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Automatic recognition of Chinese scientific and technological terms using integrated linguistic knowledge

机译:使用综合语言知识自动识别中国科学技术术语

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We introduce our research on using integrated linguistic knowledge to automatically recognize Chinese scientific and technological terms based on the careful analysis of the characteristics of this kind of terms. The system of automatic term recognition includes two phases: learning stage and application stage. In the stage of learning, we use a series of machine learning methods to get various kinds of integrated knowledge for automatic term recognition from a large-scale corpus and a term bank. These knowledge includes the inner structural knowledge of terms, the statistical domain features of term component, the statistical mutual information between the components of terms, the outer environment features of terms and the distinct text-level features of term recognition etc.. In the stage of application, through an efficient model, we use all these various types of knowledge into automatic term recognition. The experiments show that the system can give great help to the expert of term standardization to discover new terms.
机译:在对此类术语的特征进行仔细分析的基础上,我们将介绍使用综合语言知识自动识别中国科学技术术语的研究。自动术语识别系统包括两个阶段:学习阶段和应用阶段。在学习阶段,我们使用一系列机器学习方法从大型语料库和术语库中获取用于自动术语识别的各种集成知识。这些知识包括术语的内部结构知识,术语组成部分的统计域特征,术语组成部分之间的统计互信息,术语的外部环境特征以及术语识别的独特文本级特征等。应用程序,通过有效的模型,我们将所有这些各种类型的知识用于自动术语识别。实验表明,该系统可以为术语标准化专家发现新术语提供很大帮助。

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