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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ ³í¹®Áö

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Current Result Document : 67 / 272 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) ´ë±Ô¸ð ¿öÅ©ÇÃ·Î¿ì ¼Ò¼Ó¼º ³×Æ®¿öÅ©¸¦ À§ÇÑ ±ÙÁ¢ Á߽ɵµ ·©Å· ¾Ë°í¸®Áò
¿µ¹®Á¦¸ñ(English Title) An Estimated Closeness Centrality Ranking Algorithm for Large-Scale Workflow Affiliation Networks
ÀúÀÚ(Author) À̵µ°æ   ¾ÈÇö   ±è±¤ÈÆ   Do-kyong Lee   Hyun Ahn   Kwang-hoon Pio Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 17 NO. 01 PP. 0047 ~ 0053 (2016. 02)
Çѱ۳»¿ë
(Korean Abstract)
¿öÅ©ÇÃ·Î¿ì ¼Ò¼Ó¼º ³×Æ®¿öÅ©´Â ¿öÅ©ÇÃ·Î¿ì ±â¹Ý Á¶Á÷ÀÇ ¼öÇàÀÚ¿Í ¾÷¹« »çÀÌÀÇ ¿¬°ü°ü°è¸¦ ³ªÅ¸³»´Â ¼Ò¼È ³×Æ®¿öÅ©ÀÇ ÇÑ ÇüÅÂÀ̸ç, À̸¦ ±â¹ÝÀ¸·Î ¿¬°á Á߽ɵµ, ±ÙÁ¢ Á߽ɵµ, »çÀÌ Á߽ɵµ, À§¼¼ Á߽ɵµ µî°ú °°Àº ´Ù¾çÇÑ ºÐ¼® ±â¹ýµéÀÌ Á¦¾ÈµÇ¾ú´Ù. ƯÈ÷, Àü»çÀû ¿öÅ©ÇÃ·Î¿ì ¸ðµ¨À» ±â¹ÝÀ¸·Î ÇÏ´Â ¼Ò¼Ó¼º ³×Æ®¿öÅ©ÀÇ ±ÙÁ¢ Á߽ɵµ ºÐ¼®Àº ¿öÅ©ÇÃ·Î¿ì ¼Ò¼Ó¼º ³×Æ®¿öÅ©ÀÇ ±Ô¸ð°¡ Áõ°¡ÇÔ¿¡ µû¶ó, Á߽ɵµ ¹× ·©Å· °è»êÀÇ ½Ã°£ º¹Àâµµ ¹®Á¦Á¡À» °¡Áø´Ù´Â °ÍÀ» ¹ß°ßÇÏ¿´´Ù. º» ³í¹®¿¡¼­´Â ±ÙÁ¢ Á߽ɵµ ºÐ¼®ÀÇ ½Ã°£ º¹Àâµµ ¹®Á¦¸¦ °³¼±Çϱâ À§ÇØ, ±Ù»çÄ¡ ÃßÁ¤ ¹æ¹ýÀ» ÀÌ¿ëÇÑ ¿öÅ©ÇÃ·Î¿ì ±â¹Ý ¼Ò¼Ó¼º ³×Æ®¿öÅ©ÀÇ ÃßÁ¤ ±ÙÁ¢ Á߽ɵµ ±â¹Ý ·©Å· ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. ³ëµåÀÇ Å¸ÀÔÀÌ ¼öÇàÀÚÀÎ, ¿öÅ©ÇÃ·Î¿ì ¿¹Á¦ ¸ðµ¨À» ÃßÁ¤ ±ÙÁ¢ Á߽ɵµ ±â¹Ý ·©Å· ¾Ë°í¸®Áò¿¡ Àû¿ëÇÑ ¼º´É ºÐ¼®À» ½Ç½ÃÇÏ¿´´Ù. ¼öÇà °á°ú, ³×Æ®¿öÅ© ±Ô¸ð °üÁ¡¿¡¼­ÀÇ Á¤È®µµ´Â Æò±ÕÀûÀ¸·Î 47.5% Çâ»óµÇ¾ú°í, »ùÇà ¸ðÁý´Ü ºñÀ² °üÁ¡¿¡¼­´Â Æò±ÕÀûÀ¸·Î 9.44%Á¤µµÀÇ Çâ»óµÈ ¼öÄ¡¸¦ º¸¿´´Ù. ¶ÇÇÑ, ÃßÁ¤ ±ÙÁ¢ Á߽ɵµ ·©Å· ¾Ë°í¸®ÁòÀÇ Æò±Õ °è»ê ½Ã°£Àº ³×Æ®¿öÅ©ÀÇ ³ëµå ¼ö°¡ 2400°³, »ùÇà ¸ðÁý´ÜÀÇ ºñÀ²ÀÌ 30%ÀÏ ¶§, ±âÁ¸ ±ÙÁ¢ Á߽ɵµ ·©Å· ¾Ë°í¸®ÁòÀÇ Æò±Õ °è»ê ½Ã°£º¸´Ù 82.40%ÀÇ ³ôÀº ¼º´ÉÀ» º¸¿´´Ù.
¿µ¹®³»¿ë
(English Abstract)
A type of workflow affiliation network is one of the specialized social network types, which represents the associative relation between actors and activities. There are many methods on a workflow affiliation network measuring centralities such as degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In particular, we are interested in the closeness centrality measurements on a workflow affiliation network discovered from enterprise workflow models, and we know that the time complexity problem is raised according to increasing the size of the workflow affiliation network. This paper proposes an estimated ranking algorithm and analyzes the accuracy and average computation time of the proposed algorithm. As a result, we show that the accuracy improves 47.5%, 29.44% in the sizes of network and the rates of samples, respectively. Also the estimated ranking algorithm's average computation time improves more than 82.40%, comparison with the original algorithm, when the network size is 2400, sampling rate is 30%.
Å°¿öµå(Keyword) ¼Ò¼Ó¼º ³×Æ®¿öÅ©   ÃßÁ¤ ±ÙÁ¢ Á߽ɵµ   ·©Å· ¾Ë°í¸®Áò   affiliation network   estimated closeness centrality   ranking algorithm  
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