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, 2025, 11(1), 1-17, SCI, IF5.2, 中科院2区
Qiqi Cai, Jian Cao, and Guandong Xu, and Nengjun Zhu, Distributed Recommendation Systems: Survey and Research Directions, ACM Transactions on Information Systems, 2024,43(1), SCI, IF6, CCF-A刊
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, IEEE Transactions On Knowledge And Data Engineering (TKDE), 2023, 36(11), 6547-6559, SCI, IF8.9, 中科院2区, CCF-A刊
Xinzhi Wang, Nengjun Zhu*, Jiahao Li, Yudong Chang, and Zhennan Li, Entity Recognition Based on Heterogeneous Graph Reasoning of Visual Region and Text Candidate, Machine Learning, 2023, 113(8), 1-20, SCI, IF5.8, 中科院3区, CCF-B刊
Xiao Wei, Chenyang Huang, and Nengjun Zhu*, Event Causality Extraction through External Event Knowledge Learning and Polyhedral Word Embedding, Machine Learning, 2023, 113(8), 5351-5378, SCI, IF5.8, 中科院3区, CCF-B刊
Bohan Jia, Jian Cao, Shiyou Qian, Nengjun Zhu, Xin Dong, Liang Zhang, Lei Cheng, and Linjian Mo, SMONE: A Session-based Recommendation Model based on Neighbor Sessions with Similar Probabilistic Intentions, ACM Transactions on Knowledge Discovery from Data (TKDD), 2023, 17(8), 111: 1-22, SCI, IF4.4, 中科院3区, CCF-B刊
Nengjun Zhu, Jian Cao*, Xinjiang Lu, Chuanren Liu, Hao Liu, Yanyan Li, Xiangfeng Luo, and Hui Xiong, Predicting a Person's Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network, ACM Transactions on Knowledge Discovery from Data (TKDD), 2022, 16(2), 116: 1-23, SCI, IF4.4, 中科院3区，CCF-B刊
Nengjun Zhu, Jian Cao, Xinjiang Lu, Hui Xiong, Learning a Hierarchical Intent Model for Next-Item Recommendation, ACM Transactions on Information Systems (TOIS). 2021. vol. 40, no. 2, article 38, pp. 1-28, CCF-A期刊
Nengjun Zhu, Jian Cao, Xinjiang Lu, and Qi Gu, Leveraging pointwise prediction with learning to rank for top-N recommendation, World Wide Web. Springer US, 2020. vol. 24, no. 1, pp. 375-396, CCF-B期刊
Nengjun Zhu, Jian Cao, Kunwei Shen, Xiaosong Chen, and Siji Zhu, A Decision Support System with Intelligent Recommendation for Multi-Disciplinary Medical Treatment, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). ACM, 2020. vol. 16, no. 1s, 33, pp1-23, CCF-B期刊
Yang Gu, Jian Cao*, Hengyu You, Nengjun Zhu*, and Shiyou Qian, ADELA: Accelerating Evolutionary Design of Machine Learning Pipelines with the Accompanying Surrogate Model, AAAI 2025 (CCF-A, Accepted)
Xinzhi Wang, Mengyue Li, Nengjun Zhu*, Jiayan Qian, and Zhanyi Zheng, Early Fire Detection based on Local Morphological Knowledge Matching, Proceedings of the IEEE International Conference on Data Mining (ICDM), 2024, 490-499, EI, CCF-B会
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, Proceedings of the IEEE International Conference on Data Mining (ICDM), 2024, 965-970, EI, CCF-B会
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, Proceedings of the 32nd ACM International Conference on Multimedia (MM), 2024, 10459-10467, EI, CCF-A会
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, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2024, 2634-2641, EI, CCF-A会
Nengjun Zhu*, Jieyun Huang, Jian Cao, Xinjiang Lu, Hao Liu, and Hui Xiong, MtiRec: A Medical Test Recommender System based on the Analysis of Treatment Programs, Proceedings of the IEEE International Conference on Data Mining (ICDM), 2023, 898-907, EI, CCF-B会
Nengjun Zhu, Jieyun Huang, Jian Cao, and Shanshan Feng, Learning User Embeddings based on Long Short-Term User Group Modeling for Next-Item Recommendation, Proceedings of CCF Conference on Computer Supported Cooperative Work and Social Computing, 2022, EI, CCSCW最佳论文
Haoran Xin, Xinjiang Lu, Nengjun Zhu, Tong Xu, Dejing Dou, and Hui Xiong, CAPTOR: A Crowd-Aware Pre-Travel Recommender System for Out-of-Town Users, Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2022, 1174-1184, EI, CCF-A会
Nengjun Zhu, Jian Cao, Yanchi Liu, Yang Yang, Haochao Ying, and Hui Xiong, Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation, in Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM). ACM, 2020. pp807-815, CCF-B会
