Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
¿Â¶óÀÎ °ÔÀÓ¿¡¼ »ç¿ëÀÚÀÇ ÀÌÅ» ¿¹Ãø ¹× ÀÌÅ» »çÀ¯ ºÐ¼® : ¼Ò¼È È°µ¿ ¼ºÇâ ¹× °ÔÀÓ Âü¿©µµ¸¦ ÁßÁ¡À¸·Î |
¿µ¹®Á¦¸ñ(English Title) |
User Behavior Analysis for Predicting Churn of Loyal Customers in Online Games based on Social Relationships and Degree of Participation |
ÀúÀÚ(Author) |
¼Àººñ
¿ìÁö¿µ
±èÈÖ°
Eunbi Seo
Jiyoung Woo
Huy Kang Kim
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¿ø¹®¼ö·Ïó(Citation) |
VOL 45 NO. 11 PP. 1124 ~ 1134 (2018. 11) |
Çѱ۳»¿ë (Korean Abstract) |
¿Â¶óÀÎ ·ÑÇ÷¹À× °ÔÀÓ(MMORPG) ³» »ç¿ëÀÚµéÀº ´Ù¾çÇÑ ¼Ò¼È È°µ¿ ¼ºÇâÀ» º¸À̸ç, ÀϺΠ»ç¿ë ÀÚÀÇ °æ¿ì È¥ÀÚ °ÔÀÓÀ» Áñ±â´Â ¼ºÇâÀ» ³ªÅ¸³»±âµµ ÇÑ´Ù. º» ³í¹®¿¡¼´Â »ç¿ëÀÚ°¡ ¼Ò¼ÓµÈ ±æµåÀÇ Æ¯¼ºÀ» ¼Ò¼È È°µ¿ ¹× ¼Ò¼Ó°¨ Á¤µµ¿¡ µû¶ó ºÐ·ùÇÏ°í, ºÐ·ùµÈ °¢ ±×·ìÀÇ ÀÌÅ»À² ¹× ÀÌÅ»¿øÀÎÀ» ºÐ¼®ÇÑ´Ù. ¶ÇÇÑ ¼Ò¼ÈÈ°µ¿ ¼ºÇâÀ¸·Î ºÐ·ùµÈ °¢ »ç¿ëÀÚ ±×·ìÀ» ´ë»óÀ¸·Î °ÔÀÓ Âü¿©µµ º¯µ¿ ÃßÀ̸¦ ÃøÁ¤ÇÏ¿© ÀÌÅ»À» ¿¹ÃøÇÏ´Â ÇÁ·¹ÀÓ¿öÅ©¸¦ Á¦¾ÈÇÑ´Ù. ºñ½ÁÇÑ ¼ºÇâÀ¸·Î ºÐ·ùµÈ °¢ ±×·ìÀÇ »ç¿ëÀÚ´Â ÀÌÅ» Á÷Àü¿¡ À¯»çÇÑ Çൿ ÆÐÅÏÀ» º¸ÀÏ ¼ö ÀÖÀ¸¹Ç·Î, À̸¦ ±âÁØÀ¸·Î ÀÌÅ» »ç¿ëÀÚ¿Í ºñÀÌÅ» »ç¿ëÀÚÀÇ ÆÐÅÏÀ» ºÐ·ùÇÒ ¼ö ÀÖ´Ù. ¿£¾¾¼ÒÇÁÆ®ÀÇ ´ëÇ¥ MMORPGÀÎ ¾ÆÀÌ¿Â µ¥ÀÌÅ͸¦ ´ë»óÀ¸·Î º» ¸ðµ¨À» Å×½ºÆ®ÇÏ¿´À¸¸ç, Æò±Õ ¾à 75%ÀÇ Á¤¹Ðµµ¸¦ º¸¿©ÁÖ¾ú´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Game users in MMORPGs engage in a variety of social activities. However, a few users tend to play games alone, and are designated ¡®loners¡¯ similar to modern society. We classified game guilds and game users based on similar user behaviors and community characteristics. We propose a model that predicts churn users by measuring the participation of users in each group. Users in each group show similar behavioral patterns, suggesting that we can classify churn users along with ordinary users. We tested this model for NCsoft¡¯s MMORPG, Aion. Using Randomforest, the recall was measured at an average of 75%.
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Å°¿öµå(Keyword) |
À¯Àú ÇàÀ§ ºÐ¼®
ÀÌÅ» »ç¿ëÀÚ ¿¹Ãø
¿Â¶óÀÎ ·ÑÇ÷¹À× °ÔÀÓ
µ¥ÀÌÅ͸¶ÀÌ´×
user behavior analysis
churn user prediction
MMORPG
data mining
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