Arabic Question Answering: Systems, Resources, Tools, and Future Trends

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• 作者：Mohamed Shaheen (1)
  Ahmed Magdy Ezzeldin (1)
  
• 关键词：QA ; Factoid questions ; QA4MRE ; Question analysis ; Passage retrieval ; Answer extraction ; Answer validation ; Test ; sets ; Evaluation ; Metrics ; Language resources ; NLP ; Information retrieval ; Stemming ; Corpus ; NER ; Stemming ; Lemmatization ; Morphological analysis ; Part ; of ; speech tagging ; Diacritization ; Overview ; Review ; Survey
• 刊名：Arabian Journal for Science and Engineering
• 出版年：2014
• 出版时间：June 2014
• 年：2014
• 卷：39
• 期：6
• 页码：4541-4564
• 全文大小：
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• 作者单位：Mohamed Shaheen (1)
  Ahmed Magdy Ezzeldin (1)
  
  1. College of Computing and Information Technology, Arab Academy for Science, Technology and Maritime Transport, Alexandria, Egypt
  

文摘

Arabic is the 6th most wide-spread natural language in the world with more than 350 million native speakers. Arabic question answering systems are gaining great importance due to the increasing amounts of Arabic content on the Internet and the increasing demand for information that regular information retrieval techniques cannot satisfy. In spite of the importance of Arabic question answering, there is no review that covers Arabic question answering systems, tools, resources, and test-sets so far, which was the motivation for this work. In this survey, different Arabic question answering systems are demonstrated and analyzed and the main question answering tasks like question analysis, passage retrieval, and answer extraction are explored. The main difficulties of modern standard Arabic and how these difficulties are tamed and classified are also explained. Arabic question answering evaluation metrics, test-sets, and language resources are reviewed, and future trends are also highlighted to guide new research in this area. This survey provides guidance for new research in Arabic question answering to get up-to-date knowledge about the state-of-the-art approaches in this area. It also demonstrates the tools created and used by researchers to build an Arabic question answering system.