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Deep Learning-based Recommendation System using User Purchase History
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사용자 구매 내역을 활용한 딥러닝 기반 추천 시스템

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Type
Academic journal
Author
Hong-Seok Oh (충북대학교) Jae-Min Jeong (충북대학교) Yoon-Joong Nam (씽즈) Young-Duk Seo (인하대학교) Eui-Jong Lee (충북대학교)
Journal
Korean Institute of Information Technology The Journal of Korean Institute of Information Technology Vol.20 No.6 KCI Accredited Journals
Published
2022.6
Pages
117 - 128 (12page)
DOI
10.14801/jkiit.2022.20.6.117

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Deep Learning-based Recommendation System using User Purchase History
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Recently, there has been an increase in studies related to recommendation systems in various fields such as video on demand (VOD), Internet protocol television (IPTV), and e-commerce. Also, various methods (e.g., collaborator filter, support vector machine, and k-means clustering) have been applied to the recommendation systems. In this paper, we proposed a deep neural network-based recommendation system for generating various recommendation results with purchase history. We performed experiments to show the effectiveness of the proposed system using industrial data. The experimental results show that the deep learning-based system can generate recommendation results with various points of view.
#recommendation system #artificial neural network #deep neural network #big data

Contents

요약
Abstract
Ⅰ. 서론
Ⅱ. 관련 연구
Ⅲ. 딥러닝 기반 추천시스템
Ⅳ. 실험 결과
Ⅴ. 결론
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UCI(KEPA) : I410-ECN-0101-2022-004-001333993