Models of searching and browsing: languages, studies, and applications

  • Authors:
  • Doug Downey;Susan Dumais;Eric Horvitz

  • Affiliations:
  • Department of Computer Science and Engineering, University of Washington, Seattle, WA;Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA

  • Venue:
  • IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
  • Year:
  • 2007

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Abstract

We describe the formulation, construction, and evaluation of predictive models of human information seeking from a large dataset of Web search activities. We first introduce an expressive language for describing searching and browsing behavior, and use this language to characterize several prior studies of search behavior. Then, we focus on the construction of predictive models from the data. We review several analyses, including an exploration of the properties of users, queries, and search sessions that are most predictive of future behavior. We also investigate the influence of temporal delay on user actions, and representational tradeoffs with varying the number of steps of user activity considered. Finally, we discuss applications of the predictive models, and focus on the example of performing principled prefetching of content.