| Mixup-transformer: Dynamic data augmentation for NLP tasks L Sun, C Xia, W Yin, T Liang, PS Yu, L He arXiv preprint arXiv:2010.02394, 2020 | 151 | 2020 |
| Time-aware metric embedding with asymmetric projection for successive POI recommendation H Ying, J Wu, G Xu, Y Liu, T Liang, X Zhang, H Xiong World Wide Web 22, 2209-2224, 2019 | 65 | 2019 |
| Meta-path based service recommendation in heterogeneous information networks T Liang, L Chen, J Wu, H Dong, A Bouguettaya Service-Oriented Computing: 14th International Conference, ICSOC 2016, Banff …, 2016 | 54 | 2016 |
| Earec: leveraging expertise and authority for pull-request reviewer recommendation in github H Ying, L Chen, T Liang, J Wu Proceedings of the 3rd international workshop on crowdsourcing in software …, 2016 | 40 | 2016 |
| A blockchain-based incremental update supported data storage system for intelligent vehicles Y Yin, Y Li, B Ye, T Liang, Y Li IEEE Transactions on Vehicular Technology 70 (5), 4880-4893, 2021 | 37 | 2021 |
| Mobile app recommendation via heterogeneous graph neural network in edge computing T Liang, X Sheng, L Zhou, Y Li, H Gao, Y Yin, L Chen Applied Soft Computing 103, 107162, 2021 | 32 | 2021 |
| FGC: GCN-based federated learning approach for trust industrial service recommendation Y Yin, Y Li, H Gao, T Liang, Q Pan IEEE Transactions on Industrial Informatics 19 (3), 3240-3250, 2022 | 28 | 2022 |
| Multi-view factorization machines for mobile app recommendation based on hierarchical attention T Liang, L Zheng, L Chen, Y Wan, SY Philip, J Wu Knowledge-Based Systems 187, 104821, 2020 | 27 | 2020 |
| Exploiting heterogeneous information for tag recommendation in API management T Liang, L Chen, J Wu, A Bouguettaya 2016 IEEE International conference on Web services (ICWS), 436-443, 2016 | 27 | 2016 |
| Joint training capsule network for cold start recommendation T Liang, C Xia, Y Yin, PS Yu Proceedings of the 43rd international ACM SIGIR conference on Research and …, 2020 | 25 | 2020 |
| A broad learning approach for context-aware mobile application recommendation T Liang, L He, CT Lu, L Chen, SY Philip, J Wu 2017 IEEE International Conference on Data Mining (ICDM), 955-960, 2017 | 24 | 2017 |
| Co-clustering WSDL documents to bootstrap service discovery T Liang, L Chen, H Ying, J Wu 2014 IEEE 7th International Conference on Service-Oriented Computing and …, 2014 | 24 | 2014 |
| Recurrent neural network based collaborative filtering for QoS prediction in IoV T Liang, M Chen, Y Yin, L Zhou, H Ying IEEE Transactions on Intelligent Transportation Systems 23 (3), 2400-2410, 2021 | 21 | 2021 |
| Selecting dynamic skyline services for QoS-based service composition J Wu, L Chen, T Liang Applied Mathematics & Information Sciences 8 (5), 2579, 2014 | 21 | 2014 |
| Content-aware recommendation via dynamic heterogeneous graph convolutional network T Liang, L Ma, W Zhang, H Xu, C Xia, Y Yin Knowledge-Based Systems 251, 109185, 2022 | 20 | 2022 |
| SMINet: State-aware multi-aspect interests representation network for cold-start users recommendation W Tao, Y Li, L Li, Z Chen, H Wen, P Chen, T Liang, Q Lu Proceedings of the AAAI conference on artificial intelligence 36 (8), 8476-8484, 2022 | 19 | 2022 |
| Spectral adversarial training for robust graph neural network J Li, J Peng, L Chen, Z Zheng, T Liang, Q Ling IEEE Transactions on Knowledge and Data Engineering 35 (9), 9240-9253, 2022 | 16 | 2022 |
| Leveraging data augmentation for service QoS prediction in cyber-physical systems Y Yin, H Xu, T Liang, M Chen, H Gao, A Longo ACM Transactions on Internet Technology (TOIT) 21 (2), 1-25, 2021 | 16 | 2021 |
| SMS: A framework for service discovery by incorporating social media information T Liang, L Chen, J Wu, G Xu, Z Wu IEEE Transactions on Services Computing 12 (3), 384-397, 2016 | 16 | 2016 |
| A semi-supervised deep convolutional framework for signet ring cell detection H Ying, Q Song, J Chen, T Liang, J Gu, F Zhuang, DZ Chen, J Wu Neurocomputing 453, 347-356, 2021 | 15 | 2021 |
Jian Wu (吴健)Zhejiang University在 zju.edu.cn 的电子邮件经过验证
