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Adaptive News Access

  • Chapter
The Adaptive Web

Part of the book series: Lecture Notes in Computer Science ((LNISA,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.

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Author information

Authors and Affiliations

  1. FX Palo Alto Laboratory, 3400 Hillview Ave., Bldg. 4, Palo Alto, CA 94304, USA

    Daniel Billsus

  2. Rutgers University, ASBIII, 3 Rutgers Plaza, New Brunswick, NJ 08901,  

    Michael J. Pazzani

Authors
  1. Daniel Billsus
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  2. Michael J. Pazzani
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Peter Brusilovsky Alfred Kobsa Wolfgang Nejdl

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Billsus, D., Pazzani, M.J. (2007). Adaptive News Access. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds) The Adaptive Web. Lecture Notes in Computer Science, vol 4321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72079-9_18

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  • DOI: https://doi.org/10.1007/978-3-540-72079-9_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72078-2

  • Online ISBN: 978-3-540-72079-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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