Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
¿Àµð¿À ÄÁÅؽºÆ®ÀÇ ¼±È£ °æÇâ ¹× È°µ¿ ÆÐÅÏ ºÐ¼® ±â¹ý |
¿µ¹®Á¦¸ñ(English Title) |
Methods for Analyzing Preference Tendencies and Activity Patterns with Audio Contexts |
ÀúÀÚ(Author) |
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Hyun Jung La
Moon Kwon Kim
Han Ter Jung
Soo Dong Kim
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¿ø¹®¼ö·Ïó(Citation) |
VOL 45 NO. 04 PP. 0348 ~ 0359 (2018. 04) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù¿£ SNS, UCC, µðÁöÅÐ ´ÙÀ̾ µîÀÇ °³ÀÎ ÄÁÅؽºÆ®°¡ ¸¹¾ÆÁö°í ÀÖÀ¸¸ç, ±× Á¾·ùµµ ´Ù¾çȵǰí ÀÖ´Ù. ÀÌ¿¡ µû¶ó °³ÀÎ ÄÁÅؽºÆ®¸¦ ÅëÇÑ ½Ã¸Çƽ ºÐ¼®¿¡ ´ëÇÑ °ü½ÉÀÌ Áõ°¡ÇÏ°í ÀÖ´Ù. ½Ã¸Çƽ ºÐ¼®À» ÅëÇØ °³ÀÎ ÄÁÅؽºÆ®·ÎºÎÅÍ ¶óÀÌÇÁ ½ºÅ¸ÀÏ, »îÀÇ Áú µîÀÇ °³ÀÎÀÌ ÀÎÁöÇÏÁö ¸øÇÏ´Â ´Ù¾çÇÑ Ãø¸éÀ» Ãß·ÐÇس¾ ¼ö ÀÖ´Ù. º» ³í¹®¿¡¼´Â, °³ÀÎ ÄÁÅؽºÆ® Áß ¿Àµð¿À ÄÁÅؽºÆ®¿¡ ´ëÇÑ ½Ã¸Çƽ ºÐ¼®ÀÇ ¹æ ¹ý·ÐÀ» Á¦¾ÈÇÑ´Ù. ƯÈ÷, ½Ã¸Çƽ ºÐ¼®ÀÇ Á¾·ù Áß ÇϳªÀÎ °³ÀÎ ¼±È£µµ¿Í Çൿ ÆÐÅÏ ºÐ¼®¿¡ ´ëÇÏ¿© »ó¼¼ÇÑ ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. ±×¸®°í, Á¦¾ÈµÈ ±â¹ýÀ» Æò°¡Çϱâ À§ÇÏ¿©, ½º¸¶Æ® ´ÙÀ̾ ½Ã½ºÅÛ °³¹ß¿¡ ½Ã¸Çƽ ºÐ¼® ÇÁ·Î¼¼½º¸¦ Àû¿ëÇÏ°í, ½ÇÇèÇÑ Æò°¡ °á°ú¸¦ Á¦½ÃÇÑ´Ù. Á¦¾ÈµÈ ±â¹ýÀ» Æò°¡ÇÑ´Ù. Á¦¾ÈÇÏ´Â ¾Ë°í¸®ÁòÀ» ÅëÇÑ °³ÀÎ ÄÁÅؽºÆ®ÀÇ ºÐ¼® °á°ú´Â °³ÀÎ ºñ¼ ¼ºñ½º, Ãßõ ¼ºñ½º, ±¤°í ¼ºñ½º µîÀÇ ´Ù¾çÇÑ ºÐ¾ß¿¡ È°¿ëµÉ ¼ö ÀÖÀ» °ÍÀ¸·Î ±â´ëµÈ´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Recently, there has been a trend for collecting various rich personal contexts, such as social network services (SNS), user created contents (UCC), and digital diaries. Because of this trend, much more attention to semantic analysis with personal contexts is being paid. The semantic analysis allows users to analyze and understand diverse aspects of their lives such as their lifestyle and quality of life which are not easily recognized by them. Hence, in this paper, we propose a process to infer semantics from personal contexts, more specifically, audio contexts. This paper is focused on proposing detailed algorithms for analyzing user¡¯s preference tendencies and activity patterns. To evaluate the proposed methods, we apply them to developing a system, called Smart Diary System, which is used to analyze a user¡¯s preference tendency and activity pattern from audio diaries, and we present experiment results with the system. We expect to use the proposed process and algorithms in various application domains such as personal secretary service, recommendation services, and advertising services.
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Å°¿öµå(Keyword) |
¿Àµð¿À ÄÁÅؽºÆ®
½Ã¸Çƽ ºÐ¼®
¼±È£ °æÇ⠺м®
È°µ¿ ÆÐÅÏ ºÐ¼®
audio context
semantic analysis
preference tendency analysis
activity pattern analysis
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