원문정보
한국인터넷방송통신학회
The International Journal of Advanced Smart Convergence
Volume 12 Number 4
2023.12
pp.202-207
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this paper, we discuss the design and implementation of a recommendation platform actually built in the field. We survey deep learning-based recommendation models that are effective in reflecting individual user characteristics. The recently proposed RNN-based sequential recommendation models reflect individual user characteristics well. The recommendation platform we proposed has an architecture that can collect, store, and process big data from a company's commercial services. Our recommendation platform provides service providers with intuitive tools to evaluate and apply timely optimized recommendation models. In the model evaluation we performed, RNN-based sequential recommendation models showed high scores.
목차
Abstract
1. Introduction
2. Recommendation Models
3. Design
3.1 Recommendation Model Learning Procedure
3.2 AI Recommendation Platform Architecture
4. Implementation : Evaluate and Deploy Recommendation Models
5. Conclusion
References
1. Introduction
2. Recommendation Models
3. Design
3.1 Recommendation Model Learning Procedure
3.2 AI Recommendation Platform Architecture
4. Implementation : Evaluate and Deploy Recommendation Models
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보