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首页> 外文期刊>Malaysian Journal of Computer Science >Ontological Lexicon Enrichment: The Badea System For Semi-Automated Extraction Of Antonymy Relations From Arabic Language Corpora
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Ontological Lexicon Enrichment: The Badea System For Semi-Automated Extraction Of Antonymy Relations From Arabic Language Corpora

机译：本体词典丰富：从阿拉伯语语料库中半自动提取反义关系的Badea系统

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language processing tools and applications; however, they are expensive to build, maintain, and extend. In this paper, we present the Badea system for the semi-automated extraction of lexical relations, specifically antonyms using a pattern-based approach to support the task of ontological lexicon enrichment. The approach is based on an ontology of eed?pairs of antonyms in the Arabic language; we identify patterns in which the pairs occur and then use the patterns identified to find new antonym pairs in an Arabic textual corpora. Experiments are conducted on Badea using texts from three Arabic textual corpuses: KSUCCA, KACSTAC, and CAC. The system is evaluated and the patterns?reliability and system performance is measured. The results from our experiments on the three Arabic corpora show that the pattern-based approach can be useful in the ontological enrichment task, as the evaluation of the system resulted in the ontology being updated with over 300 new antonym pairs, thereby enriching the lexicon and increasing its size by over 400%. Moreover, the results show important findings on the reliability of patterns in extracting antonyms for Arabic. The Badea system will facilitate the enrichment of ontological lexicons that can be very useful in any Arabic natural language processing system that requires semantic relation extraction.
机译：语言处理工具和应用程序;但是，它们的构建，维护和扩展成本很高。在本文中，我们介绍了Badea系统，该系统用于半自动提取词汇关系，特别是使用基于模式的方法来支持实体词库充实任务的反义词。该方法基于阿拉伯语的一对反义词本体。我们确定出现配对的模式，然后使用识别出的模式在阿拉伯语文本语料库中找到新的反义词对。使用来自三个阿拉伯语文本语料库（KSUCCA，KACSTAC和CAC）的文本在Badea上进行了实验。评估系统并测量模式，可靠性和系统性能。我们对三种阿拉伯语料库的实验结果表明，基于模式的方法可用于本体充实任务，因为对该系统的评估导致本体被300多个新的反义词对更新，从而丰富了词典和将其大小增加400％以上。此外，结果显示了在提取阿拉伯语反义词时模式可靠性方面的重要发现。 Badea系统将有助于丰富本体词典，这些本体词典在任何需要语义关系提取的阿拉伯自然语言处理系统中都非常有用。

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