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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ³×Æ®¿öÅ©ÀÇ Áßø Ŭ·¯½ºÅ͸µ ±¸Á¶¸¦ °í·ÁÇÑ Á¤º¸ È®»ê ¸ðµ¨
¿µ¹®Á¦¸ñ(English Title) Cascading Behavior and Information Diffusion in Overlapping Clusters
ÀúÀÚ(Author) ÀÌ¿ìÁß   ȲÁö¿µ   Woojung Lee   Joyce Jiyoung Whang  
¿ø¹®¼ö·Ïó(Citation) VOL 47 NO. 04 PP. 0422 ~ 0432 (2020. 04)
Çѱ۳»¿ë
(Korean Abstract)
Á¤º¸ ÀüÆÄ(information diffusion) ¿¬±¸¶õ ³×Æ®¿öÅ©¿¡¼­ ƯÁ¤ ³ëµå(initial adopters)°¡ »õ·Î¿î Á¤º¸¸¦ ½ÀµæÇÒ °ÍÀ¸·Î °¡Á¤ÇÏ°í, ±×·ÎºÎÅÍ ´Ù¸¥ ³ëµå·Î ÆÛÁö´Â Á¤º¸ÀÇ ÀüÆÄ ¾ç»ó(cascading behavior)¿¡ ´ëÇÑ ¸ÞÄ¿´ÏÁòÀ» ¸ðµ¨¸µÇÏ´Â °ÍÀÌ´Ù. ´ëºÎºÐÀÇ ±âÁ¸ Á¤º¸ ÀüÆÄ ¿¬±¸µéÀº ³ëµå°¡ ÇϳªÀÇ Å¬·¯½ºÅÍ(cluster) ¿¡¸¸ ¼ÓÇÑ´Ù°í °¡Á¤Çϸç, ÀÌ °¡Á¤¿¡ ÀÇÇØ Å¬·¯½ºÅÍ°¡ Á¤º¸ ÀüÆĸ¦ ¹æÇØÇÔÀ» º¸¿© ¿Ô´Ù. ÇÏÁö¸¸, ½ÇÁ¦ ³×Æ®¿öÅ©¿¡´Â ³ëµå°¡ ¿©·¯ Ŭ·¯½ºÅÍ¿¡ ¼ÓÇÒ ¼ö ÀÖ´Ù. Áï, Ŭ·¯½ºÅÍ´Â ÁßøµÉ ¼ö ÀÖ´Ù. º» ¿¬±¸´Â ³×Æ®¿öÅ©¿¡ Áßø Ŭ·¯½ºÅÍ(overlapping cluster)°¡ Á¸ÀçÇÒ ¶§ÀÇ Á¤º¸ ÀüÆÄ ¾ç»ó¿¡ ´ëÇØ ¼Ò°³ÇÑ´Ù. »õ·Î¿î Á¤º¸¸¦ ½ÀµæÇÑ ³ëµå°¡ ³×Æ®¿öÅ©ÀÇ Áßø Ŭ·¯½ºÅÍ¿¡ ¼ÓÇϰųª ³×Æ®¿öÅ©ÀÇ °¢ ³ëµå¿¡ ´ëÇØ Á¤º¸ °øÁ¸¼º(compatibility)À» Çã¿ëÇÏ¿´À» ¶§ Ŭ·¯½ºÅÍ´Â Á¤º¸ ÀüÆÄÀÇ ¹æÇØ¿ä¼Ò°¡ ¾Æ´ÔÀ» º¸ÀδÙ. ³× °³ÀÇ ½ÇÁ¦ ³×Æ®¿öÅ© µ¥ÀÌÅÍ ¼Â(dataset)¿¡¼­ º» ¿¬±¸¿¡¼­ Á¦½ÃÇÑ ¸ðµ¨°ú ÀÌ·ÐÀ» °ËÁõÇÑ´Ù.
¿µ¹®³»¿ë
(English Abstract)
Information diffusion models formulate and explain cascading behavior in networks where a small set of initial adopters is assumed to acquire new information and the new information is propagated to the other nodes in the network. Most existing information diffusion models assume that a node in a network belongs to only one cluster, and based on this assumption, it has been shown that clusters are obstacles to cascades. However, in many real-world networks, a node can belong to multiple clusters, i.e., clusters can overlap. In this paper, we study cascading behavior in a network when clusters overlap. We show that clusters are not obstacles to cascades if the initial adopters are placed in the overlapped region between the clusters or if we allow compatibility. We verify our theorems and models on four real-world datasets.
Å°¿öµå(Keyword) Á¤º¸ ÀüÆÄ ¾ç»ó   Á¤º¸ ÀüÆÄ   Áßø Ŭ·¯½ºÅ͸µ   °øÁ¸¼º   ±×·¡ÇÁ ¸¶ÀÌ´×   cascading behavior   information diffusion   overlapping clustering   compatibility   graph mining  
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