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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö > Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö ¼ÒÇÁÆ®¿þ¾î ¹× µ¥ÀÌÅÍ °øÇÐ

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Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) µ¥ÀÌÅÍ ½ºÆ®¸²¿¡ ´ëÇÑ Å°¿öµå °Ë»öÀ» À§ÇÑ, È¿À²ÀûÀÎ °»½ÅÀÌ °¡´ÉÇÑ µð½ºÅ© ±â¹Ý ¿ª»öÀÎ ±¸Á¶
¿µ¹®Á¦¸ñ(English Title) An Update-Efficient, Disk-Based Inverted Index Structure for Keyword Search on Data Streams
ÀúÀÚ(Author) ¹ÚÀºÁÖ   À̱â¿ë   EunJu Park   KiYong Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 05 NO. 04 PP. 0171 ~ 0180 (2016. 04)
Çѱ۳»¿ë
(Korean Abstract)
Æ®À§ÅÍ¿Í °°Àº ¼Ò¼È ³×Æ®¿öÅ· ¼­ºñ½º(social networking service)ÀÇ È®»êÀ¸·Î ½ºÆ®¸² ÇüÅÂÀÇ µ¥ÀÌÅÍ°¡ Å©°Ô Áõ°¡ÇÏ°í ÀÖ´Ù. ½ºÆ®¸² ÇüÅ·Πµé¾î¿Í ´©ÀûµÇ´Â µ¥ÀÌÅ͸¦ È¿À²ÀûÀ¸·Î °Ë»öÇϱâ À§Çؼ­´Â »öÀÎÀÌ ¹Ýµå½Ã ÇÊ¿äÇÏ´Ù. º» ³í¹®¿¡¼­´Â ½ºÆ®¸² ÇüÅ·Πµé¾î¿Í °è¼Ó ´©ÀûµÇ´Â µ¥ÀÌÅÍ¿¡ ´ëÇÑ Å°¿öµå °Ë»öÀ» È¿À²ÀûÀ¸·Î ÇÒ ¼ö ÀÖ°Ô ÇØÁÖ´Â, È¿À²ÀûÀÎ °»½ÅÀÌ °¡´ÉÇÑ µð½ºÅ© ±â¹Ý ¿ª»öÀÎ(inverted index) ±¸Á¶¸¦ Á¦¾ÈÇÑ´Ù. µ¥ÀÌÅÍ ½ºÆ®¸²À» °Ë»öÇϱâ À§Çؼ­´Â µ¥ÀÌÅÍÀÇ À¯ÀÔ¿¡ µû¶ó ¿ª»öÀÎÀ» °è¼ÓÇؼ­ °»½ÅÇØ ÁÖ¾î¾ß ÇÑ´Ù. ÀüÅëÀûÀÎ ¿ª»öÀÎÀ» »ç¿ëÇÏ´Â °æ¿ì, ¿ª»öÀÎÀ» °»½ÅÇϱâ À§Çؼ­´Â ¸Å¹ø µð½ºÅ©¿¡ ÀúÀåµÈ ¸ðµç »öÀÎ µ¥ÀÌÅ͸¦ ÀÐ°í ´Ù½Ã ½á¾ß ÇϹǷΠµð½ºÅ© I/O Ãø¸é¿¡¼­ ¸Å¿ì ºñÈ¿À²ÀûÀÌ´Ù. ÀÌ·¯ÇÑ ¹®Á¦¸¦ ÇØ°áÇϱâ À§ÇØ º» ³í¹®¿¡¼­´Â ¿ª»öÀÎÀ» Å©±â°¡ Áö¼öÀûÀ¸·Î Áõ°¡ÇÏ´Â ¿©·¯ ¿ª»öÀεé·Î ³ª´©¾î ÀúÀåÇÑ´Ù. »õ·Î¿î µ¥ÀÌÅÍ°¡ µé¾î¿À¸é ¿ì¼± °¡Àå ÀÛÀº Å©±âÀÇ ¿ª»öÀο¡ »ðÀÔÇÏ°í, ÀÛÀº Å©±âÀÇ ¿ª»öÀεéÀ» ´õ Å« Å©±â¸¦ °¡Áø ¿ª»öÀεé°ú ³ªÁß¿¡ º´ÇÕÇÔÀ¸·Î½á Æò±ÕÀûÀ¸·Î ¿ª»öÀÎÀ» °»½ÅÇÏ´Â ºñ¿ëÀ» Å©°Ô ³·Ãá´Ù. ¶ÇÇÑ µð½ºÅ©¿¡ ÀúÀåµÈ ¿ª»öÀεéÀ» º´ÇÕÇÒ ¶§ ¹ß»ýÇÏ´Â µð½ºÅ© I/O ºñ¿ëÀ» ÃÖ¼ÒÈ­ÇÔÀ¸·Î½á ¿ª»öÀÎÀÇ °»½Å ºñ¿ëÀ» ´õ¿í ³·Ãá´Ù. ´Ù¾çÇÑ ½ÇÇèÀ» ÅëÇØ ±âÁ¸ ¹æ¹ý°ú Á¦¾È ¹æ¹ýÀÇ È¿À²¼ºÀ» ºñ±³ÇÏ°í, Á¦¾È ¹æ¹ýÀÌ °»½Å ºñ¿ë¿¡ ÀÖ¾î ±âÁ¸ ¹æ¹ý¿¡ ºñÇØ ÈξÀ È¿À²ÀûÀÓÀ» º¸ÀδÙ.
¿µ¹®³»¿ë
(English Abstract)
As social networking services such as twitter become increasingly popular, data streams are widely prevalent these days. In order to search data accumulated from data streams efficiently, the use of an index structure is essential. In this paper, we propose an update-efficient, disk-based inverted index structure for efficient keyword search on data streams. When new data arrive at the data stream, the index needs to be updated to incorporate the new data. The traditional inverted index is very inefficient to update in terms of disk I/O, because all index data stored in the disk need to be read and written to the disk each time the index is updated. To solve this problem, we divide the whole inverted index into a sequence of inverted indices with exponentially increasing size. When new data arrives, it is first inserted into the smallest index and, later, the small indices are merged with the larger indices, which leads to a small amortize update cost for each new data. Furthermore, when indices stored in the disk are merged with each other, we minimize the disk I/O cost incurred for the merge operation, resulting in an even smaller update cost. Through various experiments, we compare the update efficiency of the proposed index structure with the previous one, and show the performance advantage of the proposed structure in terms of the update cost.
Å°¿öµå(Keyword) ¿ª»öÀΠ  µ¥ÀÌÅÍ ½ºÆ®¸²   »öÀÎ °»½Å   Å°¿öµå °Ë»ö   Inverted Index   Data Streams   Index Update   Keyword Search  
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