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刘红岩

管理科学与工程系  教授


电话:  +8610-62789961
电邮:  liuhy@sem.tsinghua.edu.cn
办公室: 伟伦楼 456C
办公室开放时间: 周三上午

Link to English page of Dr. Liu:  http://www.sem.tsinghua.edu.cn/en/liuhy 

 

刘红岩,清华大学经济管理学院管理科学与工程系教授,清华大学博士,博士生导师。主要研究领域为大数据管理与分析、数据/文本挖掘、商务智能、社会网络分析、个性化推荐系统、医疗数据分析、金融数据分析、语音和图像数据分析、计算机视觉及3D点云场景理解等。讲授课程包括数据库原理与应用、商务智能、机器学习及Python应用、数据仓库与数据挖掘、数据结构、C语言、信息管理等。

刘红岩教授在国际学术期刊和国内外学术会议上发表论文近百篇(其中在UTD 24期刊6篇),包括国际顶级及高水平学术期刊如ISRMIS QuarterlyINFORMS Journal on ComputingACM Transactions on Information SystemsACM Transactions on Database SystemsIEEE Transactions on Knowledge and Data EngineeringDecision Support SystemsACM Transactions on Management Information Systems,以及顶级国际学术会议如VLDBIEEE ICDEACM SIGKDDIEEE ICDMSIAM on Data Mining (SDM)WWWACM CIKMICIS等。获得11项国家发明专利授权;主持国家自然科学基金多项以及多项企业研究院和企业合作研究课题,作为主要成员参与国家自然科学基金重大项目、国家自然科学基金创新研究群体项目、国家自然科学基金国际(地区)合作与交流项目等。出版专著《社会计算:用户在线行为分析与挖掘》(清华大学出版社,2014年)、出版国家规划教材《商务智能技术及应用(第二版)》(清华大学出版社,2020年)、《数据库技术及应用》(清华大学出版社,2013年)等。曾获得过多项奖励及荣誉称号,获得国际会议最佳论文奖6次,包括数据挖掘一流国际会议SDMCSWIMADMAWISEKSEMINFORMS Workshop on Data Science等。管理科学与工程学会优秀博士论文指导教师,主持的国家自然科学基金项目《基于数据挖掘的用户网上行为模式的发现技术与应用研究》被基金委评为特优。

曾以合作研究或访问学者身份访问多所国际高校,如美国伊利诺依大学(UIUC)计算机系(20049—200510月)、加州大学戴维斯分校管理学院、香港中文大学系统工程与工程管理系(20112月)、香港科技大学计算机系(20028月)、香港中文大学工学院(20014—6月)、香港中文大学商学院(19998—12月),与国际上多位知名的教授从事合作研究,如国际著名的数据挖掘专家UIUC Jiawei Han教授、国际知名数据库专家Hongjun Lu教授、香港中文大学的Jeffrey X. Yu教授、亚利桑那大学Hsinchun Chen教授以及UC DavisCatherine Yang等。曾担任众多国际会议的程序委员会委员,例如 ICIS Associate Editor, CIKM, PACIS, PAISI, ADMA, APWeb/WAIM, WISE, WISM, CSWIM, CNAISICNC-FSKD等及部分会议的PC Co-chair, Track ChairPanel Chair, 同时担任多个国际高水平学术期刊如Management Science, ISR, MISQ, TKDE, Decision Sciences, INFORMS Journal on Computing, ACM Transactions on Management Information Systems, DSS等国际期刊的审稿人。现为INFORMSACMIEEEAISSIAM等国际学术组织会员,中国计算机学会高级会员、计算机学会数据库专委会委员、中国管理现代化研究会电子商务与网络空间管理专委会副主任。


英文国际期刊论文选列(Selected Journal Papers

[1] Jiawei Chen, Yinghui Yang, Hongyan Liu, Mining Bilateral Reviews: A Relational Topic Modeling Framework for Transaction Success Prediction in Sharing Economy. Information Systems Research. ForthcomingUTD 24期刊)

[2] Shen Liu, Hongyan Liu. Tagging Items Automatically Based on Both Content Information and Browsing Behaviors. INFORMS Journal on Computing (JOC). Forthcoming.UTD 24期刊)

[3] Jiangning He, Xiao Fang, Hongyan Liu. Mobile App Recommendation: An Involvement-Enhanced approach. MIS Quarterly. 2019, 43(3): 827-849. UTD 24期刊)

[4] Yidong Chai, Hongyan Liu, Jie Xu. A New Convolutional Neural Network Model for Peripapillary Atrophy Areas Segmentation from Retinal Fundus Images. Applied Soft ComputingVolume 86, January 2020. 

[5] Jiawei Chen, Hongyan Liu, Yinghui Yang, Jun He. "Effective Selection of a Compact and High-Quality Review Set with Information Preservation. ACM Transactions on Management Information Systems. Volume 10, Issue 4, December 2019, Article No.: 15, pp 1–22. 

[6] Jun H, Hongyan Liu, Yiqing Zheng, Shu Tang, Wei He, Xiaoyong Du. Bi-Labeled LDA: Inferring Interest Tags for Non-Famous Users in Social Network. Data Science and Engineering. Open Access; Published: 29 November 2019

[7] Yidong Chai, Hongyan Liu, Jie Xu. Glaucoma Diagnosis Based on Both Hidden Features and Domain Knowledge through Deep Learning Models. Knowledge-Based Systems. 2018: 147-156.

[8] Jiangning He, Hongyan Liu. Mining Exploratory Behavior to Improve Mobile App Recommendation. ACM Transactions on Information Systems (TOIS). Vol 35, No 4, Article 32. 2017. (SCI, EI)

[9] Jiangning He, Hongyan Liu, Hui Xiong. SocoTraveler: Travel-package Recommendations Leveraging Social Influence of Different Relationship Types. Information & Management. Volume 53, Issue 8, Pages 934-950. (December 2016). (SCI, SSCI, EI)

[10]Jiangning He, Hongyan Liu, Raymond Lau, Jun He. Relationship Identification across heterogeneous online social networks. Computational Intelligence. Volume 33, Issue 3. August 2017. Pages 448-477. (SCI, EI)

[11]Hongyan Liu, Yinghui Yang, Zhuohua Chen, Yong Zheng. A Tree-Based Contrast Set Mining Approach to Detecting Group Differences. INFORMS Journal on ComputingVolume 26 Issue 2, Spring 2014, pp. 208-221.  (SCI, EI) UTD 24期刊)

[12]Jun He, Hongyan Liu, Jeffrey X. Yu, Pei Li, Wei He, Xiaoyong Du. Assessing Single-Pair Similarity over Graphs by Aggregating First-Meeting Probabilities. Information systems. Volume 42, June 2014, Pages 107–122. (SCI, EI) 

[13]Yinghui Yang, Hongyan Liu, and Yuanjue Cai. Discovery of Online Shopping Patterns across Web Sites. INFORMS Journal on Computing.  2013Vol. 25No. 1. pp.161-176. (SCI, EI) UTD 24期刊)

[14]Jun He, Hongyan Liu, Yingqin Gu, Jun Yan, Hong Chen. Scalable and Noise Tolerant Web Knowledge Extraction for Search Task Simplification. Decision Support Systems. Volume 56, December 2013, Pages 156–167. (SCI, EI)

[15]Hongyan Liu, Jun He, Yingqin Gu, Hui Xiong, Xiaoyong Du. Detecting and Tracking Topics and Events from Web Search Logs. ACM Transactions on Information Systems (TOIS). Volume 30 Issue 4, November 2012. Article No. 21.SCI, EI

[16]Hongyan Liu, Jun He, Wenting Song, Tingting Wang. Combining User Preference and User Opinion for Accurate Recommendation. Electronic Commerce Research and Applications (ECRA). Vol. 12, No. 1. 14-23. 2013.SCI, SSCI, EI

[17]Hongyan Liu, Jun He, Dan Zhu, Xiaofeng Ling, Xiaoyong Du. Measuring Similarity Based on Link Information: A Comparative Study. IEEE Transactions on Knowledge and Data Engineering (TKDE). VOL. 25, NO. 12, DECEMBER 2013. 2823-2840 SCI, EI

[18]Yinghui Yang, Balaji Padmanabhan, Hongyan Liu and Xiaoyu Wang. Discovery of Periodic Patterns in Sequence Data: A Variance Based Approach. INFORMS Journal on Computing2012, Vol. 24, No. 3. pp. 372-386. SCI, EIUTD 24期刊)



会议论文选列Refereed Proceedings with high impact

[1] Sun, Qi, Liu, Hongyan, He, Jun, Fan, Zhaoxin, Du, Xiaoyong. DAGC: Employing Dual Attention and Graph Convolution for Point Cloud based Place Recognition. The Annual ACM International Conference on Multimedia Retrieval (ICMR). Dublin, Ireland, 8-11, June, 2020.

[2] Qiyi Wang, Hongyan Liu and Jun He. A Graph Attentive Network Model for P2P Lending Fraud Detection. The 13th International Conference on Knowledge Science, Engineering and Management (KSEM 2020), Hangzhou, China, August 28-30, 2020. (Best paper Runner-up)

[3] Zhaoxin Fan, Hongyan Liu, Jun He, Qi Sun, Xiaoyong Du. A Graph-based One-Shot Learning Method for Point Cloud Recognition. The 28th Pacific Conference on Computer Graphics and Applications (Pacific Graphics 2020), Oct 26, 2020, Wellington, New Zealand. 

[4] Zhaoxin Fan, Hongyan Liu, Jun He, Qi Sun, Xiaoyong Du. SRNet: A 3D Scene Recognition Network using Static Graph and Dense Semantic Fusion. The 28th Pacific Conference on Computer Graphics and Applications (Pacific Graphics 2020), Oct 26, 2020, Wellington, New Zealand. 

[5] Lang Mei, Hongyan Liu, Jun He, Xiaoyong Du. Latent Path Connected Space Model for Recommendation. Apweb-WAIM 2019. August 1-3, 2019, Chengdu, China. 163-172.

[6] Yidong Chai, Weifeng Li, Bin Zhu, Hongyan Liu. "Detecting Fake Reviews in the Cold Start Setting: A Deep Generative Topic Modeling Framework. WITS. 2019.12.18-20. Munich, Germany.

[7] Jiawei Chen, Hongyan Liu, Shiqiang Zheng. Session-Based Learning for Anchor Ranking on Live Streaming Platforms. International Conference on Information Systems (ICIS 2018), 12. 13-16, 2018. San Francisco, CA, USA.

[8] Shen Liu, Hongyan Liu, Exploiting Partial Tag Information for Accurate and Explainable Recommendation, 2018 INFORMS Workshop on Data Science (DS 2018). November 3, Phoenix, Arizona, USA.

[9] Zhuohua Chen, Hongyan Liu,Sanpu Han. Leveraging Community-Level Social Influence and Vocal Competence for Singing-Song Recommendation. 2018 INFORMS Workshop on Data Science (DS 2018). November 3, Phoenix, Arizona, USA. Best Paper Award Runner-Up.

[10]Feifei Li, Hongyan Liu, Jun He, Xiaoyong Du. Attentive and Collaborative Deep Learning for Recommendation. APWeb-WAIM Joint Conference on Web and Big Data. Macau. July 23-25, 2018.

[11]Feifei Li, Hongyan Liu, Jun He, Xiaoyong Du. Exploiting Instance Relationship for Effective Extreme Multi-label Learning. the 3rd International Conference on Database Systems for Advanced Applications (DASFAA18). May 21-24, Gold Coast, Australia.

[12]Shen Liu, Hongyan Liu, Exploiting User Consuming Behavior for Effective Item Tagging. The 26th ACM International Conference on Information and Knowledge Management (CIKM2017). November 6-10, 2017, Singapore. (EI)

[13]Yidong Chai, Hongyan Liu, Li Zhang. Extracting Visual Words from Images for Effective Medical Diagnosis. The 21st Pacific Asia Conference on Information Systems (PACIS2017). July 17-20, Langkawi, Malaysia.  

[14]Luo He, Xiaolei Xie, Hongyan Liu, Bo Li. How Out-of-pocket Ratio Influences Readmission: An Analysis Based on Front Sheet of Inpatient Medical Record. International Conference for Smart Health (ICSH2017), Hong Kong, Jun 26-27. (EI)

[15]Yidong Chai, Luo He, Qiuyan Me, Hongyan Liu, Liang Xu. Deep Learning through Two-branch Convolutional Neuron Network for Glaucoma Diagnosis. International Conference for Smart Health (ICSH2017), Hong Kong, Jun 26-27.2017. (EI)

[16]Lu Huang, Hongyan Liu, Jun He, Xiaoyong Du. Finding Latest Influential Research Papers through Modeling Two Views of Citation Links. The 18th International Asia-Pacific Web Conference (APWeb 2016). Suzhou, China. Sep 23-25. (EI)

[17]Jiangning He, Hongyan Liu, Jun He. Sanpu Han. Individuality or conformity: Recommendation Exploiting Community-level social Influence, PACIS 2016. Taiwan. (EI)

[18]Lu Huang, Hongyan Liu, Jun He, Xiaoyong Du. Finding Latest Influential Research Papers through Modeling Two Views of Citation Links. APWeb 2016. Suzhou, China. Sep 23-25. (EI)

[19]Wei He, Hongyan Liu, Jun He, Shu Tang, Xiaoyong Du. Extracting Interest Tags for Non-famous Users in Social Network. The 24th ACM International Conference on Information and Knowledge Management (CIKM 2015). Oct 19-23, 2015. Melbourne, Australia. (EI)

[20]Yinghui Yang, Zijie Qi, Hongyan Liu and Jun He. Constrained clustering based on the link structure of a directed graph. The 19th Pacific Asia Conference on Information Systems (PACIS 2015). Singapore. July 2015. (EI)

[21]Yinghui Yang, Zijie Qi, Hongyan Liu. Selective Domain Information Acquisition to Improve Segmentation Quality. The 17th International Conference on Electronic Commerce (ICEC 2015). Seoul, Korea, August 2015. (EI)

[22]Yongfang Ma, Yinghui Yang, Hongyan Liu. Competitor Identification based on User Preference and Item attraction. CSWIM 2015. Hefei, China. June, 2015.

[23]Jiawei Chen, Hongyan Liu, Jun He. Predicting the Influence of Group Buying on the Restaurant’s Popularity. The 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'15). 15-17 August 2015. Zhangjiajie, China. (EI)

[24]Shucheng Gong, Hongyan Liu. Constructing Decision Trees for Unstructured Data. The 10th International Conference on Advanced Data Mining and Applications (ADMA 2014). December 19-21, 2014. Guilin, China. (EI)

[25]Zhuohua Chen, Feida Zhu, Guangming Guo, Hongyan Liu. User Profiling via Affinity-aware Friendship Network. The 6th International Conference on Social Informatics (SocInfo 2014). Barcelona, Spain. Nov. 10-13. (EI)

[26]Nana Xu, Hongyan Liu, Jiawei Chen, Jun He, Xiaoyong Du. Selecting a Representative Set of Diverse Quality Reviews Automatically. The 10th SIAM International conference on Data Mining (SDM2014). Philadelphia, USA. April 24-26. (EI)

[27]Tingting Wang, Hongyan Liu, Jun He, Xiaoyong Du. Mining User Interests from Information Sharing Behaviors in Social Media. In Proceeding of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2013). Gold Coast, Australia. April 14-17, 2013. (EI)

[28]Shengyun Sun, Hongyan Liu, Jun He, Xiaoyong Du. Detecting Event Rumors on Sina Weibo Automatically. The 15th International Asia-Pacific Web Conference (APWeb’13). 4-6 April, 2013. Sydney, Australia. (EI)

[29]Ye Li, Tao Liu, Hongyan Liu, Jun He, Xiaoyong Du. Predicting Microblog User’s Age based on Text Information. The 14th international Conference on Web Information System Engineering (WISE 2013). Nanjing, China. Oct 13-15, 2013. (EI) (Best challenge paper award)



中文期刊论文

[1] 龙吟, 刘红岩, 何军, 胡鹤, 杜小勇. 电子商务网站中误导性商品描述识别. 软件学报. 2014, 25(S2):127-135. (EI)

[2] 黄璐, 林川杰, 何军, 刘红岩, 杜小勇. 融合主题模型和协同过滤的多样化移动应用推荐. 软件学报. 2017,28(3):708-720. (EI)

[3] 巩轶凡, 刘红岩, 何军, 岳永姣, 杜小勇. 带有覆盖率机制的文本摘要模型研究. 计算机科学与探索.  2019, 13(2): 205-213. 

[4] 李佳琪, 刘红岩, 何军, 王蓓, 杜小勇. (2018). 应用商城中用户年龄的推断及在推荐中的应用计算机科学与探索. 2018, 12(11), 34-44. 

[5] 严丹, 何军, 刘红岩, 杜小勇. 考虑评级信息的音乐评论文本自动生成[J]. 计算机科学与探索. 2020年第14卷第8, 1389-1396.



已授权国家发明专利

[1] 一种自动拆分英文复合词组的系统和方法 (授权专利号:200910078791.9

[2] 一种在信息检索中基于图中的块结构来计算网页结构图中的链接相似度的系统和方法(授权专利号:200910078788.7

[3] 一种数据库模式重构系统和方法 (授权专利号:200910078789.1

[4] 一种文档相似度衡量方法 (授权专利号:200910078785.3

[5] 一种基于有权图计算文本内容相似度的方法 (授权专利号:200910078787.2

[6] 互联网传播路径图简化方法(授权专利号:201210209515.3

[7] 微博话题标签自动化描述方法(授权专利号:201210209327.0 

[8] 基于地图限定区域的对象查找方法(授权专利号:201210209277.6

[9] 信息推送方法(授权专利号:201210209511.5

[10]兴趣标签生成方法(授权专利号:201510570410.4

[11]商品标签生成方法及装置(授权专利号:201711071583 .7


科研项目

[1] 国家自然科学基金面上项目,71771131考虑心理因素的用户在线行为预测及其在推荐系统中的应用研究2018.1-2021.12,负责人

[2] 企业横向项目,北京密境和风科技有限公司,基于大数据挖掘与机器学习的个性化推荐系统研究,2017.11-2018.11,负责人

[3] 国家自然科学基金面上项目,71272029,通过社会化媒体挖掘用户兴趣的方法及应用研究,2013.1-2016.12,负责人

[4] 企业横向项目,奇智软件(北京)有限公司推荐系统,2015.3-2016.3 负责人。

[5] 国家自然科学基金重大项目,71490720,大数据环境下的商务管理,20151-201912月,成员。

[6] 国家社会科学基金重大项目,13&ZD184, 国家数字档案资源整合与服务机制研究,2013.12-2017.12,子课题三负责人

[7] 国家自然科学基金重点项目,71432004,医疗与健康的数据分析与决策,2015.1-2019.12,成员。

[8] 国家自然科学基金面上项目,70871068,基于数据挖掘的用户网上行为模式的发现技术与应用研究,2009.1-2011.12,负责人 (特优)

[9] 国家自然科学基金重大项目,70890083,新兴电子商务重大基础问题及关键技术研究,2009.1-2012.12,课题三骨干