| A unified collaborative representation learning for neural-network based recommender systems Y Xu, E Wang, Y Yang, Y Chang IEEE Transactions on Knowledge and Data Engineering 34 (11), 5126-5139, 2021 | 80 | 2021 |
| Adaptive deep modeling of users and items using side information for recommendation J Han, L Zheng, Y Xu, B Zhang, F Zhuang, SY Philip, W Zuo IEEE transactions on neural networks and learning systems 31 (3), 737-748, 2019 | 72 | 2019 |
| Efficient traffic congestion estimation using multiple spatio-temporal properties Y Yang, Y Xu, J Han, E Wang, W Chen, L Yue Neurocomputing 267, 344-353, 2017 | 54 | 2017 |
| Improving existing collaborative filtering recommendations via serendipity-based algorithm Y Yang, Y Xu, E Wang, J Han, Z Yu IEEE Transactions on Multimedia 20 (7), 1888-1900, 2017 | 52 | 2017 |
| Dynamic traffic correlations based spatio-temporal graph convolutional network for urban traffic prediction Y Xu, X Cai, E Wang, W Liu, Y Yang, F Yang Information Sciences 621, 580-595, 2023 | 48 | 2023 |
| Spatial-temporal interval aware sequential POI recommendation E Wang, Y Jiang, Y Xu, L Wang, Y Yang 2022 IEEE 38th international conference on data engineering (ICDE), 2086-2098, 2022 | 41 | 2022 |
| Real-time POI recommendation via modeling long-and short-term user preferences X Liu, Y Yang, Y Xu, F Yang, Q Huang, H Wang Neurocomputing 467, 454-464, 2022 | 40 | 2022 |
| Symmetric transformer-based network for unsupervised image registration M Ma, Y Xu, L Song, G Liu Knowledge-Based Systems 257, 109959, 2022 | 34 | 2022 |
| Citywide road-network traffic monitoring using large-scale mobile signaling data Q Huang, Y Yang, Y Xu, F Yang, Z Yuan, Y Sun Neurocomputing 444, 136-146, 2021 | 32 | 2021 |
| Slanderous user detection with modified recurrent neural networks in recommender system Y Xu, Y Yang, J Han, E Wang, J Ming, H Xiong Information Sciences 505, 265-281, 2019 | 31 | 2019 |
| Deep latent factor model with hierarchical similarity measure for recommender systems J Han, L Zheng, H Huang, Y Xu, SY Philip, W Zuo Information Sciences 503, 521-532, 2019 | 28 | 2019 |
| Neural serendipity recommendation: Exploring the balance between accuracy and novelty with sparse explicit feedback Y Xu, Y Yang, E Wang, J Han, F Zhuang, Z Yu, H Xiong ACM Transactions on Knowledge Discovery from Data (TKDD) 14 (4), 1-25, 2020 | 27 | 2020 |
| Multiagent Reinforcement Learning‐Based Taxi Predispatching Model to Balance Taxi Supply and Demand Y Yang, X Wang, Y Xu, Q Huang Journal of Advanced Transportation 2020 (1), 8674512, 2020 | 27 | 2020 |
| Exploring influence maximization in online and offline double-layer propagation scheme Y Yang, Y Xu, E Wang, K Lou, D Luan Information Sciences 450, 182-199, 2018 | 26 | 2018 |
| Truthful user recruitment for cooperative crowdsensing task: A combinatorial multi-armed bandit approach H Wang, Y Yang, E Wang, W Liu, Y Xu, J Wu IEEE Transactions on Mobile Computing 22 (7), 4314-4331, 2022 | 25 | 2022 |
| Spatial-temporal interval aware individual future trajectory prediction Y Jiang, Y Yang, Y Xu, E Wang IEEE Transactions on Knowledge and Data Engineering, 2023 | 21 | 2023 |
| Exploiting the sentimental bias between ratings and reviews for enhancing recommendation Y Xu, Y Yang, J Han, E Wang, F Zhuang, H Xiong 2018 ieee international conference on data mining (icdm), 1356-1361, 2018 | 18 | 2018 |
| GS-RS: A Generative Approach for Alleviating Cold start and Filter bubbles in Recommender Systems Y Xu, E Wang, Y Yang, H Xiong IEEE Transactions on Knowledge and Data Engineering, 2023 | 16 | 2023 |
| NeuO: Exploiting the sentimental bias between ratings and reviews with neural networks Y Xu, Y Yang, J Han, E Wang, F Zhuang, J Yang, H Xiong Neural Networks 111, 77-88, 2019 | 16 | 2019 |
| Spatiotemporal fracture data inference in sparse urban crowdsensing E Wang, M Zhang, Y Xu, H Xiong, Y Yang IEEE INFOCOM 2022-IEEE Conference on Computer Communications, 1499-1508, 2022 | 15 | 2022 |
En WangProfessor, Jilin University在 jlu.edu.cn 的电子邮件经过验证
