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Jaime Teevan, U-M Symposium on Data and Computational Science, 4/23/14

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Published on May 5, 2014

When you visit a colleague's webpage, do the new articles she's posted jump out at you? When you return to your favorite news website, is it easy to find the front page story you saw yesterday? The Web is a dynamic, ever-changing collection of information, and the changes can affect, drive, and interfere with people's information seeking activities. With so much information online, it is now possible to capture and study content evolution and human interaction with evolving content on a scale previously unimaginable. This talk will use large-scale log analysis to explore how and why people revisit Web content that has changed, and illustrate how understanding the association between change and revisitation might improve browser, crawler, and search engine design.

Jaime Teevan is a Senior Researcher at Microsoft Research and an Affiliate Assistant Professor in the Information School at the University of Washington. Working at the intersection of human computer interaction, information retrieval, and social media, she studies and supports people's information seeking activities. Jaime was named a Technology Review (TR35) 2009 Young Innovator for her research on personalized search. She is particularly interested in understanding social and temporal context, co-authoring the first book on collaborative Web search and chairing of the Web Search and Data Mining (WSDM) 2012 conference. Jaime also edited a book on Personal Information Management (PIM), edited a special issue of Communications of the ACM on the topic, and organized workshops on PIM and query log analysis. She has published numerous technical papers, including several best papers, and received a Ph.D. and S.M. from MIT and a B.S. in Computer Science from Yale University.

This talk was delivered April 23, 2014 in Ann Arbor, MI.

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