以《茶经》的翻译为例,基于树剪枝理论提出了一种典籍文本快速切分方法。首先,采用似然比统计量计算两字、三字甚至多字候选单元;然后在此基础上基于树剪枝的思想构建了典籍文本快速切分的模型算法,并构建了基本流程图;最后,以《茶经》为例验证了本算法的有效性和合理性。理论分析和算例表明,该算法能有效地对典籍文本进行自动切分,并简化了计算时间的复杂度,在推广中国典籍的对外传译方面具有良好的应用前景。

This study proposes a new fast segmentation method for classic Chinese texts based on the tree pruning process. Firstly, word candidates of two, three and multiple characters are selected with likelihood ratio statistics. Then an algorithm of fast segment is presented and a basic flow chart is illustrated. Finally, the Classic of Tea is used to verify its validity and effectiveness. The theoretical analysis and experimental instances show that the algorithm is effective and promising in computer-aided translation of classic Chinese texts.
Key wordssegmentation; tree pruning; likelihood ratio; The Classic of Tea; computer-aided translation