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Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ÁöµµÇнÀ ¸Ó½Å·¯´× ±â¹Ý Ä«Å×°í¸® ¸ñ·Ï ºÐ·ù ¹× Ãßõ ½Ã½ºÅÛ ±¸Çö
¿µ¹®Á¦¸ñ(English Title) Development of Supervised Machine Learning based Catalog Entry Classification and Recommendation System
ÀúÀÚ(Author) ÀÌÇü¿ì   Hyung-Woo Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 20 NO. 01 PP. 0057 ~ 0066 (2019. 02)
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(Korean Abstract)
200 ¸¸¸í ÀÌ»óÀÇ È¸¿øÀ» º¸À¯ÇÏ°í ÀÖ´Â ¡°µµ¸Å²Ú¡± B2B ¿Â¶óÀÎ ¼îÇθôÀÎ °æ¿ì70% ÀÌ»óÀÇ ½ÃÀå Á¡À¯À²·Î ÇÏ·ç¿¡ 80¸¸°³ ÀÌ»óÀÇ ¾ÆÀÌÅÛÀÌ ÆǸŵǰí ÀÖ´Ù. ÇÏÁö¸¸, µ¿ÀÏÇϰųª À¯»çÇÑ ¹°Ç°ÀÌ ¼­·Î ´Ù¸¥ Ä«Å»·Î±× ¿£Æ®¸®¿¡ ÀúÀå ¹× µî·ÏµÇ¾î Àֱ⠶§¹®¿¡ ±¸¸ÅÀÚ°¡ ¾ÆÀÌÅÛÀ» °Ë»öÇÏ´Â °úÁ¤¿¡¼­ ¾î·Á¿òÀ» ´À³¢¸ç B2B ´ëÇü ¼îÇθô °ü¸®¿¡µµ ¹®Á¦Á¡ÀÌ ¹ß»ýÇÏ°í ÀÖ´Ù. µû¶ó¼­ ÀÌ¿¡ ´ëÇÑ ÇØ°á ¹æ¾ÈÀ¸·Î º» ¿¬±¸¿¡¼­´Â ´ë´ÜÀ§ ¼îÇθô ±¸¸Å Á¤º¸¸¦ ±â¹ÝÀ¸·Î Áöµµ-ÇнÀ ¸Ó½Å·¯´× ±â¹ýÀ» Àû¿ëÇÏ¿© »óÇ°¿¡ ´ëÇÑ Ä«Å»·Î±× ¸ñ·Ï ÀÚµ¿ ºÐ·ù ¹× Ãßõ ½Ã½ºÅÛÀ» °³¹ßÇÏ¿´´Ù. ±¸Ã¼ÀûÀ¸·Î ÆǸÅÀÚ°¡ ÀÚ¿¬¾î ÇüÅ·Π¹°Ç° µî·Ï Á¤º¸¸¦ ÀÔ·ÂÇϸé KoNLPy ÇüÅÂ¼Ò ºÐ¼® °úÁ¤À» ¼öÇàÇÏ¿´À¸¸ç, Naïve Bayes ºÐ·ù ¹æ½ÄÀ» ÀÀ¿ëÇÏ¿© ¹°Ç°¿¡ °¡Àå ÀûÇÕÇÑ Ä«Å»·Î±× Á¤º¸¸¦ ÀÚµ¿À¸·Î ÃßõÇØÁÖ´Â ½Ã½ºÅÛÀ» ±¸ÇöÇÏ¿´´Ù. Á¤È®µµ°¡ Çâ»óµÈ Ä«Å×°í¸® ¸ñ·ÏÀ» ±¸ÃàÇÏ¿© °á°úÀûÀ¸·Î °Ë»ö ¼Óµµ¿Í ¼îÇθô ¸ÅÃâÀ» Çâ»ó½ÃÅ°´Â È¿°ú°¡ ÀÖ¾ú´Ù.
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(English Abstract)
In the case of Domeggook B2B online shopping malls, it has a market share of over 70% with more than 2 million members and 800,000 items are sold per one day. However, since the same or similar items are stored and registered in different catalog entries, it is difficult for the buyer to search for items, and problems are also encountered in managing B2B large shopping malls. Therefore, in this study, we developed a catalog entry auto classification and recommendation system for products by using semi-supervised machine learning method based on previous huge shopping mall purchase information. Specifically, when the seller enters the item registration information in the form of natural language, KoNLPy morphological analysis process is performed, and the Naïve Bayes classification method is applied to implement a system that automatically recommends the most suitable catalog information for the article. As a result, it was possible to improve both the search speed and total sales of shopping mall by building accuracy in catalog entry efficiently.
Å°¿öµå(Keyword) Ä«Å×°í¸® ÀÚµ¿ Ãßõ   ¿Â¶óÀÎ B2B ¼ÒÇθô   ÁöµµÇнÀ ±â¹Ý ¸Ó½Å ·¯´×   ÇüÅÂ¼Ò ºÐ¼®   Naïve Bayes ºÐ·ù   Catalog Entry Auto-Recommendation   Online B2B Shopping Mall   Supervised Machine Learning   Morphological Analysis   Naive Bayes Classification Algorithm  
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