近期论文
查看导师新发文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
1. Yue Li, Jun Zeng*, Haoran Tang, Junhao Wen, Min Gao, and Wei Zhou.
DMSDRec: Dynamic Structure-Aware Graph Masked Autoencoder and Spatiotemporal Diffusion for Next-POI Recommendation，IEEE Transactions on Services Computing, Vol. 18, No. 4, 2025, pp 2024-2037. (WOS:001547519500011) (JCR-1, CCF-A, 中科院二区, IF =5.5)
2. Yinchen Pan, Jun Zeng*, Ziwei Wang, Haoran Tang, Junhao Wen, Min Gao, HGDRec:Next POI Recommendation Based on Hypergraph Neural Network and Diffusion Model, IEEE Transactions on Services Computing, Vol.18, 2025, 1445-1458. (WOS:001506706500007) (CCF-A, JCR-1, 中科院二区, IF =5.5)
3. Jun Zeng*, Hongjin Tao, Junhao Wen, Min Gao, Explainable Next POI Recommendation Based on Spatial-Temporal Disentanglement Representation and Pseudo Profile Generation, Knowledge-Based Systems, Vol. 309, 2025, (WOS:001372318300001)(JCR-1, 中科院一区, IF =8.153)
4. Bo Liu, Jun Zeng*, Junhao Wen, Min Gao, Wei Zhou. CBRec: A causal way balancing multidimensional attraction effect in POI recommendations，Knowledge-Based Systems，305(2024), 112607. 1-15. https://doi.org/10.1016/j.knosys.2024.112607.(JCR-1, 中科院一区, IF =8.153)
5. Jun Zeng*, Hongjin Tao, Haoran Tang, Junhao Wen and Min Gao, Global and Local Hypergraph Learning Method with Semantic Enhancement for POI Recommendation. Information Processing and Management, 62(2025), pp. 1-17. https://doi.org/10.1016/j.ipm.2024.103868 (JCR-1, 中科院一区, CCF-B, IF=7.4)
6. Xunan Dong, Jun Zeng*, Junhao Wen, Min Gao, Wei Zhou, SFL: A Semantic-based Federated Learning Method for POI Recommendation, Information Sciences. 2024(679), pp.1-15. https://doi.org/10.1016/j.ins.2024.121057(JCR-1, 中科院一区, CCF-B, IF =8.1)
7. Lin Zhong, Jun Zeng*, Ziwei Wang, Wei Zhou, Junhao Wen. SCFL: Spatio-temporal consistency federated learning for next POI recommendation. Information Processing and Management, 61(2024), pp. 1-18. https://doi.org/10.1016/j.ipm.2024.103852(JCR-1, 中科院一区, CCF-B, IF=7.4)
8. Ziwei Wang, Jun Zeng*, Lin Zhong, Ling Liu, Min Gaoa and Junhao Wen. DSDRec: Next POI recommendation using deep semantic extraction and diffusion model, Information Sciences. 2024 (678), pp.1-20. https://doi.org/10.1016/j.ins.2024.121004 (JCR-1, 中科院一区, CCF-B, IF =8.1)
9. Hongjin Tao, Jun Zeng*, Ziwei Wang, Lin Zhong, Min Gao, Junhao Wen, Next POI Recommendation Based on Spatial and Temporal Disentanglement Representation, 2023 IEEE International Conference on Web Services (ICWS 2023), July 2 - July 8, 2023，Hybrid, Chicago, IL, United states, pp. 84-90, 2023 (CCF-B ）
10. Ziwei Wang, Jun Zeng*, Hongjin Tao, Lin Zhong. RBPSum: An Extractive Summarization Approach Using Bi-Stream Attention and Position Residual Connection. 2023 International Joint Conference on Neural Networks (IJCNN), June 18 - June 23, 2023, Gold Coast, QLD, Australia, pp. 1-8, 2023.（CCF-C）
11. Hongjin Tao, Jun Zeng*, Ziwei Wang, Yang Yu, Xiaolin Hu. SynC: A Dense Retrieval Method Based on Syntactical Contrastive Learnin. 2023 International Joint Conference on Neural Networks (IJCNN), June 18 - June 23, 2023, Gold Coast, QLD, Australia, pp. 1-8, 2023.（CCF-C）
12. Ziwei Wang, Jun Zeng*, Junhao Wen, Min Gao and Wei Zhou, Point-of-interest Recommendation using Deep Semantic Model, Expert Systems with Applications. 2023, DOI: 10.1016/j.eswa.2023.120727(SCI JCR-1, 中科院一区, IF =8.093)
13. Yang Yu, Jun Zeng*, Lin Zhong, Min Gao, Junhao Wen, Yingbo Wu, Multi-views Contrastive Learning for Dense Text Retrieval, Knowledge-Based Systems, 2023(274), pp.1-10 DOI: 10.1016/j.knosys.2023.110624 (SCI JCR-1, 中科院一区, IF =8.153)
14. Jun Zeng*, Yizhu Zhao, Ziwei Wang, Hongjin Tao, Min Gao, Junhao Wen，LGSA: A next POI prediction method by using local and global interest with spatiotemporal awareness，Expert Systems with Applications. 2023, DOI:10.1016/j.eswa.2023.120291 (SCI, JCR-1, 中科院一区, IF =8.093)
15. Jun Zeng*, Yang Yu, Junhao Wen, Wenying Jiang and Luxi Cheng, Personalized Dynamic Attention Multi-task Learning Model for Document Retrieval and Query Generation, Expert Systems with Applications, 213(2023), PP. 1-8. DOI10.1016/j.eswa.2022.119026 (SCI， JCR-1, 中科院一区, IF =8.093)
16. Jun Zeng*, Juan Yao, Min Gao and Junhao Wen, A service composition method using improved hybrid teaching learning optimization algorithm in cloud manufacturing, Journal of Cloud Computing-Advances Systems and Applications, 2022,11(1),pp.1-14 DOI10.1186/s13677-022-00343-0 (SCI， JCR-2, IF=3.895)
17. Lin Zhong, Jun Zeng*, Yang Yu, Hongjin Tao, Wenying Jiang and Luxi Cheng, A text matching model based on dynamic multi‐mask and augmented adversarial, Expert Systems, 2022, 40(2), PP. 1-16. DOI10.1111/exsy.13165. (SCI，JCR-2, IF= 2.812)
18. Jun Zeng*, Haoran Tang, Yizhu Zhao, Junhao Wen, Neu-PCM: Neural-based potential correlation mining for POI recommendation, Applied Intelligence, online access. 2022. DOI:10.1007/s10489-022-04057-3(SCI, JCR-2, IF=5.019)
19. Jun Zeng*, Yizhu Zhao, Yang Yu, Min Gao, Wei Zhou, Junhao Wen, BMAM: Complete the missing POI in the incomplete trajectory via masked and bidirectional model, EURASIP Journal on Wireless Communications and Networking, 2022:1, pp.1-17.(SCI，JCR-3, IF=2.559)
20. Hongyu Zhu, Jun Zeng*, Yang Yu and Yingbo Wu, A Zero-Shot Relation Extraction Approach Based on Contrast Learning, 34th International Conference on Software Engineering and Knowledge Engineering (SEKE 2022), July 1, 2022 - July 10, 2022, Pittsburgh, PA, United states, pp. 293-299. (CCF-C)
21. Jun Zeng*, Haoran Tang, Min Gao and Junhao Wen, “PR-RCUC: A POI Recommendation Model Using Region-Based Collaborative Filtering and User-Based Mobile Context”, Mobile Networks and Applications, 2021, 26 (6) , pp.2434-2444. (SCI，JCR-2, IF=3.077)
22. Jun Zeng*, Yizhu Zhao, Yang Yu, Min Gao and Wei Zhou, The missing POI completion based on bidirectional masked trajectory model，Collaborative Computing: Networking, Applications and Worksharing - 17th EAI International Conference CollaborateCom 2021 COLLABORATECOM（2021）, Oct. 16- 18, 2021,Virtual, Online, pp. 229-243.（CCF-C）
23. Jun Zeng*, Yizhu Zhao, Yang Yu, Min Gao and Wei Zhou, Multi-D3QN: A Multi-Strategy Deep Reinforcement Learning for Service Composition in Cloud Manufacturing, Collaborative Computing: Networking, Applications and Worksharing - 17th EAI International Conference CollaborateCom 2021 COLLABORATECOM（2021）, Oct. 16- 18, 2021,Virtual, Online, pp. 225-240.（CCF-C）
24. Juan Yao, Jun Zeng*, Junhao Wen, Wei Zhou and Min Gao, “Hybrid-TC: A Hybrid Teaching-Learning-Based Optimization Algorithm for Service Composition in Cloud Manufacturing”, International Joint Conference on Neural Networks(IJCNN2021), July 18 - 22, 2021,Virtual, Shenzhen, China, pp.1-8.（CCF C类）
25. 姚娟，邢镔，曾骏，文俊浩，云制造服务组合研究综述，计算机科学, Vol. 48, No. 7, July 2021 (中文CCF-B)
26. 于扬，邢镔，曾骏，文俊浩，KSN:一种基于知识图谱和相似度网络的 Web 服务发现方法，计算机科学，Vol. 48, No. 10, 2021, pp. 160-166 (中文CCF-B)
27. Jun Zeng*, Haoran Tang and Xin He, “RCFC: A Region-Based POI Recommendation Model with Collaborative Filtering and User Context”, Collaborative Computing: Networking, Applications and Worksharing - 16th EAI International Conference CollaborateCom 2020 COLLABORATECOM（2020）, October 16-18, Shanghai, China, 2020, pp.656-670（CCF-C）
28. Jun Zeng*, Xin He, Haoran Tang and Junhao Wen, Predicting the next location: A self‐attention and recurrent neural network model with temporal context, Transaction on Emerging Telecommunications Technologies, 2020，DOI: 10.1002/ett.3898(SCI, JCR-2, IF=3.31)
29. 唐浩然，曾骏，李烽，文俊浩，结合地点类别和社交网络的兴趣点推荐，重庆大学学报, Vol. 43, No. 7, Jul. 2020. (CSCD核心)
30. Jun Zeng*, Feng Li, Xin He and Junhao Wen, “Fused collaborative filtering with user preference, geographical and social influence for point of interest recommendation”, International Journal of Web Services Research, Vol.16(4), 2019，PP. 40-52. DOI: 10.4018/IJWSR.2019100103 (SCI)
31. Jun Zeng*, Xin He, Haoran Tang, Junhao Wen , “A next location predicting approach based on a recurrent neural network and self-attention”, Collaborative Computing: Networking, Applications and Worksharing - 15th EAI International Conference CollaborateCom 2019 COLLABORATECOM（2019）, August 19- 22, 2019，London, United kingdom，2019: 309-322. ( CCF-C)
32. Jun Zeng*，Haoran Tang，Yinghua Li and Xin He, “A deep learning model based on sparse matrix for point-of-interest recommendation”, 31st International Conference on Software Engineering and Knowledge Engineering (SEKE 2019), Lisbon, Portugal, July 10-12, 2019, pp. 379-384. DOI: 10.18293/SEKE2019-156 (EI, CCF-C)
33. Jun Zeng*, Xin He, Feng Li, Yinghua Li, Junhao Wen and Wei Zhou, “A Point-of-Interest Recommendation Method Using User Similarity,” WEB INTELLIGENCE, 16(2), 105-112. 2018.DOI: 10.3233/WEB-180376 (CCF -C）
34. Jun Zeng*, Feng Li, Junhao Wen and Yingbo Wu, “A Point of Interest Recommendation Approach by Fusing Geographical and Reputation Influence on Location Based Social Networks,” 3th International Conference on Collaborative Computing: Networking, Applications and Worksharing(CollaborateCom 2017), Vol. 252 , pp. 232-242, 2018 (CCF-C)
35. Jun Zeng*, Feng Li, Yinghua Li, Junhao Wen, Yingbo Wu. “Exploring the Influence of Contexts for Mobile Recommendation,” International Journal of Web Services Research, 14(4), 33-49, 2017, DOI: 10.4018/IJWSR.2017100102 (SCI)
京公网安备 11010802027423号