Hongning Wang

Assistant Professor of Computer Science

Office: Rice Hall, Room 408

Phone: 434-982-2228

Email: hw5x-at-virginia-dot-edu

I am an assistant professor in the Department of Computer Science of University of Virginia. My research interest includes data mining, machine learning, and information retrieval, with a special emphasis on computational user behavior modeling. I graduated from the CS@UIUC in May 2014. Our group homepage is at HCDM@UVa.

News

  • Our group homepage is now available at HCDM@UVa.

  • Our proposal of "Collaborative Sensing: An Approach for Immediately Scalable Sensing in Buildings" has been funded by NSF CPS program. More details about this award can be found here.

  • Our proposal of "Collaborative Learning with Incomplete and Noisy Knowledge" has been funded by NSF III program. More details about this award can be found here.

  • I gave an invitated talk about "Collaborative Online Learning" at Yahoo Search Science Team.

  • I have received the NSF Faculty Early Career Development Program (CAREER) Award. More details about this award can be found here.

  • Our proposal of "Call for Special Issue on Search, Mining and their Applications on Mobile Devices" has been accepted by the ACM Transactions on Information Systems (TOIS). Call for papers will be announced shortly.

  • I gave an invitated talk about "Human-centric big data mining" at Center for Embedded Systems for Critical Applications (CESCA) in the Department of Electrical and Computer Engineering at Virginia Tech.

  • I gave an invitated talk about "Human-centric big data mining" in Quantitative Psychology Group in the Department of Psychology at UVa.

  • My research is reported on UVa Today.

  • The course website for CS6501 Text Mining has been deployed.

  • I was selected for the WSDM 2015 Outstanding Reviewer Award.

  • I have position opennings for Ph.D. students for Fall 2015. If you are self-motivated and want to pursue a Ph.D. degree in the areas of data mining and information retrieval, please contact me. More information about the graduate admission at CS@UVa can be found here. Please note the application deadline is December 15th, 2014.

  • I am going to offer CS6501: Text Mining next Spring semester.

  • I am offering CS6501: Information Retrieval this Fall semester.

  • I joined CS@UVa as an assistant professor.


Award and Honor


Invited Talks


Academic Activities


Publications

[Google Scholar] [DBLP]
  1. Lin Gong, Benjamin Haines and Hongning Wang. Clustered Model Adaptation for Personalized Sentiment Analysis. The 26th International World Wide Web Conference (WWW 2017). (to appear)
  2. Sarah Masud Preum, Abu Sayeed Mondol, Meiyi Ma, Hongning Wang and John A. Stankovic. Preclude: Conflict Detection in Textual Health Advice. The 15th IEEE International Conference on Pervasive Computing and Communications (PerCom 2017). (to appear)
  3. Huazheng Wang, Qingyun Wu and Hongning Wang. Factorization Bandits for Interactive Recommendation. The Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017). (to appear)
  4. Nipun Batra, Hongning Wang, Amarjeet Singh and Kamin Whitehouse. Matrix Factorisation for Scalable Energy Breakdown. The Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017). (to appear)
  5. Huazheng Wang, Qingyun Wu and Hongning Wang. Learning Hidden Features for Contextual Bandits. The 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), p1633-1642, 2016. (PDF, code)
  6. Lin Gong, Mohammad Al Boni and Hongning Wang. Modeling Social Norms Evolution for Personalized Sentiment Classification. The 54th Annual Meeting of the Association for Computational Linguistics (ACL'2016), p855-865, 2016. (PDF, code)
  7. Qingyun Wu, Huazheng Wang, Quanquan Gu and Hongning Wang. Contextual Bandits in A Collaborative Environment. The 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2016), p529-538, 2016. (PDF, Slides, code)
  8. Wasi Ahmad, Md Masudur Rahman and Hongning Wang. Topic Model based Privacy Protection in Personalized Web Search. The 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2016), p1025-1028, 2016. (PDF)
  9. Shengwen Peng, Ronghui You, Hongning Wang, Chengxiang Zhai, Hiroshi Mamitsuka and Shanfeng Zhu. DeepMeSH: Deep Semantic Representation for Improving Large-scale MeSH Indexing. The 23th Intelligent Systems for Molecular Biology (ISMB'2016), p70-79, 2016. (PDF)
  10. Md Mustafizur Rahman and Hongning Wang. Hidden Topic Sentiment Model. The 25th International World-Wide Web Conference (WWW'2016), p155-165, 2016. (PDF, Slides)
  11. Peilin Yang, Hongning Wang, Hui Fang and Deng Cai. Opinions matter: a general approach to user profile modeling for contextual suggestion. Information Retrieval Journal, pp 1-25, DOI 10.1007/s10791-015-9278-7. (Link)
  12. Dezhi Hong, Hongning Wang, Jorge Ortiz and Kamin Whitehouse. The Building Adapter: Towards Quickly Applying Building Analytics at Scale. ACM BuildSys 2015, p123-132, 2015. (Best Paper Candidate) (PDF, slides)
  13. Asif Salekin, Hongning Wang and John Stankovic. KinVocal: Detecting Agitated Vocal Events. The 13th ACM Conference on Embedded Networked Sensor Systems (SenSys 2015), p459-460, 2015. (PDF)
  14. Dezhi Hong, Hongning Wang and Kamin Whitehouse. Clustering-based Active Learning on Sensor Type Classification in Buildings. The 24th ACM International Conference on Information and Knowledge Management (CIKM'2015), p363-372, 2015. (PDF, slides)
  15. Mohammad Al Boni, Keira Qi Zhou, Hongning Wang and Matthew S. Gerber. Model Adaptation for Personalized Opinion Analysis. The 53th Annual Meeting of the Association for Computational Linguistics (ACL'2015), p769-774, 2015. (PDF)
  16. Hongning Wang, Yang Song, Ming-Wei Chang, Xiaodong He, Ahmed Hassan and Ryen White. Modeling Action-level Satisfaction for Search Task Satisfaction Prediction. The 37th Annual ACM SIGIR Conference (SIGIR'2014), p123-132, 2014. (PDF, slides)
  17. Yanen Li, Anlei Dong, Hongning Wang, Hongbo Deng, Yi Chang and ChengXiang Zhai. A Two-dimensional Click Model for Query Auto-completion. The 37th Annual ACM SIGIR Conference (SIGIR'2014), p455-464, 2014. (PDF, slides)
  18. Hongning Wang, Anlei Dong and Yi Chang. Joint Learning Approach from Clickthroughs, book chapter in Bo Long and Yi Chang (eds), Relevance Ranking for Vertical Search Engines, Morgan Kaufmann Publisher, 2014, p10-26.
  19. Hongning Wang, ChengXiang Zhai, Feng Liang, Anlei Dong and Yi Chang. User Modeling in Search Logs via A Nonparametric Bayesian Approach. The 7th ACM Web Search and Data Mining Conference (WSDM'2014), p203-212, 2014. (PDF, slides)
  20. Yang Song, Hongning Wang and Xiaodong He. Adapting Deep RankNet for Personalized Search. The 7th ACM Web Search and Data Mining Conference (WSDM'2014), p83-92, 2014. (PDF, slides)
  21. Hongning Wang, Xiaodong He, Ming-Wei Chang, Yang Song, Ryen White and Wei Chu. Personalized Ranking Model Adaptation for Web Search. The 36th Annual ACM SIGIR Conference (SIGIR'2013), p323-332, 2013. (PDF, slides)
  22. Hongning Wang, ChengXiang Zhai, Anlei Dong and Yi Chang. Content-Aware Click Modeling. The 23rd International World-Wide Web Conference (WWW'2013), p1365-1376, 2013. (PDF, slides, codes)
  23. Hongning Wang, Yang Song, Ming-Wei Chang, Xiaodong He, Ryen White and Wei Chu. Learning to Extract Cross-Session Search Tasks. The 23rd International World-Wide Web Conference (WWW'2013), p1353-1364, 2013. (PDF, slides)
  24. Yang Song, Hao Ma, Hongning Wang and Kuansan Wang. Exploring and Exploiting User Search Behaviors on Mobile and Tablet Devices to Improve Search Relevance. The 23rd International World-Wide Web Conference (WWW'2013), p1201-1212, 2013. (PDF)
  25. Ryen White, Wei Chu, Ahmed Hassan, Xiaodong He, Yang Song and Hongning Wang. Enhancing Personalized Search by Mining and Modeling Task Behavior. The 23rd International World-Wide Web Conference (WWW'2013), p1411-1420, 2013. (PDF)
  26. Chi Wang, Hongning Wang, Jialu Liu, Ming Ji, Lu Su, Yuguo Chen, Jiawei Han. On the Detectability of Node Grouping in Networks. SIAM International Conference on Data Mining (SDM'2013), p713-721, 2013.
  27. Hongbo Deng, Jiawei Han, Hao Li, Heng Ji, Hongning Wang and Yue Lu. Exploring and Inferring User-User Pseudo-Friendship for Sentiment Analysis with Heterogeneous Networks. SIAM International Conference on Data Mining (SDM'2013), p378-386, 2013.
  28. Mianwei Zhou, Hongning Wang and Kevin Chen-Chuan Chang. Learning to Rank from Distant Supervision: Exploiting Noisy Redundancy for Relational Entity Search. The 29th IEEE International Conference on Data Engineering (ICDE'2013)
  29. Yue Lu, Hongning Wang, ChengXiang Zhai and Dan Roth. Unsupervised Discovery of Opposing Opinion Networks From Forum Discussions. The 21st ACM International Conference on Information and Knowledge Management (CIKM'2012), p1642-1646, 2012. (PDF)
  30. Hongning Wang, Anlei Dong, Lihong Li, Yi Chang and Evgeniy Gabrilovich. Joint Relevance and Freshness Learning From Clickthroughs for News Search. The 2012 World Wide Web Conference (WWW'2012), p579-588, 2012. (PDF, slides)
  31. Hongning Wang, Yue Lu and ChengXiang Zhai. Latent Aspect Rating Analysis without Aspect Keyword Supervision. The 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2011), P618-626, 2011. (PDF, slides, Demo)
  32. Hongning Wang, Chi Wang, ChengXiang Zhai and Jiawei Han. Learning Online Discussion Structures by Conditional Random Fields. The 34th Annual International ACM SIGIR Conference (SIGIR'2011), P435-444, 2011. (PDF, slides, codes)
  33. Hongning Wang, Duo Zhang and ChengXiang Zhai. Structural Topic Model for Latent Topical Structure Analysis. The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL HTL'2011), P1526-1535, 2011. (PDF, codes)
  34. Yue Lu, Huizhong Duan, Hongning Wang and ChengXiang Zhai. Exploiting Structured Ontology to Organize Scattered Online Opinions. The 23rd International Conference on Computational Linguistics (COLING'2010) P734--742, 2010. (PDF)
  35. Hongning Wang, Yue Lu and Chengxiang Zhai. Latent Aspect Rating Analysis on Review Text Data: A Rating Regression Approach. The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2010), p783-792, 2010. (PDF, slides, Demo, codes)
  36. Hongning Wang, Minlie Huang and Xiaoyan Zhu. Extract Interaction Detection Methods from the Biological Literature. BMC Bioinformatics 2009, 10(Suppl 1):S55. (PDF)
  37. Hongning Wang, Minlie Huang and Xiaoyan Zhu. A Generative Probabilistic Model for Multi-Label Classification. In Proceedings of the IEEE 8th International Conference on Data Mining (IEEE ICDM 2008), p628-637, 2008. (PDF)
  38. Hongning Wang, Minlie Huang, Shilin Ding and Xiaoyan Zhu. Exploiting and Integrating Rich Features for Biological Literature Classification. BMC Bioinformatics. 2008; 9(Suppl 3): S4. (PDF)
  39. Minlie Huang, Shilin Ding, Hongning Wang and Xiaoyan Zhu. Mining Physical Protein-protein Interactions from Literature. Genome Biology 2008, 9(Suppl 2):S12. (PDF);