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Automatic Extractive Summarization of Newspaper Articles using Activation Degree of 5W1H  

윤재민 ((주) 얄리)
정유진 (포항공과대학교 컴퓨터공학)
이종혁 (포항공과대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.4, 2004 , pp. 505-515 More about this Journal
Abstract
In a newspaper, 5W1H information is the most fundamental and important element for writing and understanding articles. Focusing on such a relation between a newspaper article and the 5W1H, we propose a summarization method based on the activation degree of 5W1H. To overcome problems of the lead-based and the title-based methods, both of which are known to be the most effective in newspaper summarization, sufficient 5W1H information is extracted from both a title and a lead sentence. Moreover, for each sentence, its weight is computed by considering various factors, such as activation degree of 5W1H, the number of 5W1H categories, and its length and position. These factors make a great contribution to the selection of more important sentences, and thus to the improvement of readability of the summarized texts. In an experimental evaluation, the proposed method achieved a precision of 74.7% outperforming the lead-based method. In sum, our 5W1H approach was shown to be promising for automatic summarization of newspaper articles.
Keywords
newspaper articles; summarization; 5W1H; activation degree;
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Times Cited By KSCI : 2  (Citation Analysis)
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