Jaime Teevan, Ph.D.
Blog, Twitter: @jteevan
One Microsoft Way
Redmond, WA 98052
(425) 421-9299
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Jaime's research explores how context can help people use digital information successfully, both from an algorithmic perspective and from an interaction perspective. The types of context she has studied include:

Social Context People are valuable information resources, providing content and perspectives that may not be available by other means. This value can be captured algorithmically (e.g., personalization using social context) or via social interaction (e.g., digitally-mediated question asking). Social context is particularly interesting in a mobile context, since mobile devices are often present during people’s social interactions. (See publications: social search, mobile search)
Temporal Context What has happened in the past can provide valuable insight into a person's current information interactions. Content changes over time, as does the way people interact with that content. Jaime works to characterize information dynamics, and build and study tools that use change to their advantage. (See publications: dynamic information environments)
Personal Context Much of Jaime's research focuses on personalized search. For example, when a friend searches for Jaime's name, they probably want to find content related to her family or shared interests, whereas her colleagues probably want to find her publications and technical references. It is possible to disambiguate these two cases by looking at the language the searcher uses in other contexts. Jaime's work colleagues are likely to have used the terms “information retrieval”, “collaborative search”, and “personalization” before, so their search results can be biased towards relevant results that contain those terms. (See publications: personal search, re-finding)

For more information, please see Jaime's complete list of publications.

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