| DUSKG: A fine-grained knowledge graph for effective personalized service recommendation H Wang, Z Wang, S Hu, X Xu, S Chen, Z Tu Future Generation Computer Systems 100, 600-617, 2019 | 44 | 2019 |
| LTP: a new active learning strategy for BERT-CRF based named entity recognition M Liu, Z Tu, Z Wang, X Xu arXiv preprint arXiv:2001.02524, 2020 | 40 | 2020 |
| A new paradigm of software service engineering in big data and big service era X Xu, G Motta, Z Tu, H Xu, Z Wang, X Wang Computing 100, 353-368, 2018 | 39 | 2018 |
| LTP: a new active learning strategy for CRF-based named entity recognition M Liu, Z Tu, T Zhang, T Su, X Xu, Z Wang Neural Processing Letters 54 (3), 2433-2454, 2022 | 34 | 2022 |
| A federated approach to develop enterprise interoperability Z Tu, G Zacharewicz, D Chen Journal of Intelligent Manufacturing 27, 11-31, 2016 | 34 | 2016 |
| Programming framework and infrastructure for self-adaptation and optimized evolution method for microservice systems in cloud–edge environments X He, Z Tu, X Xu, Z Wang Future Generation Computer Systems 118, 263-281, 2021 | 33 | 2021 |
| Developing a web-enabled HLA federate based on poRTIco RTI Z Tu, G Zacharewicz, D Chen Proceedings of the 2011 Winter Simulation Conference (WSC), 2289-2301, 2011 | 25 | 2011 |
| Online deployment algorithms for microservice systems with complex dependencies X He, Z Tu, M Wagner, X Xu, Z Wang IEEE Transactions on Cloud Computing 11 (2), 1746-1763, 2022 | 20 | 2022 |
| A POI-sensitive knowledge graph based service recommendation method S Hu, Z Tu, Z Wang, X Xu 2019 IEEE International Conference on Services Computing (SCC), 197-201, 2019 | 19 | 2019 |
| Re-deploying microservices in edge and cloud environment for the optimization of user-perceived service quality X He, Z Tu, X Xu, Z Wang Service-Oriented Computing: 17th International Conference, ICSOC 2019 …, 2019 | 18 | 2019 |
| Faster R-CNN based autonomous navigation for vehicles in warehouse Y Sun, T Su, Z Tu 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM …, 2017 | 17 | 2017 |
| Building a high-level architecture federated interoperable framework from legacy information systems Z Tu, G Zacharewicz, D Chen International Journal of Computer Integrated Manufacturing 27 (4), 313-332, 2014 | 15 | 2014 |
| Domain priori knowledge based integrated solution design for internet of services H Xu, X Wang, Y Wang, N Li, Z Tu, Z Wang, X Xu 2020 IEEE international conference on services computing (SCC), 446-453, 2020 | 14 | 2020 |
| Dysr: A dynamic graph neural network based service bundle recommendation model for mashup creation M Liu, Z Tu, H Xu, X Xu, Z Wang IEEE Transactions on Services Computing 16 (4), 2592-2605, 2023 | 13 | 2023 |
| RE2SEP: a two-phases pattern-based paradigm for software service engineering X Xu, R Liu, Z Wang, Z Tu, H Xu 2017 IEEE World Congress on Services (SERVICES), 67-70, 2017 | 13 | 2017 |
| A data-driven approach for constructing multilayer network-based service ecosystem models M Liu, Z Tu, X Xu, Z Wang, Y Wang Software and Systems Modeling 22 (3), 919-939, 2023 | 12 | 2023 |
| Bidirectional sensing of user preferences and application changes for dynamic mobile app recommendations Z Tu, B Duan, Z Wang, X Xu Neural Computing and Applications 33, 9791-9803, 2021 | 11 | 2021 |
| Mv4ms: A spring cloud based framework for the co-deployment of multi-version microservices L Liu, X He, Z Tu, Z Wang 2020 IEEE International Conference on Services Computing (SCC), 194-201, 2020 | 11 | 2020 |
| A deep learning based personalized QoE/QoS correlation model for composite services M Li, H Xu, Z Tu, T Su, X Xu, Z Wang 2022 IEEE International Conference on Web Services (ICWS), 312-321, 2022 | 10 | 2022 |
| Community-based service ecosystem evolution analysis M Liu, Z Tu, H Xu, X Xu, Z Wang Service Oriented Computing and Applications 16 (2), 97-110, 2022 | 10 | 2022 |
