永利集团88304(中国区)有限公司-官方网站

[1]Intent Propagation Contrastive Collaborative Filtering, IEEE Transactions on Knowledge and Data Engineering, 2025,37(5):2665-2679 doi: 10.1109/TKDE.2025.3543241.[通信作者]

[2]Candidate-aware graph prompt-tuning for recommendation, Pattern Recognition,2025,167(11), https://doi.org/10.1016/j.patcog.2025.111733.[通信作者]

[3]Junwei Du, Yaoze Liu, Haojie Li, Xu Yu, Zhuo Chen, Feng Jiang. Multi-view constraint disentangled GAT for recommendation, Neurocomputing, 2025，640, https://doi.org/10.1016/j.neucom.2025.130317.[第1作者]

[4]Enhanced Prompting Framework for Code Summarization with Large Language Models, 2025 ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) [通信作者]

[5]A neighborhood rough sets-based ensemble method, with application to software fault prediction, Expert Systems with Applications,2025(264),3,https://doi.org/10.1016/j.eswa.2024.125919 [通信作者]

[6]Improving bug triage with the bug personalized tossing relationship, Information and Software Technology,2025(179)3, https://doi.org/10.1016/j.infsof.2024.107642.[通信作者]

[7]A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features, IEEE Transactions on Network and Service Management, 2024-08-16，doi: 10.1109/TNSM.2024.3444909. [通信作者]

[8]Behavior Pattern Mining-based Multi-Behavior Recommendation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '24). Association for Computing Machinery, New York, NY, USA, 2291–2295. https://doi.org/10.1145/3626772.3657973，2024-7-11[通信作者]

[9]Intent Distribution based Bipartite Graph Representation Learning, In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '24). Association for Computing Machinery, New York, NY, USA, 1649–1658. https://doi.org/10.1145/3626772.3657739[通信作者]

[10]A Privacy-Preserving Cross-Domain Recommendation Algorithm for Industrial IoT Devices, IEEE Transactions on Consumer Electronics, 2024, 70(1) 227-237doi: 10.1109/TCE.2023.3324968[通信作者]

[11]A random approximate reduct-based ensemble learning approach and its application in software defect prediction, Information Sciences,Volume 2022,609(9),1147-1168[通信作者]

[12]Ensemble learning based on approximate reducts and bootstrap sampling. Information Sciences.2021,547(2) 797-813 [通信作者]

[13]Ensemble learning based on random super-reduct and resampling. Artificial Intelligence Review, 2021, 54: 3115-3140. [通信作者]

[14]融合潜在联合词与异质关联兼容的Web API推荐.软件学报2025,36(5):1949-1973.[通信作者]

[15]基于问答语义匹配的知识社区新问题专家推荐方法[J].电子学报,2023,51(07):1875-1888.[第1作者]

[16]基于多关系知识增强的开发者推荐算法[J].电子学报,2023,51(11):3111-3119.[第1作者]

[17]一种结合显式特征和隐式特征的开发者混合推荐算法. 软件学报, 2022, 33(5): 1635-1651. [通信作者]

[18]基于描述语境特征词与改进GSDMM模型的服务聚类方法. 通信学报, 2021, 42(8): 176-187. [通信作者]

[19]基于混合神经网络的实体关系抽取方法研究. 中文信息学报, 2021, 35(10): 81-89. [通信作者]

[20]危化品储运事故事理图谱构建与分析. 安全与环境学报,2022,22 (06):3190-3196. [通信作者]

[21] Prediction of bug‐fixing ti9me based on distinguishable sequences fusion in open source software. Journal of Software: Evolution and Process, 2021， [第1作者]

[22] 安全管理水平量化评估指标权重优化方法. 中国安全科学学报, 2019, 29(1): 167-172.[第1作者]

师资队伍

硕士生导师

杜军威

联系方式 / CONTACT US