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Automatic Extraction of Multiword Expressions Combining Statistical and Similarity Approaches

机译:统计和相似性方法的自动提取多个表达式

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Multiword expressions (MWEs) are important for practical applications, such as machine translation (henceforth, MT), multilingual information retrieval, data mining and other natural language processing. A method of combining similarity measure and statistical tool is proposed for automatically extracting English MWEs from the corpus of Chinese government white papers and work reports from 1991 to 2010. Statistical approach is employed to calculate the co-occurrence affinity between two words. Besides, similarity measure is harnessed to compute the semantic relations between words for improving MWE coverage, thus aiming at obtaining higher precision and recall in extracting candidate multiword expressions. Experimental results showed the proposed technique improved MWE extraction efficiently.
机译:多字级表达式(MWES)对于实际应用是重要的,例如机器翻译(从您国家,MT),多语言信息检索,数据挖掘和其他自然语言处理。提出了一种结合相似度量和统计工具的方法,以自动从1991年至2010年从中国政府白文和工作报告中自动提取英语MWE。统计方法是为了计算两个词之间的共同发生亲和力。此外,利用相似度测量来计算用于改善MWE覆盖的单词之间的语义关系,从而旨在在提取候选多字级表达式中获得更高的精度和召回。实验结果表明,所提出的技术有效改善MWE提取。

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