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ÇѱÛÁ¦¸ñ(Korean Title) |
À°ÇÏ¿øÄ¢ È°¼ºÈµµ¸¦ ÀÌ¿ëÇÑ ½Å¹®±â»ç ÀÚµ¿ÃßÃâ¿ä¾à |
¿µ¹®Á¦¸ñ(English Title) |
Automatic Extractive Summarization of Newspaper Articles using Activation Degree of 5W1H |
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¿ø¹®¼ö·Ïó(Citation) |
VOL 31 NO. 04 PP. 0505 ~ 0515 (2004. 04) |
Çѱ۳»¿ë (Korean Abstract) |
À°ÇÏ¿øÄ¢Àº ½Å¹®±â»ç¸¦ ±â¼úÇϴµ¥ ÀÖ¾î¼ °¡Àå ±âº»ÀûÀÎ ¿ä¼Ò·Î¼ ±â»ç ³»¿ë Æľǿ¡ ÇÙ½ÉÀûÀÎ ¿ªÇÒÀ» ¼öÇàÇÑ´Ù. º» ³í¹®Àº ÀÌ·¯ÇÑ À°ÇÏ¿øÄ¢¿¡ ±â¹ÝÇÏ¿© ±â¼úµÇ´Â ½Å¹®±â»çÀÇ Æ¯¼º¿¡ ÁÖ¸ñÇÏ¿©, À°ÇÏ¿øÄ¢ È°¼ºÈµµ¸¦ ÀÌ¿ëÇÑ ½Å¹®±â»ç ¿ä¾à ¹æ¹ý·ÐÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ¹æ¹ý·ÐÀº ±âÁ¸ÀÇ ¿ä¾à ±â¹ý Áß °¡Àå ¿ì¼öÇÑ ¹æ¹ýÀ¸·Î ¾Ë·ÁÁø µÎ¹® ±â¹Ý ±â¹ý(lead-based method)°ú Á¦¸ñ ±â¹Ý ±â¹ý(title-based method)ÀÇ ¹®Á¦Á¡À» ±Øº¹Çϱâ À§ÇØ, Á¦¸ñ°ú µÎ¹®ÀÇ Á¤º¸¸¦ °áÇÕ½ÃÄÑ ÃæºÐÇÑ ¾îÈÖÁ¤º¸¸¦ È®º¸Çϵµ·Ï ÇÏ¿´´Ù. ƯÈ÷ À°ÇÏ¿øÄ¢ È°¼ºÈµµ, À°ÇÏ¿øÄ¢ ¹üÁÖ °³¼ö, ¹®Àå ±æÀÌ, ¹®ÀåÀÇ À§Ä¡ µî°ú °°Àº ´Ù¾çÇÑ ¿ä¼ÒµéÀ» ¹®Àå Áß¿äµµ °è»ê¿¡ ¹Ý¿µÇÔÀ¸·Î½á º¸´Ù Áß¿äÇÑ Á¤º¸¸¦ Æ÷ÇÔÇϸ鼵µ °¡µ¶¼ºÀÌ ³ôÀº ¹®ÀåµéÀÌ ¿ä¾à¹®À¸·Î ¼±ÅÃµÉ ¼ö ÀÖµµ·Ï °í·ÁÇÏ¿´´Ù. Á¦¾ÈµÈ ¹æ¹ý·ÐÀÇ Á¤È®·üÀº 74.7%·Î¼ ±âÁ¸ÀÇ µÎ¹® ±â¹Ý ±â¹ýº¸´Ù ¿ì¼öÇÑ ¼º´ÉÀ» º¸¿´À¸¸ç, ½Å¹®±â»ç¸¦ ÀÚµ¿ ¿ä¾àÇϴµ¥ ÀÖ¾î¼ ÃæºÐÈ÷ È¿°úÀûÀ¸·Î »ç¿ëµÉ ¼ö ÀÖ´Â ¹æ¹ý·ÐÀÓÀ» ½ÇÇèÀ» ÅëÇØ ÀÔÁõÇÏ¿´´Ù.
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¿µ¹®³»¿ë (English 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.
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