短语边界的识别是浅层句法分析或组块分析的基础,对真实文本的处理具有重要意义。在一个含有64426词的汉语树库的支持下,本文设计并实现了基于神经元网络的汉语短语边界自动识别模型。初步实验结果显示,该模型的界定准确率为93.24%(封闭测试)和92.56%(开放测试)。
Abstract
Prediction of Chinese phrase boundary location is the base of shallow parsing or chunk parsing. It is also very important for processing real texts. With the support of our Chinese treebank including 64426 words , this paper designs and implements a method for automatic prediction of Chinese phrase boundary location based on neural network. The preliminary results show that the precision is 93.24%(close testing) and 92.56%(open testing) respectively.
关键词
汉语短语边界自动识别 /
神经元网络 /
中文信息处理
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Key words
automatic prediction of Chinese phrase boundary location /
neural network /
Chinese information processing
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参考文献
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脚注
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基金
国家重点基础研究发展规划项目(编号:G1998030507)
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