| Convolutional matrix factorization for document context-aware recommendation D Kim, C Park, J Oh, S Lee, H Yu Proceedings of the 10th ACM conference on recommender systems, 233-240, 2016 | 948 | 2016 |
| Unsupervised attributed multiplex network embedding C Park, D Kim, J Han, H Yu Proceedings of the AAAI conference on artificial intelligence 34 (04), 5371-5378, 2020 | 294 | 2020 |
| Augmentation-free self-supervised learning on graphs N Lee, J Lee, C Park Proceedings of the AAAI conference on artificial intelligence 36 (7), 7372-7380, 2022 | 214 | 2022 |
| Hdmi: High-order deep multiplex infomax B Jing, C Park, H Tong Proceedings of the Web Conference 2021, 2414-2424, 2021 | 182 | 2021 |
| Deep hybrid recommender systems via exploiting document context and statistics of items D Kim, C Park, J Oh, H Yu Information Sciences 417, 72-87, 2017 | 126 | 2017 |
| Bootstrapping user and item representations for one-class collaborative filtering D Lee, SK Kang, H Ju, C Park, H Yu Proceedings of the 44th international ACM SIGIR conference on Research and …, 2021 | 124 | 2021 |
| Improving top-K recommendation with truster and trustee relationship in user trust network C Park, D Kim, J Oh, H Yu Information Sciences 374, 100-114, 2016 | 63 | 2016 |
| Collaborative translational metric learning C Park, D Kim, X Xie, H Yu 2018 IEEE international conference on data mining (ICDM), 367-376, 2018 | 62 | 2018 |
| IMIPMF: Inferring miRNA-disease interactions using probabilistic matrix factorization J Ha, C Park, C Park, S Park Journal of biomedical informatics 102, 103358, 2020 | 57 | 2020 |
| Do" also-viewed" products help user rating prediction? C Park, D Kim, J Oh, H Yu Proceedings of the 26th international conference on world wide web, 1113-1122, 2017 | 56 | 2017 |
| Lte4g: Long-tail experts for graph neural networks S Yun, K Kim, K Yoon, C Park Proceedings of the 31st ACM International Conference on Information …, 2022 | 51 | 2022 |
| Sequential and Diverse Recommendation with Long Tail. Y Kim, K Kim, C Park, H Yu IJCAI 19, 2740-2746, 2019 | 49 | 2019 |
| Review sentiment-guided scalable deep recommender system D Hyun, C Park, MC Yang, I Song, JT Lee, H Yu The 41st international ACM SIGIR conference on research & development in …, 2018 | 48 | 2018 |
| Target-aware convolutional neural network for target-level sentiment analysis D Hyun, C Park, MC Yang, I Song, JT Lee, H Yu Information Sciences 491, 166-178, 2019 | 43 | 2019 |
| Deep multiplex graph infomax: Attentive multiplex network embedding using global information C Park, J Han, H Yu Knowledge-Based Systems 197, 105861, 2020 | 41 | 2020 |
| Improved prediction of miRNA-disease associations based on matrix completion with network regularization J Ha, C Park, C Park, S Park Cells 9 (4), 881, 2020 | 37 | 2020 |
| Task-guided pair embedding in heterogeneous network C Park, D Kim, Q Zhu, J Han, H Yu Proceedings of the 28th ACM international conference on information and …, 2019 | 34 | 2019 |
| Ahp: Learning to negative sample for hyperedge prediction H Hwang, S Lee, C Park, K Shin Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 33 | 2022 |
| Unsupervised differentiable multi-aspect network embedding C Park, C Yang, Q Zhu, D Kim, H Yu, J Han Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 32 | 2020 |
| Large language models meet collaborative filtering: An efficient all-round llm-based recommender system S Kim, H Kang, S Choi, D Kim, M Yang, C Park Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 27 | 2024 |
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