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    Keyphrase Generation Based on Self-Attention Mechanism

    Kehua Yang1,*, Yaodong Wang1, Wei Zhang1, Jiqing Yao2, Yuquan Le1

    CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 569-581, 2019, DOI:10.32604/cmc.2019.05952

    Abstract Keyphrase greatly provides summarized and valuable information. This information can help us not only understand text semantics, but also organize and retrieve text content effectively. The task of automatically generating it has received considerable attention in recent decades. From the previous studies, we can see many workable solutions for obtaining keyphrases. One method is to divide the content to be summarized into multiple blocks of text, then we rank and select the most important content. The disadvantage of this method is that it cannot identify keyphrase that does not include in the text, let alone… More >

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