• Àüü
  • ÀüÀÚ/Àü±â
  • Åë½Å
  • ÄÄÇ»ÅÍ
´Ý±â

»çÀÌÆ®¸Ê

Loading..

Please wait....

±¹³» ³í¹®Áö

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) ¼Ò¼È »ç¹° ÀÎÅͳݿ¡¼­ »óÈ£ ÀÛ¿ë ºÐ¼®À» ÅëÇÑ À¯»ç »ç¿ëÀÚ Ãßõ
¿µ¹®Á¦¸ñ(English Title) Recommending Similar Users Through Interaction Analysis in Social IoT Environments
ÀúÀÚ(Author) ±è¿¬µ¿   ÃÖµµÁø   ÀÓÁ¾Å   º¹°æ¼ö   À¯Àç¼ö   Yeondong Kim   Dojin Choi   Jongtae Lim   Kyoungsoo Bok   Jaesoo Yoo  
¿ø¹®¼ö·Ïó(Citation) VOL 47 NO. 01 PP. 0061 ~ 0069 (2020. 01)
Çѱ۳»¿ë
(Korean Abstract)
ÃÖ±Ù ¼Ò¼È ³×Æ®¿öÅ©¿Í »ç¹° ÀÎÅͳÝÀ» °áÇÕÇÑ ¼Ò¼È »ç¹° ÀÎÅͳݿ¡ ´ëÇÑ ¿¬±¸°¡ ¸¹ÀÌ ÁøÇàµÇ°í ÀÖ´Ù. ¼Ò¼È »ç¹° ÀÎÅͳÝÀº »ç¹° ¶Ç´Â »ç¿ëÀÚ°£ Á¤º¸ °øÀ¯¸¦ À§ÇØ »ç¿ëÀÚ¿Í »ç¿ëÀÚ °£¿¡ ¿¬°á °ü°è »Ó¸¸ ¾Æ´Ï¶ó »ç¿ëÀÚ¿Í °´Ã¼ °£¿¡ °ü°è ¼³Á¤ÀÌ Áß¿äÇÏ´Ù. º» ³í¹®¿¡¼­´Â ¼Ò¼È »ç¹° ÀÎÅͳݿ¡¼­ °´Ã¼¿Í »ç¿ëÀÚ °£¿¡ »óÈ£ ÀÛ¿ëÀ» °í·ÁÇÑ À¯»ç »ç¿ëÀÚ¸¦ ÃßõÇÏ´Â ±â¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ±â¹ýÀº °´Ã¼¸¦ Áß½ÉÀ¸·Î »ç¿ëÀÚÀÇ ÇàÀ§¸¦ ºÐ¼®ÇÔÀ¸·Î½á »ç¿ëÀÚ¿Í À¯»çÇÑ »ç¿ëÀÚ¸¦ ãÀ» ¼ö ÀÖ´Ù. Á¦¾ÈÇÏ´Â ±â¹ýÀº ¼Ò¼È ³×Æ®¿öÅ©¿¡¼­ »ç¿ëÀÚµéÀÌ ÀÛ¼ºÇÑ ¹®¼­µéÀ» ±â¹ÝÀ¸·Î °ü½Éµµ¸¦ ÆǺ°ÇØ À¯»çµµ¸¦ °è»êÇÔÀ¸·Î½á À¯»çµµÀÇ Á¤È®µµ¸¦ Çâ»ó½Ãų ¼ö ÀÖ´Ù. ÃÖÁ¾ÀûÀ¸·Î µÎ À¯»çµµ °ªÀ» °í·ÁÇÏ¿© »ç¿ëÀÚ Top-N¸íÀ» À¯»ç »ç¿ëÀÚ·Î ÃßõÇÑ´Ù. Á¦¾ÈÇÏ´Â ±â¹ýÀÇ ¿ì¼ö¼ºÀ» º¸À̱â À§ÇØ ´Ù¾çÇÑ ¼º´ÉÆò°¡¸¦ ¼öÇàÇÑ´Ù.
¿µ¹®³»¿ë
(English Abstract)
Recently, there has been extensive research on the social internet of things(Social IoT) that combines social networks and internet of things. Social IoT is integral for the connection between as well as for establishing relationships between users and objects for sharing information between objects or users. In this paper, we propose a method that recommends similar users by considering interaction between objects and users in the social IoT environments. The similar users can be found by analyzing the behavior of the users around the object. The proposed method improves the accuracy of similarity by calculating similarity in determining interests based on documents written by users in social networks. Finally, it recommends Top-N users as similar users based on the two similarity values. To show the superiority of the proposed method, we conducted various performance evaluations.
Å°¿öµå(Keyword) »ç¹° ÀÎÅͳݠ  ¼Ò¼È ³×Æ®¿öÅ©   »óÈ£ ÀÛ¿ë   »ç¿ëÀÚÀÇ °ü½Éµµ   ÄÚ»çÀÎ À¯»çµµ   social internet of things   interaction   user¡¯s interest   recommend   cosine similarity  
ÆÄÀÏ÷ºÎ PDF ´Ù¿î·Îµå