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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) ½Ç½Ã°£ SNS µ¥ÀÌÅ͸¦ À§ÇÑ Storm ±â¹Ý µ¿Àû ÅÂ±× Å¬¶ó¿ìµå
¿µ¹®Á¦¸ñ(English Title) Storm-Based Dynamic Tag Cloud for Real-Time SNS Data
ÀúÀÚ(Author) ¼Õ½Ã¿î   ±è´Ù¼Ö   À̼öÁ¤   ±æ¸í¼±   ¹®¾ç¼¼   Siwoon Son   Dasol Kim   Sujeong Lee   Myeong-Seon Gil   Yang-Sae Moon  
¿ø¹®¼ö·Ïó(Citation) VOL 06 NO. 06 PP. 0309 ~ 0314 (2017. 06)
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(Korean Abstract)
ÀϹÝÀûÀ¸·Î SNS (social network service) µ¥ÀÌÅÍ´Â Á¤Çü, ºñÁ¤Çü µ¥ÀÌÅÍ°¡ ¼¯¿© ºü¸£°Ô »ý¼ºµÇ´Â ºòµ¥ÀÌÅÍÀÇ Æ¯¼ºÀ» °®±â ¶§¹®¿¡ ½Ç½Ã°£ ¼öÁý/ÀúÀå/ºÐ¼®¿¡ ¸¹Àº ¾î·Á¿òÀÌ ÀÖ´Ù. º» ³í¹®¿¡¼­´Â ÀÌ·¯ÇÑ SNS µ¥ÀÌÅÍÀÇ ºÐ¼®¿¡ È°¿ëÇÒ ¼ö ÀÖ´Â Apache Storm ±â¹Ý ½Ç½Ã°£ µ¿Àû µ¥ÀÌÅÍ ½Ã°¢È­ ±â¼úÀ» Á¦¾ÈÇÑ´Ù. StormÀº ´ëÇ¥ÀûÀÎ ºòµ¥ÀÌÅÍ ±â¼ú Áß Çϳª·Î, ½Ç½Ã°£À¸·Î ¼öÁýµÇ´Â µ¥ÀÌÅ͸¦ ºÐ»ê ȯ°æ¿¡¼­ ó¸® ¹× ºÐ¼®ÇÏ´Â ¼ÒÇÁÆ®¿þ¾î Ç÷§ÆûÀÌ´Ù. º» ³í¹®Àº StormÀ» »ç¿ëÇÏ¿© ºü¸£°Ô ¹ß»ýÇÏ´Â Æ®À§ÅÍ(Twitter) µ¥ÀÌÅ͸¦ ¼öÁý ¹× Áý°èÇÏ°í, ÅÂ±× Å¬¶ó¿ìµå¸¦ ÅëÇØ ±× °á°ú¸¦ µ¿ÀûÀ¸·Î Ç¥ÇöÇÏ°íÀÚ ÇÑ´Ù. À̸¦ À§ÇØ, »ç¿ëÀÚ°¡ ¿ä±¸ÇÏ´Â Å°¿öµå¸¦ ÀԷ¹ްí ÇØ´ç Å°¿öµå¸¦ ÅëÇÑ ½Ã°¢È­ °á°ú¸¦ ½Ç½Ã°£À¸·Î È®ÀÎÇÒ ¼ö ÀÖ´Â À¥ ÀÎÅÍÆäÀ̽º¸¦ ¼³°è ¹× ±¸ÇöÇÑ´Ù. ¶ÇÇÑ, °¢°¢ÀÇ ÅÂ±× Å¬¶ó¿ìµå °á°ú¸¦ ºñ±³ÇÏ¿© ¿Ã¹Ù·Î ½Ã°¢È­µÇ¾ú´ÂÁö È®ÀÎÇÑ´Ù. º» ¿¬±¸¸¦ ÅëÇØ, »ç¿ëÀÚ´Â °ü½ÉÀÖ´Â ÁÖÁ¦°¡ SNS¿¡¼­ ¾î¶»°Ô º¯È­ÇÏ°í ÀÖ´ÂÁö Á÷°üÀûÀ¸·Î ÆÇ´ÜÇÒ ¼ö ÀÖ°Ô µÇ¸ç, ½Ã°¢È­ °á°ú´Â ÁÖÁ¦º° Æ®·»µå ºÐ¼®, °í°´ ´ÏÁî ÆÄ¾Ç µî ´Ù¸¥ ¼­ºñ½º¿¡µµ È°¿ëÀÌ °¡´ÉÇÏ´Ù.
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(English Abstract)
In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.
Å°¿öµå(Keyword) µ¿Àû ½Ã°¢È­   ºòµ¥ÀÌÅÍ   ½Ç½Ã°£ 󸮠  SNS ºÐ¼®   ÅÂ±× Å¬¶ó¿ìµå   Dynamic Visualization   Big Data   Real-Time Processing   SNS Analysis   Tag Cloud  
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