| 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 | 64* | 2022 |
| 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 | 11 | 2023 |
| 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 |
| A novel multi-layer network model for service ecosystems M Liu, Z Tu, J Wang, Z Wang 2020 international conference on service science (ICSS), 23-30, 2020 | 10 | 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, 2023 | 9 | 2023 |
| Sraslr: A novel social relation aware service label recommendation model Y Zhu, M Liu, Z Tu, T Su, Z Wang 2021 IEEE International Conference on Web Services (ICWS), 87-96, 2021 | 9 | 2021 |
| Data correction and evolution analysis of the ProgrammableWeb service ecosystem M Liu, Z Tu, Y Zhu, X Xu, Z Wang, QZ Sheng Journal of Systems and Software 182, 111066, 2021 | 8 | 2021 |
| T2l2: A tiny three linear layers model for service mashup creation M Liu, Y Zhu, H Xu, Z Tu, Z Wang Service-Oriented Computing: 19th International Conference, ICSOC 2021 …, 2021 | 5 | 2021 |
| A text mining based method for policy recommendation T Zhang, M Liu, C Ma, Z Tu, Z Wang 2021 IEEE International Conference on Services Computing (SCC), 233-240, 2021 | 4 | 2021 |
| Crossover service phenomenon analysis based on event evolutionary graph M Liu, Z Wang, Z Tu Service-Oriented Computing–ICSOC 2018 Workshops: ADMS, ASOCA, ISYyCC, CloTS …, 2019 | 4 | 2019 |
| Behaviornet: A fine-grained behavior-aware network for dynamic link prediction M Liu, Z Tu, T Su, X Wang, X Xu, Z Wang ACM Transactions on the web 18 (2), 1-26, 2024 | 3 | 2024 |
| Learning representation over dynamic graph using aggregation-diffusion mechanism M Liu, Z Tu, X Xu, Z Wang arXiv preprint arXiv:2106.01678, 2021 | 2 | 2021 |
| Tagtag: a novel framework for service tags recommendation and missing tag prediction W Chen, M Liu, Z Tu, Z Wang International Conference on Service-Oriented Computing, 340-348, 2022 | 1 | 2022 |
| External Service Sensing (ESS): Research Framework, Challenges and Opportunities Z Wang, M Liu, Z Tu, X Xu arXiv preprint arXiv:2106.09208, 2021 | 1 | 2021 |
| Conceptual models and evaluation metrics for transboundary service ecosystems M Liu, Z Tu, H Xu, X Xu, Z Wang 2020 International Conference on Service Science (ICSS), 1-8, 2020 | 1 | 2020 |
| QoSGNN: Boosting QoS Prediction Performance with Graph Neural Networks M Liu, H Xu, QZ Sheng, Z Wang IEEE Transactions on Services Computing, 2023 | | 2023 |
| BEAR: Revolutionizing Service Domain Knowledge Graph Construction with LLM S Yu, T Huang, M Liu, Z Wang International Conference on Service-Oriented Computing, 339-346, 2023 | | 2023 |
| Observation Is Reality? A Graph Diffusion-Based Approach for Service Tags Recommendation S Yu, Q Li, M Liu, Z Wang International Conference on Service-Oriented Computing, 100-114, 2023 | | 2023 |
| Who Should I Engage With at What Time? A Missing Event-Aware Temporal Graph Neural Network M Liu, Z Tu, X Xu, Z Wang IEEE Transactions on Neural Networks and Learning Systems, 2023 | | 2023 |
| Identifying and Removing the Ghosts of Reproducibility in Service Recommendation Research T Jiang, M Liu, Z Tu, Z Wang International Conference on Advanced Information Systems Engineering, 577-593, 2023 | | 2023 |
Zhongjie WangHarbin Institute of TechnologyVerified email at hit.edu.cn
