| Title |
Embedding-based Collaborative Filtering Recommender System for Supporting Housing Decision Making |
| Authors |
김재희(Kim, Jae-Hee) ; 장선우(Chang, Sun-Woo) ; 이득영(Rhee, Deuk-Young) ; 전한종(Jun, Han-Jong) |
| DOI |
https://doi.org/10.5659/JAIK.2020.36.11.163 |
| Keywords |
Housing Preference; Recommender System; Embeddings; Housing Decision Making; Personalization |
| Abstract |
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. |