ABSTRACT
Automatic summarization is the scientific art of representing the essence of a long document(s) in a document(s) that is significantly smaller than its original by employing computer programs. e field is traced back to the 1950s [113], and in recent years has enjoyed
significant progress and is still more promising in the future [77,80,109]. Automatic summarization systems employ a procedure that may be based on one or more of the following: statistical process, knowledge base, artificial intelligence, computational linguistics, and other related techniques to achieve its goal [77,80,109]. Examples of automatic summarization systems are AutoSummarize [81], SweSum [82], Inxight Summarizer [82], IBM Intelligent Miner [117], and DimSum [84,109]. Automatic summarization approaches may categorize into three types: high level, low level, and hybrid approaches [77,80,109].
