导师代码： 12012
导师姓名： 曾伟
性别： 男
特称：

职称： 副教授
学位： 工学博士学位
属性： 专职
电子邮件： zwei504@gmail.com

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学术经历： 本人已在Knowledge and Information Systems，applied soft computing，neurocomputing，ICDM等国际知名期刊和会议发表论文。

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个人简介： 长期从事推荐系统的研究工作，研究内容包括：推荐系统多样性、数据稀疏性和推荐网络结构分析。擅长于算法设计、数值分析和建模。多次到香港、海外知名高校访问，例如香港浸会大学、华沙大学、瑞士弗里堡大学、罗马大学。目前共主持两项国际项目和两项国家级项目（青年基金和面上项目），主持了多项横向项目，项目经费累计超过500万。与中石油川庆集团、中电10所、中建西勘院、中建地下空间、成都银行、民生银行等国企保持良好的合作关系。目前从事的工作主要包括：个性化推荐、大数据金融、页岩气大数据、航电设备故障诊断预测等。

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科研项目： 1. 基于大数据的复杂装备智能诊断与评估技术，十三五”装备预研共用技术，225万，2018-2022。2. 点过程在用户行为建模中的研究及应用, 国家自然基金面上项目，65万，2018-2022。3. On the diversity Problem of Recommender Systems （EG57-092011），瑞士联邦政，2012 –2013。 4.Sino Swiss Science and Technology Cooperation Program Follow-up Grants（TE-70382），瑞士联邦政府，2014. 7 – 2014. 9。5. 推荐系统的信息核挖掘及其应用研究（**），国家科学自然基金，2016-2018。6. 横向项目若干，经费累计超过500万。

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研究成果： [1] collaborative filtering via factorized neural networks, Xinke Zhao, Wei Zeng, Yixin He, Applied Soft Computing, 2021（学生一作）。[2] Collaborative filtering via heterogeneous neural networks, Wei Zeng, Ge Fan, Shan Sun, Biao Geng, Weiyi Wang, Jiacheng Li, Weibo Liu, Applied Soft Computing, 2021。[3] PPPNE: Personalized Proximity Preserved Network Embedding, Ge Fan, Biao Geng, Jianrong Tao, Kai Wang, Changjie Fan, Wei Zeng, Neurocomputing, 2021（学生一作）。[4] Preference Modeling by Exploiting Latent Components of Ratings, J Chen, W Zeng, J Shao, G Fan, Knowledge and Information Systems, 2019 （学生一作）。[5] Wei Zeng, An Zeng, Hao Liu, Ming-sheng Shang and Tao Zhou, Uncovering the information core in recommender systems, Scientific Report 4: 6140. [6] Wei Zeng, An Zeng, Ming-sheng Shang, Yi-cheng Zhang, Information filtering in sparse online systems: recommendation via semi-local diffusion, PLoS ONE 8: e79354. [7] Wei Zeng, An Zeng, Hao Liu, Ming-sheng Shang and Yi-cheng Zhang, Similarity from multi-dimensional scaling: solving the accuracy and diversity dilemma in information filtering, PLoS ONE. [8] Wei Zeng, Yuxiao Zhu, Linyuan Lü and Tao Zhou, Negative ratings play a positive role in information filtering, Physica A,390: 4486-4493[9] Wei Zeng, An Zeng, Ming-sheng Shang and Yi-cheng Zhang, Membership in social networks and the application in information filtering, The European Physical Journal B, 86: 375. [10] Wei Zeng, Ming-Sheng Shang, Qian-Ming Zhang, LinYuan Lü, Tao Zhou, Can dissimilar users contribute to accuracy and diversity of personalized recommendation? International Journal of Modern Physics C (IJMPC), 2010, 21: 1217-1227[11] Wei Zeng and Li Chen, Heterogeneous Data Fusion via Matrix Factorization for Augmenting Item, Group and Friend Recommendations, The 28th ACM Symposium On Applied Computing, SAC 2013, Coimbra, Portugal, March 18 - 22, 2013. [12] Wei Zeng and Li Chen. Recommending Interest Groups to Social Media Users by Incorporating Heterogeneous Resources. In Proceedings of 26th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE’13), pages 361-371, Amsterdam, Netherlands, June 17-21, 2013.[13] Li Chen and Wei Zeng and Quan Yuan, A unified framework for recommending items, groups and friends in social media environment via mutual resource fusion, Expert Syst. Appl. 40: 2889-2903.[14] Ming-Sheng Shang, LinYuan Lü, Wei Zeng, Tao Zhou and Yi-Cheng Zhang, Relevance is more significant than correlation: Information filtering on sparse data. Europhysics Letters, 2009, 88:68008[15] Wei Zeng, Ming-Sheng Shang, Tie-Yun Qian, Useful acquiring ratings for collaborative filtering. 2009 IEEE Youth Conference on Information Computing and Telecommunication (YC-ICT '09), 483.[16] Wei Zeng and Ming-Sheng Shang, Effects of negative ratings on personalized recommendation. 2010 5th International Conference on Computer Science and Education (ICCSE), 375[17] Yu-Xiao Zhu, Wei Zeng and Qian-Ming Zhang, The effect of rating variance on personalized recommendation, 2010 5th International Conference on Computer Science and Education (ICCSE), 366[18] Qian-Ming Zhang, Ming-Sheng Shang, Wei Zeng, Yong Chen and Linyuan Lü, Empirical comparison of local structural similarity indices for collaborative-filtering-based recommender systems, Physics Procedia, 2010, 3: 1887-1896

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专业研究方向： 专业名称 研究方向 招生类别
081200计算机科学与技术 01计算理论 硕士
081200计算机科学与技术 02机器智能与模式识别 硕士
081200计算机科学与技术 07嵌入式系统 硕士

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