报(自然科学版), 2012, 30(1): 45-49. |
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