高 旻    

职称：教授/博导

研究方向：个性化推荐系统、异常模式检测、社会媒体挖掘

邮箱：gaomin@cqu.edu.cn  

简介 - Bio

高旻，博士，重庆大学大数据与软件学院教授、博士生导师；IEEE、中国计算机学会CCF、中国人工智能学会CAAI会员，CCF服务计算专委会委员，CCF软件工程专委会通信委员，CAAI青年工作委员会委员；美国亚利桑那州立大学访问学者(合作导师：Huan Liu教授)、英国雷丁大学访问学者(合作导师：Kecheng Liu教授)。研究领域包括推荐系统、异常检测、社会媒体挖掘。目前作为项目负责人承担国家自然科学基金项目2项、国家重点研发项目子课题、重庆市自然科学基金2项、中国博士后基金面上项目1项，以主研身份参加国家973计划项目、国家重点研发计划项目、国家科技支撑计划项目、国家自然科学基金项目等多项；目前以第一作者或通讯作者发表学术论文50余篇(Google Scholar Link)，并担任多个国际权威期刊和会议评审人，CIKM、IJCAI 、AAAI等会议的PC Member。

招募 - Join us

团队以科学研究为导向，研究内容与实际应用紧密结合，注重学生能力培养。团队氛围自由学风浓厚，实验室设备齐全。尊重学生自主性，按学生意愿选择研究方向，时间分配自由无强制，对外学术交流机会充足。欢迎编程能力强、数学英语基础扎实有强烈科研兴趣的同学加入，有科研经历或学术成果者优先。欢迎联系！    

动态 - Bulletin  

[ 2024/04 ] 论文被TKDD（CCF B）接收

[ 2024/02 ] 论文被WWW2024（CCF A）接收

[ 2024/01 ] 团队面向推荐系统的数据污染攻击实验平台ARLib正式发布，敬请关注

[ 2023/12 ] 两篇论文被ICASSP（CCF B）接收

[ 2023/11 ] 论文被VLDB（CCF A）接收

[ 2023/10 ] 大四同学论文被Expert Systems with Applications（SCI JCR Q1）接收

[ 2023/08 ] 大三同学与硕士论文被CollaborateCom与ITCAI（CCF C）接收

[ 2023/07 ] 大三同学论文被NLPCC（CCF C）接收

[ 2023/05 ] 论文被KDD2023（CCF A）接收

[ 2023/04 ] 王佳获华为奖学金研究生组一等奖（全校仅1位）

[ 2023/01 ] 论文被Information Processing and Management（SCI JCR Q1）接收

课题 - Research  

[1] 国家自然科学基金面上项目，基于域自适应与多任务序列关系感知的谣言应对研究，62176028，主持

[2] 国家自然科学基金青年基金，基于用户可信度的抗托攻击协同过滤推荐机理研究，71102065，主持

[3] 重庆市自然科学基金，多模态特征下对抗-增量式的社交网络不良言论用户检测研究，cstc2020jcyj-msxm2711，主持

[4] 中国博士后基金，基于项目时间序列异常检测的抗攻击协同过滤推荐研究，2012M521680，主持

[5] 重庆市前沿与应用基础研究计划项目，基于多维社交关系挖掘的抗干扰社会化推荐研究，cstc2015jcyjA40049，主持

[6] 中央高校基金重点项目，多视图协同训练的托攻击检测研究，106112014CDJZR095502，主持

[7] 微波源功率实时智能控制理论与控制方法，科技部国家基础研究规划项目(973计划)，主研

[8] 在线交易可靠性监测与分析技术研究，科技部国家科技支撑计划项目，主研

项目 - Projects  

QRec - 推荐算法实验平台

Yue - 音乐推荐算法实验平台

ARLib - 数据污染攻击实验平台

SDLib - 托攻击检测实验平台

Datasets - 数据集

学生 - Alumni  

大数据与软件学院学生

2011级 袁   泉（腾讯）

2012级 崔丽艳（重庆新桥医院）

2013级 田仁丽（今日头条）

2014级 谭   侃（湖南中国移动通信有限公司）李祥（重庆锐明信息技术有限公司）

2015级 余俊良（澳大利亚昆士兰大学博士后） 钟浩文（长安汽车有限公司）

2016级 宋宇琦（美国南卡罗莱纳大学全额奖学金攻博） 杨帆（中国信托登记有限责任公司）

2017级 赵泽华（悉尼大学全额奖学金攻博） 王昕毅（太平洋保险） 卢珍妮（上海银行）

2018级 张峻伟（浙江大学攻读博士学位） 王宗威（中国证券登记结算有限公司） 王润生（重庆工程学院任教）

2019级 张   帅（中冶赛迪） 钞美玲（东方财富） 曹阳（百度、长安汽车）吴凡（第630研究所） 李豪（TPLink）

2020级 王   佳（中冶赛迪） 王诗琦（浙江电网） 陶影辉（贵州航天计量测试技术研究所） 赵亮（华为）

2021级 周宏伟  黄胤秋   郭林昕   彭   琳   陈   勇

2022级 甘定怡  殷俊伟   姚云航

2023级 蔡茂林  马   浩   王顺楠    陈无寒

参与实验室科研项目学生

夏会（2012.6-2014.6）重庆理工大学 副教授

黄海魂（2012.6-2014.6）大众点评

李文涛（2014.6-2016.12）澳洲悉尼科技大学、香港中文大学 博士后

窦桐（2016.9-2018.6）爱奇艺科技有限公司

夏新（2019.10）澳洲昆士兰大学 攻博

杨焱景（2020.9-2022.6）南京大学 攻博

学生获奖 - Awards  

田仁丽（2013.9-2016.6）获2015年研究生国家奖学金 ￥20,000 （综评第一）

谭侃（2014.9-2017.6）获2016年华为奖学金 （综评第三）

余俊良（2015.9-2018.6）获2017年研究生国家奖学金 ￥20,000 （综评第一）获重庆市优秀硕士论文 ￥2,000

宋宇琦（2016.9-2019.6）获2017年研究生国家奖学金 ￥20,000 （综评第一）

赵泽华（2017.9-2020.6）获2018年研究生国家奖学金 ￥20,000 （综评第一）获重庆市优秀硕士论文 ￥2,000

张峻伟（2018.9-）获2019年航天奖学金，获2020年研究生国家奖学金 ￥20,000（综评第二）获重庆市优秀硕士论文 ￥2,000

王佳（2020.9-2023.6）获2022年研究生国家奖学金 ￥20,000 （综评第一）2023年华为奖学金一等奖 ￥8,000 （综评第一）

彭琳（2021.9-2024.6）获2022年研究生国家奖学金 ￥20,000 （综评第一）

会议论文 - Conference Papers  

[41] Yinqiu Huang,  Wang, Min Gao*, et al. Entire Chain Uplift Modeling with Context-Enhanced Learning for Intelligent Marketing. Companion Proceedings of the ACM Web Conference 2024. (WWW, CCF A)[data]

[40] Wentao Li, Maolin Cai, Min Gao, Dong Wen, Lu Qin, Wei Wang. Expanding Reverse Nearest Neighbors. PVLDB, 17(4): 630 - 642, 2023. (VLDB, CCF A)[code]

[39] Junwei Yin, Min Gao*, Kai Shu, Jia Wang, Yinqiu Huang, and Wei Zhou. Fine-Grained Discrepancy Contrastive Learning For Robust Fake News Detection. IEEE International Conference on Acoustics, Speech and Signal Processing. (ICASSP 2024, CCF B)

[38] Yunhang Yao, Min Gao*, Hongwei Zhou, Zongwei Wang, Zehua Zhao, and Qingyu Xiong. Ranking Enhanced Fine-grained Contrastive Learning For Recommendation. IEEE International Conference on Acoustics, Speech and Signal Processing. (ICASSP 2024, CCF B)

[37] Zongwei Wang, Min Gao*, Wentao Li*, Junliang Yu, Linxin Guo, and Hongzhi Yin. Efficient Bi-Level Optimization for Recommendation Denoising. Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining. (SIGKDD 2023, CCF A)[code]

[36] Chaoran Zhang, Min Gao*, Yinqiu Huang, Feng Jiang, Jia Wang, and Junhao Wen, DAAL: Domain Adversarial Active Learning Based on Dual Features for Rumor Detection. The 12th CCF International Conference on Natural Language Processing and Chinese Computing. (NLPCC 2023, CCF C)

[35] Wentao Li, Min Gao*, Dong Wen, Hongwei Zhou, Cai Ke, and Lu Qin. Manipulating Structural Graph Clustering. The 38th IEEE International Conference on Data Engineering. (ICDE 2022, CCF A).

[34] Liang Zhao, Min Gao*, and Zongwei Wang. ST-GSP: Spatial-Temporal Global Semantic Representation Learning for Urban Flow Prediction. International Conference on Web Search and Data Mining. International Conference on Web Search and Data Mining (WSDM 2022, CCF B), Phoenix, Arizona, USA, 2022.[link][code]

[33] Junwei Zhang, Min Gao*, Junliang Yu, Lei Guo, and Jundong Li. Double-Scale Self-Supervised Hypergraph Convolutional Network for Group Recommendation. The ACM International Conference on Information and Knowledge Management (CIKM 2021, CCF B), Queensland, Australia, November 2021. [link][code]

[32] Junliang Yu, Hongzhi Yin, Min Gao, Xin Xia, Xiangliang Zhang, and Quoc Viet Hung Nguyen. Socially-Aware Self-Supervised Tri-Training for Recommendation. The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD 2021, CCF A), Singapore. August 2021. [link] [code]

[31] Wentao Li, Min Gao*, Fan Wu, Wenge Rong, Junhao Wen, and Lu Qin. Manipulating Black-Box Networks for Centrality Promotion. The 37th IEEE International Conference on Data Engineering. (ICDE 2021, CCF A).

[30] Shiqi Wang, Min Gao*, Zongwei Wang, Jia Wang, Fan Wu, and Junhao Wen. Fine-Grained Spatial-Temporal Representation Learning with Missing Data Completion for Traffic Flow Prediction. International Conference on Collaborative Computing: Networking, Applications and Worksharing. (CollaborateCom, CCF C)

[29] Yinqiu Huang, Min Gao*, Jia Wang, and Kai Shu. DAFD: Domain Adaptation Framework for Fake News Detection. International Conference on Neural Information Processing. (ICONIP 2021, CCF C)

[28] Meiling Chao, Min Gao*, Junwei Zhang, et al. PATR: A Novel Poisoning Attack Based on Triangle Relations Against Deep Learning-Based Recommender Systems. International Conference on Collaborative Computing: Networking, Applications and Worksharing. (CollaborateCom, CCF C)

[27] Runsheng Wang, Min Gao*, Junwei Zhang, and Quanwu Zhao. JUST-BPR: Identify Implicit Friends with Jump and Stay for Social. The 27th International Conference on Neural Information Processing. (ICONIP 2020, CCF C)

[26] Zehua Zhao, Min Gao*, Fengji Luo, Yi Zhang, and Qingyu Xiong. LSHWE: Improving Similarity-Based Word Embedding with Locality Sensitive Hashing for Cyberbullying Detection. International Joint Conference on Neural Networks. (IJCNN 2020, CCF C) [code]

[25] Jia Wang, Min Gao*, Zongwei Wang, Runsheng Wang, and Junhao Wen. Robustness Analysis of Triangle Relations Attack in Social Recommender Systems. IEEE Cloud 2020 (CCF C)

[24] Junliang Yu, Min Gao, Hongzhi Yin, Jundong Li, Chongming Gao, and Qinyong Wang. Generating Reliable Friends via Adversarial Training to Improve Social Recommendation. The 19th IEEE International Conference on Data Mining. (ICDM 2019, CCF B)  [code]

[23] Zongwei Wang, Min Gao*, Xinyi Wang, Junliang Yu, Qingyu Xiong, and Junhao Wen. A Minimax Game for Generative and Discriminative Sample Models in Recommendation Systems. The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining. (PAKDD 2019, CCF C)  [code].

[22] Junwei Zhang, Min Gao*, Junliang Yu, Xinyi Wang, Yuqi Song, and Qingyu Xiong. Nonlinear Transformation for Multiple Auxiliary Information in Music Recommendation. 2019 International Joint Conference on Neural Networks. (IJCNN 2019, CCF C)  [code].

[21] Zhenni Lu, Min Gao*, Xinyi Wang, Junwei Zhang, Haider Ali, and Qingyu Xiong. SRRL: Select Reliable Friends for Social Recommendation with Reinforcement Learning. The 26th International Conference on Neural Information Processing.  (ICONIP 2019, CCF C)  [code]

[20] Xinyi Wang, Min Gao*, Zhenni Lu, Zongwei Wang, Junwei Zhang, and Yi Zhang. DMCM: A Deep Multi-Channel Model for Dynamic Movie Recommendation. The 26th International Conference on Neural Information Processing.  (ICONIP 2019, CCF C)  [code]

[19] Junliang Yu, Min Gao*, Jundong Li, Hongzhi Yin, and Huan Liu. Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation. The 27th ACM International Conference on Information and Knowledge Management.  (CIKM 2018, CCF B)  [code].

[18] Fan Yang, Min Gao*, Junliang Yu, Yuqi Song, and Xinyi Wang. Detection of Shilling Attack Based on Bayesian Model and User Embedding. The IEEE 29th International Conference on Tools with Artificial Intelligence. (ICTAI 2018, CCF C)  [code]

[17] Yuqi Song, Min Gao*, Junliang Yu, and Qingyu Xiong. Social Recommendation Based on Implicit Friends Discovering via Meta-Path. The IEEE 29th International Conference on Tools with Artificial Intelligence. (ICTAI 2018, CCF C)

[16] Siqi Xiang, Wenge Rong, Zhang Xiong, Min Gao, Qingyu Xiong. Visual and Audio Aware Bi-Modal Video Emotion Recognition, Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017, CCF B)

[15] Yuqi Song, Min Gao*, Junliang Yu, Wentao Li, Junhao Wen, and Qingyu Xiong. PUD: Social Spammer Detection Based on PU Learning. International Conference on Neural Information Processing. Springer, 2017.11 (ICONIP 2017, CCF C).

[14] Junliang Yu, Min Gao*, Wenge Rong, Yuqi Song, Qianqi Fang, Qingyu Xiong. Make Users and Preferred Items Closer: Recommendation via Distance Metric Learning. International Conference on Neural Information Processing. Springer, 2017.11 (ICONIP 2017, CCF C).

[13] Junliang Yu, Min Gao*, Yuqi Song, Zehua Zhao, Wenge Rong, & Qingyu Xiong. Connecting Factorization and Distance Metric Learning for Social Recommendations. Knowledge Science, Engineering and Management, Springer, Melbourne, Australia, 2017.08 (KSEM 2017, CCF C).

[12] Nan Jiang, Wenge Rong, Min Gao, Yikang Shen, Zhang Xiong. Exploration of tree-based hierarchical Softmax for recurrent language models. In Twenty-Sixth International Joint Conference on Artificial Intelligence 2017,07 (IJCAI 2017, CCF A).

[11] Wentao Li, Min Gao*, Wenge Rong, Junhao Wen, Qingyu Xiong, Ruixi Jia and Tong Dou. Social Recommendation Using Euclidean Embedding, 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Alaska, USA, 2017.05. (IJCNN 2017, CCF C)  [code]

[10] Xiang Li, Min Gao*, Wenge Rong, Qingyu Xiong, and Junhao Wen. Shilling Attacks Analysis in Collaborative Filtering Based Web Service Recommendation Systems, 2016 IEEE International Conference on Web Services (ICWS), San Francisco, US, 2016.06. (ICWS 2016, CCF B)

[09] Wentao Li, Min Gao*, Hua Li, Qingyu Xiong, Junhao Wen, and Zhongfu Wu. Dropout Prediction in MOOCs Using Behavior Features and Multi-view Semi-supervised Learning, International Joint Conference on Neural Networks, IEEE, Vancouver, Canada, 2016.07. (IJCNN 2016, CCF C)

[08] Wentao Li, Min Gao*, Wenge Rong, Junhao Wen, Qingyu Xiong, and Bin Ling. LSSL-SSD: Social Spammer Detection with Laplacian Score and Semi-supervised Learning, International Conference on Knowledge Science, Engineering and Management (KSEM), 2016, Springer, Passau, German. 2016.10. (KSEM 2016, CCF C)

[07] Feng Jiang, Min Gao*, Qingyu Xiong, Junhao Wen, and Yi Zhang. Robust Social Recommendation Techniques: A Review, Lecture Notes in Computer Science, the 17th International Conference on Informatics and Semiotics in Organisations (ICISO), São Paulo, Brazil, 2016.08. (EI)

[06] Liyan Cui, Min Gao, Qingyu Xiong, Junhao Wen, and Ning Xie. Temperature Monitoring Based on Image Processing for Intelligent Microwave Heating, Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015, Qingdao, China, 2015.07. (EI)

[05] Min Gao* and Zhongfu Wu. EPN-based method for web service composition. Lecture Notes in Computer Science, 2009, 5854: 345-354. (EI)

[04] Min Gao* and Zhongfu Wu. Personalized Context-aware Collaborative Filtering based on Neural Network and Slope One, Lecture Notes in Computer Science, 2009, 5738: 109-116. (EI)

[03] Min Gao* and Zhongfu Wu. Incorporating pragmatic information in personalized recommendation systems, The 11th International Conference on Informatics and Semiotics in Organisations, 2009, Beijing, China, 156-164. (EI)

[02] Min Gao*, Zhongfu Wu, and Kecheng Liu. Pragmatic Grid for personalized resource provision, IEEE International Conference on Service Operations and Logistics, and Informatics, 2008: 1023-1028. (EI)

[01] Min Gao*, et al., An EPN-based method for web service composition, in Proceedings of the 2008 IEEE International Conference on Networking, Architecture, and Storage, 2008: 163-164. (EI)

期刊论文 - Journal Papers  

[34] Yinqiu Huang, Min Gao*, Kai Shu, Chenghua Lin, Jia Wang, Wei Zhou. EML: Emotion-Aware Meta Learning for Cross-Event False Information Detection. ACM Transactions on Knowledge Discovery from Data, 2024 (SCI, CCF B)

[33] Yujiang Wu, Min Gao*, Ruiqi Liu, Jie Zeng, Quanwu Zhao, Jinyong Gao, Jia Zhang. Multi-Time Scale Aware Host Task Preferred Learning for WEEE Return Prediction. Expert Systems With Applications, 2024,  238, 122160 (SCI JCR Q1) [link]

[33] Shiqi Wang, Chongming Gao, Min Gao*, Junliang Yu, Zongwei Wang, Hongzhi Yin. Who Are the Best Adopters? User Selection Model for Free Trial Item Promotion. IEEE Transactions on Big Data (TBD), 2023, 9(2): 746-757 (SCI JCR Q1) [link][code]

[32] Yinqiu Huang, Min Gao*, Jia Wang, Junwei Yin, Kai Shu, Qilin Fan, Junhao Wen. Meta-Prompt Based Learning for Low-Resource False Information Detection. Information Processing and Management (IPM), 2023, 60(3): 103279 (SCI JCR Q1) [link]

[31] Jia Wang, Min Gao*, Yinqiu Huang, Kai Shu, Hualing Yi. FinD: Fine-Grained Discrepancy-Based Fake News Detection Enhanced by Event Abstract Generation. Computer Speech & Language (CSL), 2023, 78: 101461. (SCI JCR Q3) [link]

[30] 曹阳, 高旻*, 余俊良, 范琪琳, 荣文戈, 文俊浩. 基于双图混合随机游走的社会化推荐模型. 电子学报, 2023, 51(2): 286-296. DOI: 10.12263/DZXB.20210504. (CCF A) [link]

[29] Jia Zhang, Min Gao*, Liang Zhao, Jiaqi Hu, Jinyong Gao, Meiling Deng, Chao Wan, Linda Yang. Multi-time Scale Attention Network for WEEE Reverse Logistics Return Prediction, Expert Systems With Applications, 2023, 2011: 118610. (SCI JCR Q1) [link][code]

[28] Lin Peng, Huan Wu, Min Gao*, Hualing Yi, Qingyu Xiong, Linda Yang, Shuiping Cheng. TLT: Recurrent fine-tuning transfer learning for water quality long-term prediction. Water Research. 2022(225): 119171. (SCI JCR Q1) [link]

[27] Yinghui Tao, Min Gao*, Junliang Yu, Zongwei Wang, Qingyu Xiong, and Xu Wang. Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation. IEEE Transactions on Computational Social Systems, 2022. (SCI JCR Q2) [link][code]

[26] 张帅, 高旻*, 文俊浩, 熊庆宇, 唐旭. 基于自监督学习的去流行度偏差推荐方法. 电子学报, 2022, 50(10): 2361-2371. DOI: 10.12263/DZXB.20210443. (CCF A) [link]

[25] Zongwei Wang, Min Gao*, Jundong Li, Junwei Zhang, and Jiang Zhong. Gray-Box Shilling Atack: An Adversarial Learning Approach. ACM Transactions on Intelligent Systems and Technology, 2022, 13(5): 82 (1-21). (SCI JCR Q1)[link]

[24] Jia Wang, Min Gao*, Zongwei Wang, Chenghua Lin, Wei Zhou, and Junhao Wen. Ada: Adversarial Learning Based Data Augmentation for Malicious Users Detection. Applied Soft Computing, 2022 (117) 108414. (SCI JCR Q1) [link][code]

[23] Hao Li, Min Gao*, Fengtao Zhou, Yueyang Wang, Qilin Fan, and Linda Yang. Fusing Hypergraph Spectral Features for Shilling Attack Detection, Journal of Information Security and Applications, 63 (2021) 103051: 1-10. SCI JCR Q2 CCF C)[link][code]

[22] Fan Wu, Min Gao*, Junliang Yu, Zongwei Wang, Kecheng Liu, and Xu Wang. Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack. Information Sciences, 2021, 578: 683-701. (SCI JCR Q1 CCF B) [link][code]

[21] AmritaBhattacharjee, 舒凯, 高旻*, 刘欢. 网络信息生态系统中的虚假信息：检测、缓解与挑战. 计算机研究与发展, 2021, 58 (7): 1353-1365. (CCF A) [link][专知]

[20] Junwei Zhang, Min Gao*, Junliang Yu, Linda Yang, Zongwei Wang, and Qingyu Xiong. Path-based Reasoning over Heterogeneous Networks for Recommendation via Bidirectional Modeling. Neurocomputing, 2021, 461(10), 438-449. (SCI JCR Q1 CCF C) [link][code]

[19] Junliang Yu, Hongzhi Yin, Jundong Li, Min Gao, Zi Huang, and Lizhen Cui. Enhancing Social Recommendation with Adversarial Graph Convolutional Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE)（In press）(SCI JCR Q1 CCF A) [link]

[18] Chao Wu, Qingyu Xiong, Min Gao, Qiude Li, Yang Yu, and Kaige Wang. A Relative Position Attention Network for Aspect-Based Sentiment Analysis. Knowledge and Information Systems (KAIS) (2020): 1-15 (SCI JCR Q1 CCF B) [link]

[17] Min Gao1, Junwei Zhang1, Junliang Yu, Jundong Li, Junhao Wen, and Qingyu Xiong. Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective. Information Sciences, 2021 (546):1166-1185.(SCI 中科院一区 JCR Q1 CCF B)  [link]

[16] 宋宇琦, 高旻*, 李骏东, 荣文戈, 熊庆宇. 网络欺凌检测综述. 电子学报, 2020, 48(6): 1220-1229. (CCF A)

[15] Min Gao*, Bin Ling, Linda Yang, Junhao Wen, Qingyu Xiong, and Shun Li. From Similarity Perspective: A Robust Collaborative Filtering Approach for Service Recommendations. Frontiers of Computer Science (中国计算机科学前沿:英文版), 2019(2): 1-16. (SCI CCF C)

[14] Junliang Yu, Min Gao*, Wenge Rong, Wentao Li, Qingyu Xiong, and Junhao Wen. Hybrid Attacks on Model-Based Social Recommender Systems. Physica A Statistical Mechanics & Its Applications, 2017 (483): 171-181. (SCI impact factor：2.132)

[13] Min Gao*, Xiang Li, Wenge Rong, Lulan Yu, Xinyu Xiao, Junhao Wen, and Qingyu Xiong. The Performance of Location Aware Shilling Attacks in Web Service Recommendation, International Journal of Web Services Research, 2017, 14(3): 53-66. (SCI)

[12] Wentao Li, Min Gao*, Hua Li, Jun Zeng, Qingyu Xiong, and Sachio Hirokawa. Shilling Attack Detection in Recommender Systems via Selecting Patterns Analysis, IEICE Transactions on Information and System, 2016, E99–D (10): 2600-2611. (SCI)  [code]

[11] 谭侃, 高旻*, 李文涛, 田仁丽, 文俊浩, 熊庆宇, 基于双层采样主动学习的社交网络虚假用户检测方法. 自动化学报, 2017, 43(3): 436-449. (EI)

[10] 李文涛, 高旻*，李华，熊庆宇，文俊浩，凌斌, 一种基于流行度分类特征的托攻击检测算法. 自动化学报, 2015 41 (9): 1563-1576. (EI)

[09] Hui Xia, Bin Fang, Min Gao, Hui Ma, Yuanyan Tang, and Jing Wen. A  novel item anomaly detection approach against shilling attacks in collaborative recommendation systems using the dynamic time interval segmentation technique, Information Sciences 306 (2015): 150-165. (SCI CCF B, IF: 4.305)

[08] Feng Jiang, Min Gao*, and Hui Xia. An Evaluation Approach Based on Word-of-Mouth for Trust Models in Recommendation Systems, Computer Modelling and New Technologies, 2014, 18(11): 605-609. (EI)

[07] Min Gao*, Yunqing Fu, Yixiong Chen, and Feng Jiang. User-Weight Model for Item-based Recommendation Systems, Journal of Software, 2012, 7(9): 2133-2140. (EI)

[06] Min Gao*, Yue Ma, Qingyu Xiong, Junhao Wen, Huixi Tan, and Chengliang Wang. Construction and Implementation of Surveillance System for Software Engineering Oriented Trainings, International Review on Computers and Software, 2012, 7(4): 1855-1859. (EI)

[05] Min Gao*, Zhongfu Wu, and Feng Jiang. Userrank for item-based collaborative filtering recommendation. Information Processing Letters 111, no. 9 (2011): 440-446. (SCI CCF C)

[04] Min Gao*, Zhongfu Wu, and Feng Jiang. An Anti-"Shilling Attacks" Collaborative Filtering Algorithm Based on User Trust Ranks and Items, Journal of Chongqing University (Natural Science) 重庆大学学报（自然科学版）, 2011, 34(5): 135-142. (In Chinese) (EI)

[03] Min Gao*, Kecheng Liu, and Zhongfu Wu. Personalisation in web computing and informatics: Theories, techniques, applications, and future research. Information Systems Frontiers 12, no. 5 (2010): 607-629. (SCI IF：3.232)

[02] Min Gao* and Zhongfu Wu. Incorporating Personalized Contextual Information in Item-based Collaborative Filtering Recommendation. Journal of Software. 2010, 5(7): 729-736. (EI)

[01] Min Gao and Zhongfu Wu*. Personalized context and item based collaborative filtering recommen,dation, Journal of Southeast University (Natural Science) 东南大学学报（自然科学版）, 2009, 9(39): 27-31. (In Chinese) (EI)


专利 - Patents  

[09] 高旻, 黄胤秋,殷俊伟,王佳,熊庆宇,王悦阳,范琪琳. 基于情绪感知元学习的跨事件虚假新闻检测方法. 202310310495.7

[08] 高旻, 殷俊伟,郭林昕,黄胤秋,江峰,熊庆宇. 一种基于读者行为模拟的虚假新闻检测方法及设备. 202310685289.4

[07] 高旻, 赵亮等. 一种面向区域流量预测的时空全局语义表示学习方法. 202210135460.X

[06] 高旻, 武宇江. 一种基于多时间尺度的主任务优先预测方法. 202310381960.6

[05] 高旻, 刘瑞奇等. 双重迁移的预测模型生成方法及废旧家电回收量预测方法. 202310462176.8

[04] 高旻, 张甲等. 基于多时间尺度注意力网络的废旧家电回收量预测方法. 202210642950.9

[03] 高旻，张峻伟等. 一种基于对抗学习与双向长短期记忆网络的推荐算法.202010903794.8

[02] 赵泽华，高旻等. 一种网络欺凌检测方法. 202010083486.5

[01] 李文涛，高旻等. 一种基于流行度分类特征的托攻击检测算法. 201510238156.8