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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
SQMR-tree: ´ë¿ë·® °ø°£ µ¥ÀÌŸ¸¦ À§ÇÑ È¿À²ÀûÀÎ ÇÏÀ̺긮µå À妽º ±¸Á¶ |
¿µ¹®Á¦¸ñ(English Title) |
SQMR-tree: An Efficient Hybrid Index Structure for Large Spatial Data |
ÀúÀÚ(Author) |
½ÅÀμö
±èÁ¤ÁØ
±èÈ«±¸
ÇѱâÁØ
In-Su Shin
Joung-Joon Kim
Hong-Koo Kang
Ki-Joon Han
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¿ø¹®¼ö·Ïó(Citation) |
VOL 19 NO. 04 PP. 0045 ~ 0054 (2011. 08) |
Çѱ۳»¿ë (Korean Abstract) |
º» ³í¹®¿¡¼´Â ±âÁ¸¿¡ Á¦½ÃµÈ MR-tree¿Í SQR-treeÀÇ ÀåÁ¡À» °áÇÕÇÏ¿© ´ë¿ë·® °ø°£ µ¥ÀÌÅ͸¦ º¸´Ù È¿À²ÀûÀ¸·Î ó¸®ÇÒ ¼ö ÀÖ´Â ÇÏÀ̺긮µå À妽º ±¸Á¶ÀÎ SQMR-tree(Spatial Quad MR-tree)¸¦ Á¦½ÃÇÑ´Ù. MR-tree´Â R-tree¿¡ R-tree ¸®ÇÁ ³ëµå¸¦ Á÷Á¢ Á¢±ÙÇØÁÖ´Â ¸ÅÇÎ Æ®¸®¸¦ Àû¿ëÇÑ À妽º ±¸Á¶ÀÌ°í, SQR-tree´Â SQ-tree (Spatial Quad-tree)¿Í SQ-treeÀÇ ¸®ÇÁ ³ëµå¸¶´Ù ½ÇÁ¦·Î °ø°£ °´Ã¼¸¦ ÀúÀåÇÏ´Â R-tree°¡ °áÇÕµÈ À妽º ±¸Á¶ÀÌ´Ù. SQMR-tree´Â SQR-tree¸¦ ±âº» ±¸Á¶·Î SQR-TreeÀÇ R-tree¸¶´Ù ¸ÅÇÎ Æ®¸®°¡ Àû¿ëµÈ ÇüŸ¦ °¡Áø´Ù. µû¶ó¼, SQMR-tree´Â SQR-tree¿Í °°ÀÌ °ø°£ °´Ã¼°¡ ¿©·¯ R-tree¿¡ ºÐ»ê ÀúÀåµÇ¸ç ÁúÀÇ ¿µ¿ª¿¡ ÇØ´çÇÏ´Â R-tree¸¸ Á¢±ÙÇÏ¸é µÇ±â ¶§¹®¿¡ °ø°£ ÁúÀÇ Ã³¸® ºñ¿ëÀ» ÁÙÀÏ ¼ö ÀÖ´Ù. ¶ÇÇÑ, SQMR-tree´Â MR-tree¿Í °°ÀÌ ¸ÅÇÎ Æ®¸®¸¦ ÅëÇØ Æ®¸® °Ë»ö ¾øÀÌ R-tree ¸®ÇÁ ³ëµåÀÇ ºü¸¥ Á¢±ÙÀÌ °¡´ÉÇϱ⠶§¹®¿¡ °Ë»ö ¼º´ÉÀ» Çâ»ó½Ãų ¼ö ÀÖ´Ù. ¸¶Áö¸·À¸·Î ½ÇÇèÀ» ÅëÇØ SQMR-treeÀÇ ¿ì¼ö¼ºÀ» ÀÔÁõÇÏ¿´´Ù. |
¿µ¹®³»¿ë (English Abstract) |
In this paper, we propose a hybrid index structure, called the SQMR-tree(Spatial Quad MR-tree) that can process spatial data efficiently by combining advantages of the MR-tree and the SQR-tree. The MR-tree is an extended R-tree using a mapping tree to access directly to leaf nodes of the R-tree and the SQR-tree is a combination of the SQ-tree(Spatial Quad-tree) which is an extended Quad-tree to process spatial objects with non-zero area and the R-tree which actually stores spatial objects and are associated with each leaf node of the SQ-tree. The SQMR-tree consists of the SQR-tree as the base structure and the mapping trees associated with each R-tree of the SQR-tree. Therefore, because spatial objects are distributedly inserted into several R-trees and only R-trees intersected with the query area are accessed to process spatial queries like the SQR-tree, the query processing cost of the SQMR-tree can be reduced. Moreover, the search performance of the SQMR-tree is improved by using the mapping trees to access directly to leaf nodes of the R-tree without tree traversal like the MR-tree. Finally, we proved superiority of the SQMR-tree through experiments. |
Å°¿öµå(Keyword) |
´ë¿ë·® °ø°£ µ¥ÀÌÅÍ
ÇÏÀ̺긮µå À妽º ±¸Á¶
Large Spatial Data
Hybrid Index Structure
R-tree
SQMR-tree
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