[Ml-stat-talks] susan dumais, tuesday november 6, 4:30pm

David Blei blei at CS.Princeton.EDU
Sat Nov 2 07:05:32 EDT 2013


throughout her long career, susan dumais has made a major impact on
some of the most important problems in information retrieval.  she is
speaking next tuesday at 4:30pm.  the abstract is below.

this is not to be missed, especially for those interested in machine
learning, information retrieval, natural language processing, and web



Temporal Dynamics and Information Retrieval
Susan Dumais, Microsoft Research
Tuesday, November 5 4:30pm
Friend Center 006

Many digital resources, like the Web, are dynamic and ever-changing
collections of information. However, most tools developed for
interacting with Web content, such as browsers and search engines,
focus on a single static snapshot of the information. In this talk, I
will present analyses characterizing how Web content changes over
time, how people re-visit Web pages over time, and how re-visitation
patterns are influenced by changes in user intent and content. These
results have implications for many aspects of information management
including crawling policy, ranking and information extraction
algorithms, result presentation, and system evaluation. I will
describe a prototype that supports people in understanding how the
information they interact with changes over time, and new information
retrieval models that incorporate the temporal dynamics to improve
ranking. Finally, I will conclude with speculations about "slow
search" and an overview of challenges that need to be addressed to
fully incorporate temporal dynamics into information systems.

Susan Dumais is a Distinguished Scientist and manager of the Context,
Learning and User Experience for Search (CLUES) Group at Microsoft
Research. Prior to joining Microsoft Research, she was at Bell Labs
and Bellcore for many years, where she worked on Latent Semantic
Analysis, interfaces for combining search and navigation, and
organizational impacts of new technology. Her current research focuses
on user modeling and personalization, context and search, temporal
dynamics of information, and novel evaluation methods. She has worked
closely with several Microsoft groups (Bing, Windows Desktop Search,
SharePoint, and Office Online Help) on search-related innovations.
Susan has published widely in the fields of information science,
human-computer interaction and cognitive science, and holds several
patents on novel retrieval algorithms and interfaces. Susan is an
adjunct professor in the Information School at the University of
Washington. She is Past-Chair of ACM's Special Interest Group in
Information Retrieval (SIGIR), and serves on several editorial boards,
technical program committees, and government panels. She was elected
to the CHI Academy in 2005, an ACM Fellow in 2006, received the SIGIR
Gerard Salton Award for Lifetime Achievement in 2009, and was elected
to the National Academy of Engineering (NAE) in 2011. More information
is available at her

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