Build probabilistic generative models for unifying the analyses of the latent structures and correspondence in human-generated text data and behavior data to get a comprehensive understanding of users' underlying intents. Read More
Organize users' longitudinal information seeking activities into tasks, and develop online learning algorithms to proactively infer users intents and dynamically adapt the systems from interactions with humans for long-term optimality. Read More
Provide meaningful privacy guarantees by obfuscating users' search behaviors via probabilistic generative models, and develop algorithmic methods to evaluate the cost and privacy benefits of different obfuscation techniques. Read More
December 19, 2016
One paper got accepted by WWW 2017 for personalized sentiment analysis with non-parameteric Bayesian clustering.
November 12, 2016
Two papers got accepted by AAAI-2017: one for online collaborative recommendation and one for collaborative sensing.
October 1, 2016
Our project of "Collaborative Sensing: An Approach for Immediately Scalable Sensing in Buildings" in collaboration with Dr. Kamin Whitehouse has been funded by NSF CPS program. More details about this award can be found here.
August 30, 2016
July 12, 2016
May 13, 2016
Lin Gong has been awared for the Presidential Fellowships in Data Science. Congratulations!
December 30, 2015
Hongning Wang has received the NSF Faculty Early Career Development Program (CAREER) Award. More details about this award can be found here.
December 21, 2015
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.