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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ³í¹®Áö D : µ¥ÀÌŸº£À̽º

Á¤º¸°úÇÐȸ ³í¹®Áö D : µ¥ÀÌŸº£À̽º

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) µµ·Î ³×Æ®¿öÅ©¿¡¼­ A* ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇÑ k-ÃÖ±ÙÁ¢ ÀÌ¿ô °´Ã¼¿¡ ´ëÇÑ È¿°úÀûÀÎ °æ·Î Ž»ö ¹æ¹ý
¿µ¹®Á¦¸ñ(English Title) Efficient Path Finding Based on the A* algorithm for Processing k-Nearest Neighbor Queries in Road Network Databases
ÀúÀÚ(Author) ½Å¼ºÇö   ÀÌ»óö   ±è»ó¿í   ÀÌÁ¤ÈÆ   ÀÓÀ»±Ô   Sunghyun Shin   Sangchul Lee   Sangwook Kim   Junghoon Lee   Eul Gyu Im  
¿ø¹®¼ö·Ïó(Citation) VOL 36 NO. 05 PP. 0405 ~ 0410 (2009. 10)
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(Korean Abstract)
º» ³í¹®¿¡¼­´Â ±âÁ¸ k-ÃÖ±ÙÁ¢ °´Ã¼ °Ë»öÀÇ È¿À²¼ºÀ» °³¼±ÇÏ°í µµ·Î ³×Æ®¿öÅ©¿¡ÀÇ ÀÀ¿ëÀ» ¿ëÀÌÇÏ°Ô Çϱâ À§ÇÏ¿© ÁúÀÇ Á¡À¸·ÎºÎÅÍ k°³ÀÇ Á¤Àû °´Ã¼±îÁöÀÇ °æ·Î¸¦ È¿°úÀûÀ¸·Î Ž»öÇÒ ¼ö ÀÖ´Â ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÑ ¹æ¹ýÀº ¿ì¼±, k-ÃÖ±ÙÁ¢ ÀÌ¿ô ÁúÀÇ ¹æ¹ýÀ» ÀÌ¿ëÇÏ¿© Èĺ¸ Á¤Àû °´Ã¼µéÀ» ¼±Á¤ÇÑ ÈÄ À̵é Èĺ¸ °´Ã¼µéÀÇ À§Ä¡ Á¤º¸¸¦ ÀÌ¿ëÇÏ¿© ÃÖ´Ü °æ·Î¸¦ Ž»öÇÑ´Ù. ÀÏ´ë´Ù °æ·ÎŽ»öÀ» À§ÇÏ¿© A* ¾Ë°í¸®ÁòÀ» °³¼±ÇÏ¿© ¹Ýº¹µÈ ÀÏ´ëÀÏ °æ·ÎŽ»ö¿¡ µû¸£´Â Áߺ¹µÈ ³ëµå ½ºÄµÀ» Á¦°ÅÇÑ´Ù. ¶Ç, °è»êµÈ °á°ú¸¦ ÀÌ¿ëÇÏ¿© ÁúÀÇÁ¡À¸·ÎºÎÅÍ ³×Æ®¿öÅ© °Å¸®»óÀ¸·Î °¡±î¿î k°³ÀÇ Á¤Àû °´Ã¼µéÀÇ À§Ä¡¸¦ ÀçÁ¤·ÄÇÏ¿© ¹ÝȯÇÑ´Ù. ¼º´ÉÆò°¡ ½ÇÇè °á°ú, Á¦¾ÈÇÑ ¹æ¹ýÀº ±âÁ¸ ¹æ¹ýµéÀÎ INE, post-Dijkstra, ±×¸®°í naive method¿¡ ºñÇØ Á¤È®¼ºÀÌ 100% ·Î ¸Å¿ì ³ô°Ô ³ªÅ¸³µÀ¸¸ç, ³ëµå Ž»ö ½Ã°£Àº 1.3¢¦3.0¹è·Î Çâ»óµÈ ¼º´ÉÀ» º¸¿´´Ù.
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(English Abstract)
This paper proposes an efficient path finding scheme capable of searching the paths to k static objects from a given query point, aiming at both improving thelegacy k-nearest neighbor search and making it easily applicable to the road network environment. To the end of improving the speed of finding one-to-many paths, the modified A* obviates the duplicated part of node scans involved in the multiple executions of a one-to-one path finding algorithm. Additionally, the cost to the each object found in this step makes it possible to finalize the k objects according to the network distance from the candidate set as well as to order them by the path cost. Experiment results show that the proposed scheme has the accuracy of around 100% and improves the search speed by 1.3¢¦3.0 times of k-nearest neighbor searches, compared with INE, post-Dijkstra, and naive method.
Å°¿öµå(Keyword) µµ·Î ³×Æ®¿öÅ©   k-ÃÖ±ÙÁ¢ ÀÌ¿ô ÁúÀÇ   A* ¾Ë°í¸®Áò   road network   k-nearest neighbor query   A* algorit   branch and bound  
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