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AUTOMATIC RECOGNITION OF CHINESE SCIENTIFIC AND TECHNOLOGICAL TERMS USING INTEGRATED LINGUSITIC KNOWLEDGE

机译:用综合语言知识自动识别中国科技术语

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摘要

The paper introduces 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:本文介绍了我们对使用综合语言知识来自动认识中国科技术语的研究,以仔细分析这种术语的特征。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来获取各种综合知识,用于从大规模语料库和术语银行自动术语识别。这些知识包括内部结构知识,术语组件的统计域特征,术语组件之间的统计互联信息,术语的外部环境特征和术语识别的不同文本级别特征。在舞台中应用,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,该系统可以对学期标准化的专家提供很大帮助,以发现新的条款。

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