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  • 标题:ONTOLOGY POPULATION FROM QURANIC TRANSLATION TEXTS BASED ON A COMBINATIONOF LINGUISTIC PATTERNS AND ASSOCIATION RULES
  • 本地全文:下载
  • 作者:TAHER WEAAM ; SAIDAH SAAD
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2016
  • 卷号:86
  • 期号:2
  • 出版社:Journal of Theoretical and Applied
  • 摘要:With the increasing volume of English translation of Islamic documents available on the web, there is a need to retrieve and extract important information in order to fully understanding these documents. Understanding the Quran is a grand challenge for society, for western public education, for Muslim-world education, for knowledge representation and reasoning and for knowledge extraction from text. Ontology learning from the Quran text is challenging task due to the nature of the Quran text which has scattered organization of knowledge and its unique feature. This paper illustrates an ontology learning based on a hybrid method which combines lexico-syntactic patterns and association rules for English translation of the meaning of the Quran text. First, this paper designs a new two layers of filtering method which combine linguistic and statistical methods for concept extraction. Second, this work designs a new hybrid method based on lexico-syntactic patterns and association rules method for relation extraction. The results showed that using the two layers of extraction prove to be adequate and efficient measures for automatic extraction of Quranic concepts with an overall F-measure of 85.3%. In addition, the results obtained indicate that the used methods are very suitable technique for extracting relation from with an overall F-measure of 87.3% and 88.3% respectively.
  • 关键词:Ontology Learning; Statistical Methods; Pattern Extraction; Association Rules; Quran
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