Selected Recent Publications

ChengXiang Zhai


  • Shubhra Kanti Karmaker Santu, Liangda Li, Dae Hoon Park, Chengxiang Zhai, Yi Chang, Modeling the Influence of Popular Trending Events on User Search Behavior, Proceedings of WWW 2017 , to appear.

  • Xueqing Liu, Chengxiang Zhai, Wei Han, Onur Gungor, Numerical Range Facets Partition: Evaluation Metric and Methods, Proceedings of WWW 2017. To appear.

  • Xiaolong Wang, Jingjing Wang, Chengxiang Zhai. Dual-Clustering Maximum Entropy with Application to Classification and Word Embedding. In Proceedings of the 31st AAAI conference on Artificial Intelligence, 2017, to appear.

  • Chase Geigle and Chengxiang Zhai, Modeling MOOC Student Behavior With Two-Layer Hidden Markov Models. Proceedings of ACM Learning at Scale 2017. to appear.

  • Sheng Wang, Edward Huang, Runshun Zhang, Xiaoping Zhang, Baoyan Liu, Xuezhong Zhou, ChengXiang Zhai. A Conditional Probabilistic Model for Joint Analysis of Symptoms, Diagnoses, and Herbs in Traditional Chinese Medicine Patient Records. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017, to appear.

  • Sendong Zhao, Quan Wang, Sean Massung, Ting Liu, and ChengXiang Zhai. Constructing and Embedding Abstract Event Causality Networks from Text Snippets, Proceedings of WSDM 2017. To appear.


  • ChengXiang Zhai: Towards a game-theoretic framework for text data retrieval. IEEE Data Eng. Bull. 39(3): 51-62 (2016).

  • Xiaolong Wang, Jingjing Wang, Jie Luo, Chengxiang Zhai, Yi Chang. Blind Men and The Elephant Thurstonian Pairwise Preference for Ranking in Crowdsourcing, Proceedings of ICDM 2016

  • Rongda Zhu, Aston Zhang, Jian Peng, and Chengxiang Zhai, Exploiting Temporal Divergence of Topic Distributions for Event Detection, Proceedings of IEEE BigData 2016

  • Edward W Huang, Sheng Wang, Runshun Zhang, Baoyan Liu, Xuezhong Zhou, ChengXiang Zhai. PaReCat: Patient Record Subcategorization for Precision Traditional Chinese Medicine. Proceedings of ACM BCB 2016, Oct. 2016.

  • Shubhra Kanti Karmaker Santu, Parikshit Sondhi and ChengXiang Zhai. Generative Feature Language Models for Mining Implicit Features from Customer Reviews. Proceedings of ACM CIKM 2016

  • Dae Hoon Park, Yi Fang, Mengwen Liu, ChengXiang Zhai: Mobile App Retrieval for Social Media Users via Inference of Implicit Intent in Social Media Text. Proceedings of ACM CIKM 2016. pp. 959-968.

  • Shengwen Peng, Ronghui You, Hongning Wang, Chengxiang Zhai, Hiroshi Mamitsuka, Shanfeng Zhu: DeepMeSH: deep semantic representation for improving large-scale MeSH indexing. Bioinformatics 32(12): 70-79 (2016)

  • Martin Leginus, ChengXiang Zhai, Peter Dolog: Personalized generation of word clouds from tweets. JASIST 67(5): 1021-1032 (2016)

  • Chase Geigle, ChengXiang Zhai: Scaling up Online Question Answering via Similar Question Retrieval. ACM Learning at Scale 2016: pp. 257-260, 2016.

  • Chase Geigle, ChengXiang Zhai, Duncan C. Ferguson: An Exploration of Automated Grading of Complex Assignments. ACM Learning at Scale 2016: pp. 351-360, 2016.

  • Yinan Zhang, ChengXiang Zhai: A Sequential Decision Formulation of the Interface Card Model for Interactive IR. Proceedings of ACM SIGIR 2016: pp.85-94, 2016.

  • Shan Jiang, Yuening Hu, Changsung Kang, Tim Daly Jr., Dawei Yin, Yi Chang, ChengXiang Zhai: Learning Query and Document Relevance from a Web-scale Click Graph. Proceedings of ACM SIGIR 2016: pp. 185-194, 2016.

  • Sean Massung, ChengXiang Zhai, Non-Native Text Analysis: A Survey, Natural Language Engineering, Volume 22, Issue 2 March 2016, pp. 163-186.


  • Thomas Zhang, Jason H. D. Cho, Chengxiang Zhai: Understanding User Intents in Online Health Forums. IEEE J. Biomedical and Health Informatics 19(4): 1392-1398 (2015)

  • Martin Leginus, ChengXiang Zhai, Peter Dolog: Beomap: Ad Hoc Topic Maps for Enhanced Exploration of Social Media Data. ICWE 2015: pp. 200-218, 2015.

  • Huizhong Duan, ChengXiang Zhai: Mining Coordinated Intent Representation for Entity Search and Recommendation. CIKM 2015: pp. 333-342, 2015.

  • Ismini Lourentzou, Graham Dyer, Abhishek Sharma, ChengXiang Zhai: Hotspots of news articles: Joint mining of news text & social media to discover controversial points in news. Big Data 2015: pp. 2948-2950, 2015.

  • Jason H. D. Cho, Yanen Li, Roxana Girju, Chengxiang Zhai: Recommending forum posts to designated experts. Big Data 2015: pp. 659-666, 2015.

  • Sean Massung, ChengXiang Zhai: SyntacticDiff: Operator-based transformation for comparative text mining. Big Data 2015: pp. 571-580, 2015.

  • Ke Liu, Shengwen Peng, Junqiu Wu, ChengXiang Zhai, Hiroshi Mamitsuka, Shanfeng Zhu: MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence. Bioinformatics 31(12): 339-347 (2015)

  • Sheng Wang, Hyunghoon Cho, ChengXiang Zhai, Bonnie Berger, Jian Peng: Exploiting ontology graph for predicting sparsely annotated gene function. Bioinformatics 31(12): 357-364 (2015)

  • Yuanhua Lv, ChengXiang Zhai: Negative query generation: bridging the gap between query likelihood retrieval models and relevance. Inf. Retr. Journal 18(4): 359-378 (2015)

  • Kavita Ganesan, ChengXiang Zhai: OpinoFetch: a practical and efficient approach to collecting opinions on arbitrary entities. Inf. Retr. Journal 18(6): 530-558 (2015)

  • V. G. Vinod Vydiswaran, ChengXiang Zhai, Dan Roth, Peter Pirolli: Overcoming bias to learn about controversial topics. JASIST 66(8): 1655-1672 (2015)

  • Hussein Hazimeh, ChengXiang Zhai, Axiomatic Analysis of Smoothing Methods in Language Models for Pseudo-Relevance Feedback, Proceedings of ACM SIGIR ICTIR 2015, pp. 141-150, 2015.

  • Yinan Zhang, ChengXiang Zhai, Information Retrieval as Card Playing: A Formal Model for Optimizing Interactive Retrieval Interface, Proceedings of ACM SIGIR 2015, pp. 685-694, 2015.

  • Dae Hoon Park, Hyun Duk Kim, ChengXiang Zhai, Lifan Guo, Retrieval of Relevant Opinion Sentences for New Products, Proceedings of ACM SIGIR 2015, pp. 393-402, 2015.

  • Dae Hoon Park, Mengwen Liu, ChengXiang Zhai, A Study of Retrieval Models for Mobile App Retrieval, Proceedings of ACM SIGIR 2015, pp. 533-542, 2015.

  • Mingjie Qian, ChengXiang Zhai, Joint Adaptive Loss and L2/L0-norm Minimization for Unsupervised Feature Selection, Proceedings of IJCNN 2015 , pp. 1-8, 2015.

  • DaeHoon Park, ChengXiang Zhai, Lifan Guo, SpecLDA: Modeling Product Reviews and Specifications to Generate Augmented Specifications, Proceedings of 2015 SIAM International Conference on Data Mining (SDM'15), pp. 837-845, 2015.