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I am a Ph.D. student in the Mathematics and Computer Science Department of Emory University, working with Prof. Eugene Agichtein.
My research interests primarily lie in information retrieval, machine learning and user behavior modeling.
As a short summary, my current research explores user behavior modeling of online information-seeking for web search, product search, and library search.
In particular, I investigate machine learning techniques in solving problems such as searcher intent detection, search performance evaluation, and result relevance prediction using search interaction data collected from both large-scale real usage logs and user studies.
Before coming to Emory, I obtained my B.S. degree from Zhejiang University (Hangzhou, China) in 2007. |
Publications
 Beyond Dwell Time: Estimating Document Relevance from Cursor Movements and other Post-click Searcher Behavior
Q. Guo and E. Agichtein
to appear in the 21st International World Wide Web Conference (WWW), 2012.
- Improving Relevance Prediction by Addressing Biases and Sparsity in Web Search Click Data
Q. Guo, D. Lagun, D. Savenkov, and Q. Liu (the first three authors contributed equally)
to appear in the WSDM workshop on Web Search Click Data, 2012.
- Why Searchers Switch: Understanding and Predicting Engine Switching Rationales [slides]
Q. Guo, R. W. White, Y. Zhang, B. Anderson, and S. Dumais
Proceedings of the 34th ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2011.
- Pinch, Zoom, and Slide: Touch Screens Shown Helpful for Detecting Success in Mobile Search
Q. Guo, S. Yuan and E. Agichtein
Proceedings of in the 34th ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2011.
- Find It If You Can: A Game for Modeling Different Types of Web Search Success Using Interaction Data (Best Paper Award)
M. Ageev, Q. Guo, D. Lagun, and E. Agichtein
Proceedings of the 34th ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2011.
- Ready to Buy or Just Browsing? Detecting Web Searcher Goals from Interaction Data
Q. Guo, and E. Agichtein
Proceedings of the 33rd ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2010.
- Exploring Searcher Interactions for Distinguishing Types of Commercial Intent.
Q. Guo, and E. Agichtein
Proceedings of of the 19th International World Wide Web Conference (WWW), 2010.
- Unsupervised Query Segmentation Using Click Data: Preliminary Results.
J. Kiseleva, Q. Guo, E. Agichtein, D. Billsus and W. Chai.
Proceedings of the 19th International World Wide Web Conference (WWW), 2010.
- Predicting Query Performance Using Query, Result, and User Interaction Features.
Q. Guo, R. White, S. Dumais, J. Wang, and B. Anderson
Proceedings of the 9th International Conference on Adaptivity, Personalization and Fusion of Heterogeneous Information (RIAO), 2010.
- Towards Predicting Web Searcher Gaze Position from Mouse Movements.
Q. Guo and E. Agichtein
Proceedings of the 28th ACM Conference on Human Factors in Computing Systems (CHI), 2010.
- Towards Inferring Web Searcher Intent from Behavior Data
E. Agichtein and Q. Guo
Proceedings of the CHI Workshop on Studying Online Behaviour, 2010.
- In the Mood to Click? Towards Inferring Searcher Receptiveness to Advertising
Q. Guo, E. Agichtein, C. Clarke and A. Ashkan
Proceedings of the ACM/IEEE International Conference on Web Intelligence (WI), 2009.
- Estimating Ad Clickthrough Rate through Query Intent Analysis.
A. Ashkan, C. Clarke, E. Agichtein and Q. Guo
Proceedings of the ACM/IEEE International Conference on Web Intelligence (WI), 2009.
- Beyond Session Segmentation: Predicting Changes in
Search Intent With Client-Side User Interactions.
Q. Guo and E. Agichtein
Proceedings of the 32nd ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2009.
- EMU: The Emory User Behavior Modeling System for Automatic Library Search Evaluation: Preliminary Results.
Q. Guo, R. Kelly, S. Deemer, A. Murphy, J. Smith, and E. Agichtein
Proceedings of the 9th Joint Conference on Digital Libraries (JCDL), 2009.
- Classifying and Characterizing Query Intent in Sponsored Search.
A. Ashkan, C. Clarke, E. Agichtein and Q. Guo
Proceedings of the 31st European Conference on Informational Retrieval (ECIR), 2009.
- Understanding "Abandoned" Ads: Towards Personalized Commercial Intent Inference via Mouse Movement Analysis .
Q. Guo, E. Agichtein, C. Clarke and A. Ashkan
Proceedings of the SIGIR Workshop on Information Retrieval in Advertising, 2008.
- Characterizing Query Intent From Ad Clickthrough Data.
A. Ashkan, C. Clarke, E. Agichtein and Q. Guo
Proceedings of the SIGIR Workshop on Information Retrieval in Advertising, 2008.
- Exploring Client-Side Instrumentation for Personalized Search Intent Inference. [slides]
Q. Guo and E. Agichtein
Proceedings of the AAAI Workshop on Intelligent Techniques for Web Personalization & Recommender Systems, 2008.
- Exploring Mouse Movements for Inferring Query Intent .
Q. Guo and E. Agichtein
Proceedings of the 31st ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2008.
- Modeling User Interactions for Automatic Library Search Evaluation: Preliminary Results .
Q. Guo, A. Murphy, S. Deemer and E. Agichtein
submitted to the 8th Joint Conference on Digital Libraries (JCDL), 2008.
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