NEWS

[1] Zhipeng Zhang, Yuhang Zhang, Mianxiong Dong, Kaoru Ota, Yao Zhang, Yonggong Ren. Collaborative tag-aware graph neural network for long-tail service recommendations[J]. IEEE Transactions on Services Computing, 2024, DOI: 10.1109/TSC.2024.3349853.

[2] Zhipeng Zhang, Yuhang Zhang, Anqi Wang, Pinglei Zhou, Yao Zhang, Yonggong Ren. User-oriented interest representation on knowledge graph for long-tail recommendation[C]. Proceedings of the 19th International Conference on Advanced Data Mining and Applications(ADMA), pp.340-355, Shenyang, China, August 21-23, 2023.

[3] Zhipeng Zhang, Yuhang Zhang, Tianyang Hao, Zuoqing Li, Yao Zhang, Masahiro Inuiguchi. Unearthing undiscovered interests: knowledge enhanced representation aggregation for long-tail recommendation[C]. Proceedings of the 10th International Conference on Integrated Uncertainty in Knowledge Modelling and Decision Making(IUKM), pp.91-103, Kanazawa, Japan, November 2-4, 2023.

[4] Zhipeng Zhang, Mianxiong Dong, Kaoru Ota, Yao Zhang, Yasuo Kudo. Context-enhanced probabilistic diffusion for urban point-of-interest recommendation[J]. IEEE Transactions on Services Computing, 2022, 15(6): 3156-3169.

[5] 任永功, 吕福泽, 张志鹏(通讯作者). 融合知识图谱与注意力机制的个性化序列推荐[J]. 小型微型计算机系统, 2022, 7(7): 1362-1369.

[6] Zhipeng Zhang, Mianxiong Dong, Kaoru Ota, Yao Zhang, Yonggong Ren. LBCF: A link-based collaborative filtering for over-fitting problem in recommender system[J]. IEEE Transactions on Computational Social Systems, 2021, 8(6): 1450-1464.

[7] 任永功, 王瑞霞, 张志鹏(通讯作者). 基于社交网络能量扩散的协同过滤推荐算法[J]. 模式识别与人工智能, 2021, 34(6): 561-571.

[8] 任永功, 王宁婧, 张志鹏(通讯作者). 基于加权三部图的协同过滤推荐算法[J]. 模式识别与人工智能, 2021, 34(7): 666-676.

[9] Zhipeng Zhang, Mianxiong Dong, Kaoru Ota, Yasuo Kudo. Alleviating new user cold-start in user-based collaborative filtering via bipartite network[J]. IEEE Transactions on Computational Social Systems, 2020, 7(3): 672-685.

[10] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai, Yonggong Ren. Improved covering-based collaborative filtering for new users’ personalized recommendations[J]. Knowledge and Information Systems. 2020, 62: 3133–3154.

[11] Zhipeng Zhang, Yao Zhang, Yonggong Ren. Employing neighborhood reduction for alleviating sparsity and cold start problems in user-based collaborative filtering[J]. Information Retrieval Journal. 2020, 23: 449–472.

[12] 任永功, 石佳鑫, 张志鹏(通讯作者). 融合关系挖掘与协同过滤的物品冷启动推荐算法[J]. 模式识别与人工智能, 2020, 33(1): 75-85.

[13] 任永功, 王思雨, 张志鹏(通讯作者). 缓解数据稀疏问题的协同过滤混合填充算法[J]. 模式识别与人工智能, 2020, 33(2): 166-175.

[14] 任永功, 张云鹏, 张志鹏(通讯作者). 基于粗糙集规则提取的协同过滤推荐算法[J]. 通信学报, 2020, 41(1): 76-83.

[15] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai, Yonggong Ren. Addressing Complete New Item Cold-Start Recommendation: A Niche Item-Based Collaborative Filtering via Interrelationship Mining[J]. Applied Sciences-Basel. 2019, 9, 1894.

[16] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai, Yonggong Ren. Enhancing Recommendation Accuracy of Item-Based Collaborative Filtering via Item-Variance Weighting[J]. Applied Sciences-Basel. 2019, 9, 1928.

[17] 张志鹏, 张尧, 任永功. 基于时间相关度和覆盖权重的协同过滤推荐算法[J]. 模式识别与人工智能, 2019, 32(4): 289-297.

[18] 张志鹏, 张尧, 任永功. 基于覆盖约简的个性化协同过滤推荐方法[J]. 模式识别与人工智能, 2019, 32(7): 607-614.

[19] 任永功, 高鹏, 张志鹏(通讯作者). 一种利用相关性度量的不确定数据频繁模式挖掘[J]. 小型微型计算机系统, 2019, 3(3): 623-627

[20] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai. Neighbor selection for user-based collaborative filtering using covering-based rough sets[J]. Annals of Operations Research, 2017, 256 (2): 359-374.

[21] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai. Improvement of item-based collaborative filtering by adding time factor and covering degree[C]. Proceedings of the 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems(SCIS&ISIS), pp. 543-547, Sapporo, Japan, August 25-28, 2016.

[22] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai. Modification of the covering-based collaborative filtering model to alleviate the new user cold-start problem[C]. Proceedings of the 16th International Conference on Advanced Intelligent Systems(ISIS), pp.1238-1249, Mokpo, Korea, November 4-7, 2016.

[23] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai. Applying covering-based rough set theory to user-based collaborative filtering to enhance the quality of recommendations[C]. Proceedings of the 3rd International Conference on Integrate Uncertainty in Knowledge Modeling and Decision Making(IUKM), pp.279-289, NhaTrang, Vietnam, October 15-17, 2015.

[24] 张志鹏, 黄明. 基于改进多目标遗传算法求解混合流水车间调度问题[J]. 计算机应用与软件, 2015, 32(10): 291-294.