| Journal |
Zixuan Yuan, Junmin Liu, Haoyi Zhou, Denghui Zhang, Hao Liu, Nengjun Zhu, and Hui Xiong. "LEVER: Online Adaptive Sequence Learning Framework for High-Frequency Trading". TKDE 2023, (CCF-A, Accepted) |
2023-11-01 |
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| Conference |
Nengjun Zhu, Jieyun Huang, Jian Cao, Liang Hu, Zixuan Yuan, and Huanjing Gao. "R2V-MIF: Rule-to-Vector Contrastive Learning and Multi-channel Information Fusion for Therapy Recommendation." in Proceedings of IJCAI 2024, pp 2634-2641 (CCF-A)
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2024-04-01 |
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| Conference |
Yang Gu, Jian Cao*, Shiyou Qian, Nengjun Zhu, and Wei Guan. "ProSwats: A Proxy-based Scientific Workflow Retrieval Approach by Bridging the Gap between Textual and Structural Semantics", ICWS 2024 (CCF-B, Accepted) |
2024-06-01 |
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| Journal |
Hang Yu, Weixu Liu, Nengjun Zhu*, Pengbo Li, and Xiangfeng Luo, "IN-GFD: An Interpretable Graph Fraud Detection Model for Spam Reviews", IEEE Transactions on Artificial Intelligence. (Accepted) |
2024-07-01 |
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| Conference |
Shouyu Chen, Tangwei Ye, Laizhong Yuan, Qi Zhang, Ke Liu, Usman Naseem, Ke Sun, Nengjun Zhu, and Liang Hu. “VR-DiagNet: Medical Volumetric and Radiomic Diagnosis Networks with Interpretable Clinician-like Optimizing Visual Inspection.” in Proceedings of ACM MM 2024 (CCF-A, Accepted) |
2024-07-01 |
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| Journal |
Nengjun Zhu, Jieyun Huang, Jian Cao, Liang Hu, and Siji Zhu. "Toward Medical Test Recommendation from Optimal Attribute Selection Perspectives: A Backward Reasoning Approach". Complex & Intelligent Systems 2024, Springer. (二区, Q1, Accepted) |
2024-08-01 |
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| Journal |
Qiqi Cai, Jian Cao, and Guandong Xu, Nengjun Zhu. "Distributed Recommendation Systems: Survey and Research Directions". TOIS 2024, (CCF-A, Accepted) |
2024-08-01 |
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| Conference |
Xinzhi Wang, Mengyue Li, Nengjun Zhu*, Jiayan Qian, and Zhanyi Zheng. "Early Fire Detection based on Local Morphological Knowledge Matching". in Proceedings of IEEE ICDM 2024 (CCF-B, Accepted) |
2024-09-01 |
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| Conference |
Nengjun Zhu, Lingdan Sun, Xiangfeng Luo, Jian Cao, Qi Zhang, and Xinjiang Lu. "Exploitation or Exploration Next? User Behavior Decoupling and Emerging Intent Modeling for Next-Item Recommendation". in Proceedings of IEEE ICDM 2024 (CCF-B, Accepted) |
2024-09-01 |
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| Book |
《数据结构——C++实现（第三版）》沈俊、李晓强、朱能军、张景峤、郑宇编著，ISBN 978-7-03-077312-8 |
2024-09-01 |
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| Patent |
朱能军，孙凌丹；2024；用户行为解耦与意图学习的推荐方法及系统；申请号：202411201138.8；申请日：2024.08.29；中国 |
2024-11-01 |
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