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Using features extracted from Wikipedia for the task of Word Sense Disambiguation

机译:使用从Wikipedia中提取的功能执行Word Sense歧义消除任务

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In this paper, a method using features extracted from Wikipedia for the task of Word Sense Disambiguation (WSD) is presented and evaluated. A term-concepts table constructed from Wikipedia and the redirect links is described. With its help, the Wikipedia internal links along with the categories structure are used to compute the relatedness between any two concepts through a two-level process: a term-concepts expansion followed by a links-based expansion. The result is a ranked list of concepts which are most related to the ambiguous term given the context it exists in. For the evaluation experiment, the benchmark is constructed from a segment of the internal links of Wikipedia. The evaluation results obtained suggest that introducing links analysis and the categories structure to the built term-concepts table provide improvement to the accuracy of the method in the WSD task.
机译:在本文中,提出和评估了使用从维基百科提取的特征的方法,并评估任务。描述由维基百科和重定向链路构成的术语概念表。凭借其帮助,维基百科内部链接以及类别结构用于通过两级进程计算任意两个概念之间的相关性:术语概念扩展,后跟基于链接的扩展。结果是概念的排名概念列表,与其存在的上下文相比,与模糊术语相关。对于评估实验,基准是由维基百科的内部环节的一段构建的。获得的评估结果表明,引入链接分析和类别结构对构建的术语概念表提供了改进WSD任务中方法的准确性。

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