Automatic Arabic Summarization: A survey of methodologies and systems
作者： Lamees Mahmoud Al Qassem , Di Wang , Zaid Al Mahmoud , Hassan Barada , Ahmad Al-Rubaie
DOI: 10.1016/J.PROCS.2017.10.088
关键词: Field (computer science) 、 Text graph 、 Computer science 、 Multi-document summarization 、 Structure (mathematical logic) 、 Natural language processing 、 Social media 、 Automatic summarization 、 Arabic 、 Artificial intelligence
摘要: Abstract Text summarization has been a field of intensive research over the last 50 years, especially for commonly-used and relatively simple-grammar languages such as English. Moreover, unprecedented growth in amount online information available many to users businesses, including news articles social media, made it difficult time consuming identify consume sought after content. Hence, an automatic text various generate accurate relevant summaries from huge is essential nowadays. Techniques methodologies Arabic are still immature due inherent complexity language terms both structure morphology. This paper describes main challenges surveys systems literature. survey would be good basis design that combines “good” features existing dismiss “not-so-good” features.
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