과제정보
본 논문은 국토교통부의 스마트시티 혁신인재육성사업 및 중소기업기술정보진흥원의 지원을 받았습니다
참고문헌
- 나혜연, 남기환.(2020).사용자 선호도 변화에 따른 추천시스템의 다양성 적용. 지능정보연구, 26(4), 67-86. https://doi.org/10.13088/JIIS.2020.26.4.067
- 장동수, 이청용, 김재경.(2023).딥러닝 기반 온라인 리뷰의 언어학적 특성을 활용한 추천 시스템 성능 향상에 관한 연구. 지능정보연구, 29(1), 41-63. https://doi.org/10.13088/JIIS.2023.29.1.041
- 홍태호, 홍준우, 김은미, 김민수. (2022). 영화 리뷰의 상품 속성과 고객 속성을 통합한 지능형 추천시스템. 지능정보연구, 28(2), 1-18. https://doi.org/10.13088/JIIS.2022.28.2.001
- Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014). Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555.
- Hamilton, W., Ying, Z., & Leskovec, J. (2017). Inductive representation learning on large graphs. Advances in neural information processing systems, 30.
- Hidasi, B., Karatzoglou, A., Baltrunas, L., & Tikk, D. (2015). Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939.
- Hornik, K., Stinchcombe, M., & White, H. (1989). Multilayer feedforward networks are universal approximators. Neural networks, 2(5), 359-366. https://doi.org/10.1016/0893-6080(89)90020-8
- Kipf, T. N., & Welling, M. (2016). Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907.
- Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix factorization techniques for recommender systems. Computer, 42(8), 30-37. https://doi.org/10.1109/MC.2009.263
- Li, J., Ren, P., Chen, Z., Ren, Z., Lian, T., & Ma, J. (2017, November). Neural attentive session-based recommendation. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (pp. 1419-1428).
- Liu, Q., Zeng, Y., Mokhosi, R., & Zhang, H. (2018, July). STAMP: short-term attention/memory priority model for session-based recommendation. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 1831-1839).
- Michael, K. (2020). eCommerce Events History in Cosmetics Shop. Released March 2020, Retrieved April 30, 2023, from https://www.kaggle.com/datasets/mkechinov/ecommerce-events-history-in-cosmetics-shop
- Sahoo, N., Singh, P. V., & Mukhopadhyay, T. (2012). A hidden Markov model for collaborative filtering. MIS quarterly, 1329-1356.
- Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001, April). Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th international conference on World Wide Web (pp. 285-295).
- Shani, G., Brafman, R., & Heckerman, D. (2002, August). An MDP-based recommender system, Proc. 18th Conf. In Uncertainty in Artificial Intelligence.
- Shepard, C., Rahmati, A., Tossell, C., Zhong, L., & Kortum, P. (2011). LiveLab: measuring wireless networks and smartphone users in the field. ACM SIGMETRICS Performance Evaluation Review, 38(3), 15-20. https://doi.org/10.1145/1925019.1925023
- Velickovic, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., & Bengio, Y. (2017). Graph attention networks. arXiv preprint arXiv:1710.10903.
- Wu, S., Tang, Y., Zhu, Y., Wang, L., Xie, X., & Tan, T. (2019, July). Session-based recommendation with graph neural networks. In Proceedings of the AAAI conference on artificial intelligence (Vol. 33, No. 01, pp. 346-353).