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Adaptive News Access

  • Daniel Billsus
  • Michael J. Pazzani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4321)

Abstract

This chapter describes how the adaptive web technologies discussed in this book have been applied to news access. First, we provide an overview of different types of adaptivity in the context of news access and identify corresponding algorithms. For each adaptivity type, we briefly discuss representative systems that use the described techniques. Next, we discuss an in-depth case study of a personalized news system. As part of this study, we outline a user modeling approach specifically designed for news personalization, and present results from an evaluation that attempts to quantify the effect of adaptive news access from a user perspective. We conclude by discussing recent trends and novel systems in the adaptive news space.

Keywords

News Story Collaborative Filter Relevant Content News Service News Content 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Daniel Billsus
    • 1
  • Michael J. Pazzani
    • 2
  1. 1.FX Palo Alto Laboratory, 3400 Hillview Ave., Bldg. 4, Palo Alto, CA 94304USA
  2. 2.Rutgers University, ASBIII, 3 Rutgers Plaza, New Brunswick, NJ 08901 

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