과제정보
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2022R1F1A1074696).
참고문헌
- J. Son, S. B. Kim, H. Kim, and S. Cho, "Review and Analysis of Recommender Systems," Journal of Korean Institute of Industrial Engineers, vol. 41, no. 2. pp. 185-208, Apr. 2015. https://doi.org/10.7232/JKIIE.2015.41.2.185
- S. Y. Cho, J. E. Choi, K. H. Lee, and H. W. Kim, "An Online Review Mining Approach to a Recommendation System," Information Systems Review, vol. 17, no. 3, pp. 95-111, Dec. 2015. https://doi.org/10.14329/isr.2015.17.3.095
- I. Im, Personalization Recommendation System Using Python, 1st ed. Seoul: CRbooks, 2020.
- Introduction to recommender systems [Internet]. Available: https://thingsolver.com/introduction-to-recommender-systems/.
- How Netflix Works. electronics [Internet]. Available: https://electronics.howstuffworks.com/netflix2.htm.
- Amazon's Product Recommendation System In 2021: How Does The Algorithm Of The eCommerce Giant Work? [Internet]. Available: https://recostream.com/blog/amazon-recommendation-system.
- Recommend Deep Learning Personalization [Internet]. Available:https://medium.com/daangn/%EB%94%A5%EB%9F%AC%EB%8B%9D-%EA%B0%9C%EC%9D%B8%ED%99%94-%EC%B6%94%EC%B2%9C-1eda682c2e8c.
- S. S. Choudhury, S. N. Mohanty, and A. K. Jagadev, "Multimodal trust based recommender system with machine learning approaches for movie recommendation," International Journal of Information Technology, vol. 13, no. 2, pp. 475-482, Jan. 2021. https://doi.org/10.1007/s41870-020-00553-2
- P. Covington, J. Adams, and E. Sargin, "Deep Neural Networks for YouTube Recommendations," in Proceedings of the 10th ACM conference on recommender systems, New York: NY, USA, pp. 191-198, 2016.
- M. Naumov, D. Mudigere, H. M. Shi, J. Huang, N. Sundaraman, J. Park, X. Wang, U. Gupta, C. Wu, A. G. Azzolini, D. Dzhulgakov, A. Mallevich, I. Cherniavskii, Y. Lu, R. Krishnamoorthi, A. Yu, V. Kondratenko, S. Pereira, X. Chen, W. Chen, V. Rao, B. Jia, L. Xiong, and M. Smelyanskiy, "Deep Learning Recommendation Model for Personalization and Recommendation Systems," arXiv preprint arXiv:1906.00091, May. 2019.
- Y. Koren, R. Bell, and C. Volinsky, "Matrix Factorization Techniques for Recommender Systems," Computer, vol. 42, no. 8, pp. 30-37, Aug. 2009.
- H. Wang, Z. Shen, S. Jiang, G. Sun, and R. J. Zhang, "User-based Collaborative Filtering Algorithm Design and Implementation," in Journal of Physics: Conference Series, Changsha, China, vol. 1757, no. 1, p. 012168, 2021. https://doi.org/10.1088/1742-6596/1757/1/012168
- B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, "Item-based collaborative filtering recommendation algorithms," in Proceedings of the 10th international conference on World Wide Web, New York: NY, USA. pp. 285-295, 2001.
- The Concept and Application of the Recommended Algorithm and the Patterns of Development [Internet]. Available: https://www.kocca.kr/trend/vol20/sub/s21.html.
- What Content-Based Filtering is and Why You Should Use It [Internet]. Available: https://www.upwork.com/resources/what-is-content-based-filtering#:~:text=Content%2Dbased%filtering%is%a,them%to%a%user%profile.
- Recommendation system using knowledge graph [Internet]. Available:https://zzaebok.github.io/knowledge_graph/recommender_syste/KG_recommend/.
- The Cold Start Problem for Recommender System [Internet]. Available: https://medium.com/@markmilankovich/the-cold-start-problem-for-recommender-systems-89a76505a7.
- The Ethical and Privacy Issues of Recommendation Engines on M edia Platform s [Internet]. Available: https://towardsdatascience.com/the-ethical-and-privacy-issues-of-recommendation-engines-on-media-platforms-9bea7bcb0abc.
- K. Sun, T. Qian, T. Chen, Y. Liang, Q. V.H. Nguyen, and H. Yin, "Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation", In Proceedings of the AAAI Conference on Artificial Intelligence, New York, USA. pp. 214-221, 2020.
- Recommender Systems: What Long-Tail tells ? [Internet]. Available: https://medium.com/@kyasar.mail/recommender-systems-what-long-tail-tells-91680f10a5b2.
- Homepage of the dogpresident [Internet]. Available: https://dogpre.com/.
- Draw your own ROC Curve and Precision-Recall Curve [Internet]. Available: https://yangoos57.github.io/ml/data_viz/roc_curve_and_pe_re_curve/.