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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ³í¹®Áö C : ÄÄÇ»ÆÃÀÇ ½ÇÁ¦

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Current Result Document : 6 / 7

ÇѱÛÁ¦¸ñ(Korean Title) ¿ÀÇǴϾ𠸶ÀÌ´× ±â¼úÀ» ÀÌ¿ëÇÑ È¿À²Àû »óÇ°Æò °Ë»ö ±â¹ý
¿µ¹®Á¦¸ñ(English Title) An Efficient Search Method of Product Reviews using Opinion Mining Techniques
ÀúÀÚ(Author) À±È«ÁØ   ±èÇÑÁØ   ÀåÀ翵   Hongjune Yune   Han-joon Kim   Jae-Young Chang  
¿ø¹®¼ö·Ïó(Citation) VOL 16 NO. 02 PP. 0222 ~ 0226 (2010. 02)
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(Korean Abstract)
±Þ¼ÓÇÑ ÀüÀÚ»ó°Å·¡ÀÇ ¹ßÀüÀ¸·Î ÀÎÇÏ¿© ¿Â¶óÀλóÀ¸·Î »óÇ°À» ±¸¸ÅÇÏ°í ±×¿¡ ´ëÇÑ Æò°¡¸¦ ÀÛ¼ºÇÏ´Â °ÍÀÌ ÀϹÝÀûÀÎ ±¸¸Å ÆÐÅÏÀÌ µÇ¾ú´Ù. ±¸¸ÅÀÚµéÀÇ »óÇ°ÆòÀº ´Ù¸¥ ÀáÀçÀûÀÎ ¼ÒºñÀÚµéÀÇ »óÇ° ±¸ÀÔÀ» À̲ø¾î³»´Âµ¥ Å« µ¿±â°¡ µÈ´Ù. ÇÏÁö¸¸ ¿Â¶óÀÎ ¼îÇθô¿¡¼­´Â »óÇ°ÆòÀÇ ¼ºÁú¿¡ ºÎÇÕÇÏ´Â ¼øÀ§¸¦ ºÎ¿©ÇÏÁö ¾Ê±â ¶§¹®¿¡, »ç¿ëÀÚ°¡ ±¸ÀÔ °áÁ¤À» À§ÇÏ¿© ¼ö¸¹Àº »óÇ°Æò¿¡ Æ÷ÇÔµÈ ÀÇ°ßµéÀ» È¿°úÀûÀ¸·Î °ËÅäÇϱâ´Â ½±Áö ¾Ê´Ù. ÀϹÝÀûÀ¸·Î »óÇ°ÆòÀº °¨Á¤ÀûÀ̸ç ÁÖ°üÀûÀÎ ÀÇ°ßÀ» Æ÷ÇÔÇÏ°í ÀÖ´Ù. ±×·¡¼­ ÀÌ·¯ÇÑ »óÇ°Æò¿¡ ¼øÀ§¸¦ ºÎ¿©ÇÏ´Â ¹æ¹ýÀº ÀÏ¹Ý À¥ °Ë»ö°ú´Â ´Þ¶ó¾ß ÇÑ´Ù. º» ³í¹®¿¡¼­´Â ¿ÀÇǴϾ𠸶ÀÌ´× ±â¼úÀ» ÀÌ¿ëÇÏ¿©, »ç¿ëÀÚÀÇ Àǵµ¿¡ µû¶ó »óÇ°Æò µ¥ÀÌÅÍ¿¡ ´ëÇØ ¼øÀ§¸¦ °áÁ¤ÇÏ´Â ±â¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈµÈ ±â¹ýÀº »ç¿ëÀÚÀÇ °Ë»ö¾î»Ó¸¸ ¾Æ´Ï¶ó »óÇ°Æò ³»¿¡ ÁÖ°üÀûÀÎ ÀÇ°ßÀÇ Æ÷ÇÔ ¿©ºÎ ¹× °¨Á¤ ±Ø¼ºÀÇ ¿£Æ®·ÎÇÇ µîÀ» °í·ÁÇÏ¿© »óÇ°ÆòÀÇ °¡Ä¡¸¦ ÆÇ´ÜÇÏ¿´´Ù. ¶ÇÇÑ ½ÇÇèÀ» ÅëÇÏ¿© Á¦¾ÈµÈ ±â¹ýÀÇ ¿ì¼ö¼ºÀ» °ËÁõÇÏ¿´´Ù.
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(English Abstract)
With the continuously increasing volume of e-commerce transactions, it is now popular to buy some products and to evaluate them on the World Wide Web. The product reviews are very useful to customers because they can make better decisions based on the indirect experiences obtainable through these reviews. However, since online shopping malls do not provide ranking results, it is not easy for users to read all the relevant review documents effectively. Product reviews include subjective and emotional opinions. Thus, the review search is different from the general web search in terms of ranking strategy. In this paper, we propose an effective method of ranking the reviews that can reflect user's intention by using opinion mining techniques. The proposed method analyzes product reviews with query words, and sentimental polarity of subjective opinions. Through diverse experiments, we show that our proposed method outperforms conventional ones.
Å°¿öµå(Keyword) ¿ÀÇǴϾ𠸶ÀÌ´×   ¿ÀÇǴϾð °Ë»ö   »óÇ°Æò   °¨Á¤ ±Ø¼º   ¿£Æ®·ÎÇÇ   Opinion Mining   Opinion Search   Product Review   Sentimental Polarity   Entropy  
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