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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ÄÄÇ»ÆÃÀÇ ½ÇÁ¦ ³í¹®Áö (KIISE Transactions on Computing Practices)

Á¤º¸°úÇÐȸ ÄÄÇ»ÆÃÀÇ ½ÇÁ¦ ³í¹®Áö (KIISE Transactions on Computing Practices)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ¾ÏȣȭµÈ ´ëÁß±³Åë ±³ÅëÄ«µå ºòµ¥ÀÌÅÍ¿¡¼­ÀÇ °ü±¤°´ O-D ÅëÇàÆÐÅÏ ÃßÃâ ¾Ë°í¸®Áò: °ü±¤ µµ½Ã, Á¦ÁÖ¿¡ÀÇ Àû¿ë
¿µ¹®Á¦¸ñ(English Title) An Algorithm for Extracting Tourists¡¯ O-D Patterns Using Encrypted Smart Card Data of Public Transportation: Application to Tourist City, Jeju
ÀúÀÚ(Author) ±è¿¹Âù   ±èö¼ö   ±è¼º¹é   Yechan Kim   Chul-Soo Kim   Seong-Baeg Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 26 NO. 08 PP. 0349 ~ 0361 (2020. 08)
Çѱ۳»¿ë
(Korean Abstract)
´ëµµ½Ã°¡ ¾Æ´Ñ µµ½Ã¿¡¼­ÀÇ ´ëÁß±³Åë ¼­ºñ½º´Â ³·Àº ¼öÀͼº¿¡µµ ºÒ±¸ÇÏ°í ´Ù¼ö ½Â°´ÀÇ ÆíÀǼº°ú ¸¸Á·µµ Á¦°í¸¦ À§ÇØ °íºñ¿ëÀÌ ¿ä±¸µÈ´Ù. ±×·³¿¡µµ, ´ëÁß±³Åë ¼­ºñ½º´Â ³ôÀº ¹Î¿øÀÌ °è¼ÓÇؼ­ ¹ß»ýÇÏ´Â ¼­ºñ½º Áß ÇϳªÀÌ´Ù. ±×·¯¹Ç·Î ºòµ¥ÀÌÅÍ ºÐ¼®À» ÅëÇÑ ¸ÂÃãÇü ´ëÁß±³Åë ¼­ºñ½º¸¦ ½ÇÇöÇØ¾ß ÇÑ´Ù. ƯÈ÷ Á¦ÁÖ¿Í °°Àº °ü±¤ µµ½Ã´Â °ü±¤°´À» °Ü³ÉÇÑ ±³Åë µ¥ÀÌÅÍ ºÐ¼®ÀÌ ÇÊ¿äÇÏ´Ù. µû¶ó¼­ º» ¿¬±¸¿¡¼­´Â ¾ÏȣȭµÈ ´ëÁß±³Åë ±³ÅëÄ«µå °Å·¡ µ¥ÀÌÅÍ¿¡¼­ °ü±¤°´ÀÎ ½Â°´ÀÇ O-D(Origin to Destination) ÆÐÅÏÀ» ÃßÃâÇÏ´Â ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. À̸¦ ÅëÇØ °ÅÁÖÀÚ°¡ ¾Æ´Ñ ¹æ¹®°ü±¤°´¿¡ ÃÊÁ¡À» ¸ÂÃá ±³ÅëÄ«µå ºòµ¥ÀÌÅÍ ºÐ¼®ÀÇ °¡´É¼ºÀ» º¸¿©ÁÖ°íÀÚ ÇÑ´Ù. Á¦¾ÈÇÏ´Â ¾Ë°í¸®ÁòÀ¸·Î °³ÀÎÁ¤º¸ º¸È£¹ýÀÇ ½ÃÇàÀ¸·Î, °³º° ½Â°´ÀÇ Á¤º¸¸¦ ¾Ë ¼ö ¾ø´Â ¾ÏȣȭµÈ µ¥ÀÌÅͷκÎÅÍ °ü±¤°´ÀÇ O-D ÆÐÅϸ¸À» ÃßÃâÇÒ ¼ö ÀÖ´Ù. Á¦¾ÈÇÑ ¾Ë°í¸®ÁòÀ» Á¦ÁÖ Áö¿ª ´ëÁß±³Åë ¹ö½º ±³ÅëÄ«µå ºòµ¥ÀÌÅÍ¿¡ Àû¿ëÇÏ¿© Å×½ºÆ®ÇÏ¿´´Ù. º» ¿¬±¸´Â °ü±¤°´°ú °°Àº Àӽà ¹æ¹®°´ÀÇ Æ¯¼ºÀ» °í·ÁÇÑ ´ëÁß±³Åë üÁ¦ µîÀÇ °³¼±À» °¡Á®¿À´Â µ¥ È°¿ëÇÒ ¼ö ÀÖ´Ù. ¶Ç, Á¦¾ÈÇÏ´Â ¾Ë°í¸®ÁòÀ» ±³ÅëÄ«µå ºòµ¥ÀÌÅÍ Åë°è¿¡ Á¢¸ñÇÒ °æ¿ì, ½Ã°£ ¿äÀÏ ¿ùº° ¿¹»ó °ü±¤°´À» È¿°úÀûÀ¸·Î ´ëÀÀÇÒ ¼ö ÀÖ´Â Á¤º¸¸¦ ÃßÃâÇÒ ¼ö ÀÖ´Ù
¿µ¹®³»¿ë
(English Abstract)
Despite the low profitability in smaller cities, such cities pay high costs for public transportation services to meet citizens¡¯ needs. Nevertheless, public transport services continue to generate many citizens¡¯ complaints. Thus, to address such complaints and to meet citizens¡¯ needs, it is necessary to provide customized public transportation service via public transportation big data analysis. Especially in the case of tourist cities such as Jeju, it is also needed to analyze the public transit smart-card transaction data focusing on tourists¡¯ transportation activities. Thus, we propose an algorithm which can extract the O-D (Origin to Destination) patterns of tourist passengers, from the encrypted smart card data of public transportation. In this work, we show the possibility of public transit smart card data analysis focusing on not residents, but tourists. Our proposed method can extract tourists¡¯ O-D patterns from the encrypted data, which for legal reasons protect the identity of passengers. The proposed algorithm was tested with smart-card transaction data from the Jeju transportation buses. This study will be used for improving the public transportation system regarding temporary visitors. Also, in case the proposed algorithm is applied to traffic card-based big data statistics, the information of effectively meeting tourists¡¯ transportation needs by time, day, and month can be extracted and manipulated
Å°¿öµå(Keyword) ´ëÁß±³Åë   °ü±¤°´   O-D ÆÐÅÏ   ÅëÇàÆÐÅÏ   ±³ÅëÄ«µå   °ü±¤ µµ½Ã   public transportation   tourist   O-D pattern   ridership pattern   smart card   tourist city  
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