Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)
ÇѱÛÁ¦¸ñ(Korean Title) |
¹®¼ ¿ä¾à ¹× ºñ±³ºÐ¼®À» À§ÇÑ ÁÖÁ¦¾î ³×Æ®¿öÅ© °¡½ÃÈ |
¿µ¹®Á¦¸ñ(English Title) |
Keyword Network Visualization for Text Summarization and Comparative Analysis |
ÀúÀÚ(Author) |
±è°æ¸²
ÀÌ´Ù¿µ
Á¶È¯±Ô
Kyeong-rim Kim
Da-yeong Lee
Hwan-Gue Cho
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¿ø¹®¼ö·Ïó(Citation) |
VOL 44 NO. 02 PP. 0139 ~ 0147 (2017. 02) |
Çѱ۳»¿ë (Korean Abstract) |
¹®ÀÚ Á¤º¸´Â ÀÎÅÍ³Ý °ø°£¿¡ Åë¿ëµÇ´Â Á¤º¸ÀÇ ´ë´Ù¼ö¸¦ Â÷ÁöÇÏ°í ÀÖ´Ù. µû¶ó¼ ´ë¿ë·®ÀÇ ¹®¼ÀÇ Àǹ̸¦ ºü¸£°Ô ƯÈ÷ ÀÚµ¿ÀûÀ¸·Î ÆľÇÇÏ´Â ÀÏÀº ºò µ¥ÀÌÅÍ ½Ã´ëÀÇ Áß¿äÇÑ ¿¬±¸ ÁÖÁ¦Áß ÇϳªÀÌ´Ù. ÀÌ ºÐ¾ßÀÇ ´ëÇ¥ÀûÀÎ ¿¬±¸ Áß Çϳª´Â ¹®¼ÀÇ Àǹ̸¦ ¿ä¾àÇØÁÖ´Â ÁÖ¿ä ÁÖÁ¦¾îÀÇ ÀÚµ¿ ÃßÃâ ¹× ºÐ¼®ÀÌ´Ù. ±×·¯³ª ´Ü¼øÈ÷ ÃßÃâµÈ °³º° ÁÖÁ¦¾îµéÀÇ ÁýÇÕ¸¸À¸·Î ¹®¼ÀÇ Àṉ̀¸Á¶¸¦ ³ªÅ¸³»±â¿¡´Â ºÎÁ·ÇÔÀÌ ÀÖ´Ù. º» ³í¹®¿¡¼´Â ÃßÃâµÈ ÁÖÁ¦¾îµéÀÇ ¿¬°ü°ü°è¸¦ ±×·¡ÇÁ·Î Ç¥ÇöÇÏ¿© ´ë»ó ¹®¼ÀÇ Àṉ̀¸Á¶¸¦ º¸´Ù ´Ù¾çÇÏ°Ô Ç¥½ÃÇÏ°í Ãß»óÈÇÒ ¼ö ÀÖ´Â ÁÖÁ¦¾î °¡½ÃÈ ¹æ¹ýÀ» °³¹ßÇÏ¿´´Ù. ¸ÕÀú °¢ ÁÖÁ¦¾îµé °£ÀÇ ¿¬°ü°ü°è¸¦ ÃßÃâÇϱâ À§ÇØ ÁÖÁ¦¾îº° Áö¹è±¸°£ ¸ðµ¨°ú ´Ü¾î°Å¸® ¸ðµ¨À» Á¦¾ÈÇÏ¿´´Ù. ÀÌ·¸°Ô ÃßÃâÇÑ ÁÖÁ¦¾î ¿¬°á¼º°ú ±×¸¦ Çü»óÈÇÑ ±×·¡ÇÁ´Â ¹®¼ÀÇ Àṉ̀¸Á¶¸¦ º¸´Ù ÇÔÃàÀûÀ¸·Î ´ã°í ÀÖÀ¸¹Ç·Î ¹®¼ÀÇ ºü¸¥ ³»¿ëÆľǰú ¿ä¾àÀÌ °¡´ÉÇϸç ÀÌ °¡½ÃÈ ±×·¡ÇÁ¸¦ ºñ±³ÇÔÀ¸·Î¼ ¹®¼ÀÇ ÀǹÌÀû À¯»çµµ ºñ±³µµ °¡´ÉÇÏ´Ù. ½ÇÇèÀ» ÅëÇÏ¿© ¹®¼ÀÇ ÀǹÌÆľǰú ºñ±³¿¡ º» ÁÖÁ¦¾î °¡½ÃÈ ±×·¡ÇÁ´Â ÀϹÝÀûÀÎ ¿ä¾à¹®À̳ª ´Ü¼ø ÁÖÁ¦¾î ¸®½ºÆ®º¸´Ù ´õ À¯¿ëÇÔÀ» º¸¿´´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the ¡°big data¡± era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors¡¯ experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.
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Å°¿öµå(Keyword) |
ÁÖÁ¦¾î ¿¬°á¸Á
ºñ±³ºÐ¼®
À¯»çµµ
°¡½ÃÈ
¿¬°á¼º ÃßÃâ
keyword network
comparative analysis
similarity
visualization
correlativity extraction
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