李辉

职称:
E-mail:
Homepage:
研究方向:
助理教授、特任副研究员、硕士生导师
hui {at} xmu.edu.cn
数据挖掘、信息检索、数据库、人工智能

【详细信息】

最新的信息可查看我的个人主页:https://lihui.info/zh

李辉,现任厦门大学信息学院计算机科学与技术系助理教授、特任副研究员、硕士生导师。我于香港大学获得计算机科学Ph.D.(2018年)和M.Phil.(2015年)学位,于中南大学获得软件工程学士学位(2012年)。

我的主要研究领域为数据挖掘、信息检索、数据库、人工智能,近期主要的研究课题为鲁棒推荐系统和异构图数据挖掘。

我目前主持国自然青年基金、腾讯微信犀牛鸟专项研究计划、CCF-腾讯犀牛鸟基金等多项科研项目。多篇论文发表于数据挖掘、信息检索、数据库、人工智能领域顶级会议和期刊上。

组内学生定期参与国内互联网企业合作科研项目。现招收研究生和愿意参与科研的本科生,欢迎对我的研究方向感兴趣的同学联系我。

【主讲课程】

  • 数据挖掘与分析(研究生英文课程)

  • 操作系统原理(本科生课程)

  • UNIX系统程序设计(本科生课程)

【CCF-A类和CCF-B类论文】

最新的论文发表列表见我的主页:https://lihui.info/publications

[1] Hui Li, Lianyun Li, Guipeng Xv, Chen Lin, Ke Li, and Bingchuan Jiang. 2022. SPEX: A Generic Framework for Enhancing Neural Social Recommendation. ACM Transactions on Information Systems (TOIS). 2022. (CCF-A类)

[2] Hui Li, Yanlin Wang, Ziyu Lyu, and Jieming Shi. Multi-task Learning for Recommendation over Heterogeneous Information Network. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2022. (CCF-A类)

[3] Yuqiu Qian, Conghui Tan, Danhao Ding, Hui Li*, and Nikos Mamoulis. Fast and Secure Distributed Nonnegative Matrix Factorization. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2022. (CCF-A类,通讯作者)

[4] Chen Lin, Xinyi Liu, Guipeng Xv, and Hui Li*. Mitigating Sentiment Bias for Recommender Systems. In International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2021. (CCF-A类,通讯作者)

[5] Yanlin Wang and Hui Li*. Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs. In AAAI Conference on Artificial Intelligence (AAAI). 2021. (CCF-A类,通讯作者)

[6] Chen Lin, Zhichao Ouyang, Junqing Zhuang, Jianqiang Chen, Hui Li*, and Rongxin Wu. Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting. In IEEE/ACM International Conference on Program Comprehension. ICPC. 2021. (CCF-B类,通讯作者)

[7] Chen Lin, Zhichao Ouyang, Xiaoli Wang, Hui Li, and Zhenhua Huang. Preserve Integrity in Realtime Event Summarization. ACM Transactions on Knowledge Discovery from Data. TKDD. 2021. (CCF-B类)

[8] Ziyu Lyu, Min Yang, and Hui Li. Multi-view Group Representation Learning for Location-aware Group Recommendation. Information Sciences. 2021. (CCF-B类)

[9] Chen Lin, Si Chen, Hui Li*, Yanghua Xiao, Lianyun Li, and Qian Yang. Attacking Recommender Systems with Augmented User Profiles. In Conference on Information and Knowledge Management (CIKM). 2020. (CCF-B类,通讯作者)

[10] Yunsen Hong, Hui Li, Xiaoli Wang, and Chen Lin. DEAMER: a Deep Exposure-Aware Multimodal Content-based Recommendation System. In International Conference on Database Systems for Advanced Applications (DASFAA). 2020. (CCF-B类)

[11] Cheng Wang, Mathias Niepert, and Hui Li*. RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). 2020. (CCF-B类,通讯作者)

[12] Hui Li, Ye Liu, Nikos Mamoulis, and David S. Rosenblum. 2020. Translation-Based Sequential Recommendation for Complex Users on Sparse Data. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2020. (CCF-A类)

[13] Hui Li, Yu Liu, Yuqiu Qian, Nikos Mamoulis, Wenting Tu, and David W. Cheung. HHMF: Hidden Hierarchical Matrix Factorization for Recommender Systems. Data Mining and Knowledge Discovery (DMKD). 2019. (CCF-B类)

[14] Yunjie Wang, Hui Li, and Chen Lin. Modeling Sentiment Evolution for Social Incidents. In Conference on Information and Knowledge Management (CIKM). 2019. (CCF-B类)

[15] Cheng Wang, Mathias Niepert, and Hui Li. LRMM: Learning to Recommend with Missing Modalities. In Conference on Empirical Methods in Natural Language Processing (EMNLP). 2018. (CCF-B类)

[16] Yanjie Wang, Rainer Gemulla, and Hui Li. On Multi-Relational Link Prediction With Bilinear Models. In AAAI Conference on Artificial Intelligence (AAAI). 2018. (CCF-A类)

[17] Hui Li, Tsz Nam Chan, Man Lung Yiu, and Nikos Mamoulis. FEXIPRO: Fast and Exact Inner Product Retrieval in Recommender Systems. In International Conference on Management of Data (SIGMOD). 2017. (CCF-A类)

[18] Danhao Ding, Hui Li, Zhipeng Huang, and Nikos Mamoulis. Efficient Fault-Tolerant Group Recommendation Using alpha-beta-core. In Conference on Information and Knowledge Management (CIKM). 2017. (CCF-B类)

[19] Ziyu Lu, Hui Li, Nikos Mamoulis, and David W. Cheung. HBGG: a Hierarchical Bayesian Geographical Model for Group Recommendation. In SIAM International Conference on Data Mining (SDM). 2017. (CCF-B类)

[20] Yuqiu Qian, Hui Li, Nikos Mamoulis, Yu Liu, and David W. Cheung. Reverse k-Ranks Queries on Large Graphs. In International Conference on Extending Database Technology (EDBT). 2017. (CCF-B类)

[21] Hui Li, Dingming Wu, and Nikos Mamoulis. A Revisit to Social Network-based Recommender Systems. In International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2014. (CCF-A类)