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A Syntactico-Semantic Method for Arabic Collocations Extraction

机译:阿拉伯词语搭配提取的句法语义方法

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This work focuses on the extraction of collocations from Arabic textual corpora. The method that we propose is hybrid. It uses syntactico-semantic information by combining an enriched linguistic filtering with a statistical filtering. Linguistic filtering applies syntactic patterns represented by finite state automata and considers both elementary collocations and augmented ones. Statistical filtering is novel since it does not use classical association measures and applies the Latent Semantic Analysis (LSA) method to infer deeper semantic relations than those derived by contiguity frequencies, co-occurrence counts, or correlations in usage. The experiments showed that LSA gives globally better results than those achieved by Mutual Information (MI), Likelihood ration (LLR), Khi-Carré (X2), z score and t-test.
机译:这项工作的重点是从阿拉伯语文本语料库中提取搭配。我们提出的方法是混合的。它通过将丰富的语言过滤与统计过滤相结合来使用语法语义信息。语言过滤应用由有限状态自动机表示的句法模式,并同时考虑基本搭配和扩充搭配。统计过滤是新颖的,因为它不使用经典的关联度量,并且应用了潜在语义分析(LSA)方法来推断比通过连续性频率,共现计数或使用中的相关性得出的语义关系更深的语义关系。实验表明,与互助信息(MI),似然比(LLR),Khi-Carré(X2),z得分和t检验相比,LSA在全球范围内提供了更好的结果。

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