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An automatic noun compound extraction from Arabic corpus

机译:阿拉伯语中的自动名词化合物提取

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The identification of noun compound as multi-word lexical units is very important task in natural language processing applications that require some degree of semantic interpretation such as, machine translation, information retrieval and text summarization. In this paper, we used the hybrid method for extracting the noun compound from Arabic corpus that is based on linguistic knowledge and statistical measures. For the candidate identification, we have used some linguistic analysis tools such as lemmatization and POS in order to filter the candidates and determine the variations. The association measures have been computed for each candidate to rank the candidates. After that, we have evaluated the association measures by using the n-best evaluation method. We reported the precision values for each association measure in each n-best list. The experimental results showed that the log-likelihood ratio is the best association measure that achieved highest precision.
机译:作为多字词汇单位的名词化合物的识别是在自然语言处理应用中的特点是需要一定程度的语义解释,例如机器翻译,信息检索和文本摘要。在本文中,我们使用了用于从语言知识和统计措施中从阿拉伯语料库中提取名词化合物的混合方法。对于候选识别,我们使用了一些语言分析工具,例如lemmatization和POS,以便过滤候选物并确定变化。每个候选人都已经计算了协会措施,以对候选人进行排名。之后,我们使用N最佳评估方法评估了关联措施。我们报告了每个N最佳列表中每个关联度量的精度值。实验结果表明,对数似然比是实现最高精度的最佳关联度量。

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