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Coping with Noisy Search Experiences

  • Pierre-Antoine Champin
  • Peter Briggs
  • Maurice Coyle
  • Barry Smyth
Conference paper

Abstract

The so-called Social Web has helped to change the very nature of the Internet by emphasising the role of our online experiences as new forms of content and service knowledge. In this paper we describe an approach to improving mainstream Web search by harnessing the search experiences of groups of like-minded searchers.We focus on the HeyStaks system (www.heystaks.com) and look in particular at the experiential knowledge that drives its search recommendations. Specifically we describe how this knowledge can be noisy, and we describe and evaluate a recommendation technique for coping with this noise and discuss how it may be incorporated into HeyStaks as a useful feature.

Keywords

Recommender System Search Experience Popularity Measure Weighted Accuracy Recommendation Knowledge 
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-Verlag London 2010

Authors and Affiliations

  • Pierre-Antoine Champin
    • 1
  • Peter Briggs
    • 2
  • Maurice Coyle
    • 2
  • Barry Smyth
    • 2
  1. 1.LIRIS, Université de Lyon, CNRS, UMR5205, Université Claude Bernard Lyon 1VilleurbanneFrance
  2. 2.CLARITY: Centre for Sensor Web Technologies School of Computer Science and InformaticsUniversity College DublinDublinIreland

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