I'm a PhD student in Computer Science at University of California, San Diego (UCSD). My advisor is Prof. Julian McAuley. Before joining in UCSD, I received my MS degree in Statistics from University of Illinois at Urbana-Champaign in 2015, and my BS degree in Statistics from Peking University in 2013. I was also a student from Yuanpei Program, Peking University.
My research is on data mining and machine learning, especially on developing interpretable, scalable and predictive approaches to model human opinions and behavior from structured and unstructured data.
My research is supported by 2017-2019 Microsoft PhD Fellowship.
Mengting Wan, Julian McAuley, "One-Class Recommendation With Asymmetric Textual Feedback", in Proc. of 2018 SIAM International Conference on Data Mining (SDM'18), San Diego, CA, USA, May 2018.
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Mengting Wan, Di Wang, Matt Goldman, Matt Taddy, Justin Rao, Jie Liu, Dimitrios Lymberopoulos, Julian McAuley, "Modeling Consumer Preferences and Price Sensitivities from Large-Scale Grocery Shopping Transaction Logs", in Proc. of 2017 International World Wide Web Conference (WWW'17), Perth, Australia, Apr. 2017
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Mengting Wan, Julian McAuley, "Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion Question Answering Systems", in Proc. of 2016 IEEE International Conference on Data Mining (ICDM'16), Barcelona, Spain, Dec. 2016
[ paper ] [ data ] [ slides ]
Mengting Wan, Xiangyu Chen, Lance Kaplan, Jiawei Han, Jing Gao, Bo Zhao, "From Truth Discovery to Trustworthy Opinion Discovery: An Uncertainty-Aware Quantitative Modeling Approach", in Proc. of 2016 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16), San Francisco, CA, USA, Aug. 2016
[ paper ] [ poster ] [ code ]
Mengting Wan, Yunbo Ouyang, Lance Kaplan, Jiawei Han, "Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network", in Proc. of 2015 SIAM International Conference on Data Mining (SDM'15), Vancouver, Canada, Apr. 2015.
[ paper ] [ poster ] [ supplementary material ]