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³í¹®¸í ÁÖ°ÅÀÇ»ç°áÁ¤Áö¿øÀ» À§ÇÑ ÀÓº£µù ±â¹Ý Çù·ÂÇÊÅ͸µ Ãßõ½Ã½ºÅÛ / Embedding-based Collaborative Filtering Recommender System for Supporting Housing Decision Making
ÀúÀÚ¸í ±èÀçÈñ(Kim, Jae-Hee) ; Àå¼±¿ì(Chang, Sun-Woo)½Äº°ÀúÀÚ ; À̵濵(Rhee, Deuk-Young) ; ÀüÇÑÁ¾(Jun, Han-Jong)
¹ßÇà»ç ´ëÇÑ°ÇÃàÇÐȸ
¼ö·Ï»çÇ× ´ëÇÑ°ÇÃàÇÐȸ³í¹®Áý, Vol.36 No.11 (2020-11)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(163) ÃÑÆäÀÌÁö(8)
ISSN 2733-6247
ÁÖÁ¦ºÐ·ù ÀÌ·Ð / °èȹ¹×¼³°è
ÁÖÁ¦¾î ÁÖ°Å ¼±È£µµ; Ãßõ½Ã½ºÅÛ; ÀÓº£µù; ÁÖ°ÅÀÇ»ç°áÁ¤; °³ÀÎÈ­ ; Housing Preference; Recommender System; Embeddings; Housing Decision Making; Personalization
¿ä¾à1 4Â÷»ê¾÷Çõ¸í½Ã´ë¿¡¼­ »ç¿ëÀÚ ¸ÂÃãÇü ¼­ºñ½ºÀÎ Ãßõ½Ã½ºÅÛÀ» ÅëÇØ ¼­ºñ½º ¸¸Á·µµ¸¦ ³ôÀÌ´Â ±â¼úÀÌ ÁÖ¸ñ¹Þ°í Àִµ¥ °ÇÃàºÐ¾ß¿¡¼­µµ ÁÖ°Å ¼±È£µµ ºÐ¼®À» ÅëÇÑ »ç¿ëÀÚ °üÁ¡ ¹Ý¿µÀ» À§ÇÑ ¿¬±¸°¡ ÁøÇàµÇ¾î¿Ô´Ù. Àα¸Åë°èÇÐÀû Ư¼º¿¡ µû¸¥ Áý´ÜÀÇ Áְż±È£µµ¸¦ ºÐ¼®ÇÑ ±âÁ¸ ¿¬±¸¿Í´Â ´Þ¸® º» ¿¬±¸´Â ºÐ¼®´ë»óÀ» °³ÀÎÀ¸·Î ¼¼ºÐÈ­ÇÏ¿© ÁÖ°Å ¼±È£µµ µµÃâ, ¸ÂÃãÇü ÁÖ°Å´ë¾È ÃßõÀÌ °¡´ÉÇϵµ·Ï ÇÏ¿´´Ù. º» ³í¹®ÀÇ ¸ñÀûÀº ÀÓº£µù ±â¹Ý ÁÖ°Å Ãßõ ½Ã½ºÅÛÀ» ±¸ÃàÇÏ¿© °³º° »ç¿ëÀÚÀÇ ¼±È£µµ µµÃâÇÏ°í ÁÖ°Å ÀÇ»ç°áÁ¤°úÁ¤ ¹× °ÇÃà°èȹ ´Ü°è Áö¿ø ¹× ¼³°èÇ°Áú Çâ»óÀ» Áö¿øÇÏ°íÀÚ ÇÑ´Ù.
¿ä¾à2 In the era of the 4th Industrial Revolution, a user-customized service recommendation system has been gaining attention in the terms of
ultra-personalization, which collects and analyzes customer information in real time to increase satisfaction through reflecting the user's
preference. In line with this global trend, various studies have been conducted to reflect the user's perspective through the analysis of housing
preferences to support the housing decision-making process and improve service satisfaction. Unlike the previous studies that analyze the
groups' housing preferences according to demographic and sociological characteristics, this study subdivided the analysis targets into the
individuals to enable the derivation of housing preferences and the recommendation of customized housing alternatives. The purpose of this
paper is to analyze the preferences of individual users by establishing an embedding-based residential recommendation system. Through this, it
was intended to support a custom housing decision-making process from the individual user's point of view and to suggest one way to
improve design quality as well as increase satisfaction in the architectural planning and design phase from the supplier's point of view.
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DOI https://doi.org/10.5659/JAIK.2020.36.11.163
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