Mining Online User Behavior: From Improving Search to Detecting Cognitive Impairment – Eugene Agichtein (Emory University)
The increasing reach of the Web enables billions of people around the world to create, share, and find information online. The behavior data created by these activities have been a goldmine for improving nearly all aspects of web search and information retrieval, and are now influencing other domains far beyond search. I will first describe how mining document authoring behavior data leads to new, more effective retrieval models. Then, I will show how mining search interaction data, such as mouse cursor movements and scrolling, can be used to model the searcher’s attention and interest at scale, with the precision previously only possible in the lab using eye tracking equipment. This enables dramatic improvements to search ranking, presentation, and search quality evaluation. The resulting techniques can be naturally adapted for other applications requiring measuring user attention. A key example is a test measuring the subject’s visual novelty preference, widely used in psychology and neuroscience to study visual recognition memory. Degraded performance on this test has been linked to cognitive impairment, in particular Alzheimer’s disease. Adapting our techniques allowed us to develop an automatic web-based version of this test, which we are now validating as an accessible and low-cost diagnostic for early detection of Alzheimer’s disease.
Eugene Agichtein is an Associate Professor of Computer Science at Emory University, where he founded and leads the Emory Intelligent Information Access Laboratory (IR Lab). The active projects in IR Lab include mining searcher behavior and interactions data, modelling social content creation and sharing, and applications to medical informatics. Eugene obtained a Ph.D. in Computer Science from Columbia University, and did a Postdoc at Microsoft Research. He has published extensively on web search, information retrieval, and web and data mining. Dr. Agichtein’s work has been supported by DARPA, NIH, NSF, Yahoo!, Microsoft, and Google, and has been recently recognized with the A.P. Sloan Research Fellowship and the “Best Paper” award at the SIGIR 2011 conference.