Information Retrieval

, Volume 9, Issue 4, pp 435–453 | Cite as

Can constrained relevance feedback and display strategies help users retrieve items on mobile devices?

  • Vishwa Vinay
  • Ingemar J. Cox
  • Natasa Milic-Frayling
  • Ken Wood


Searching online information resources using mobile devices is affected by small screens which can display only a fraction of ranked search results. In this paper we investigate whether the search effort can be reduced by means of a simple user feedback: for a screenful of search results the user is encouraged to indicate a single most relevant document. In our approach we exploit the fact that, for small display sizes and limited user actions, we can construct a user decision tree representing all possible outcomes of the user interaction with the system. Examining the trees we can compute an upper limit on relevance feedback performance. In this study we consider three standard feedback algorithms: Rocchio, Robertson/Sparck-Jones (RSJ) and a Bayesian algorithm. We evaluate them in conjunction with two strategies for presenting search results: a document ranking that attempts to maximize information gain from the user’s choices and the top-D ranked documents. Experimental results indicate that for RSJ feedback which involves an explicit feature selection policy, the greedy top-D display is more appropriate. For the other two algorithms, the exploratory display that maximizes information gain produces better results. We conducted a user study to compare the performance of the relevance feedback methods with real users and compare the results with the findings from the tree analysis. This comparison between the simulations and real user behaviour indicates that the Bayesian algorithm, coupled with the sampled display, is the most effective.


Relevance feedback Display strategies Small displays 


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Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • Vishwa Vinay
    • 1
  • Ingemar J. Cox
    • 1
  • Natasa Milic-Frayling
    • 2
  • Ken Wood
    • 2
  1. 1.Department of Computer ScienceUniversity College LondonUK
  2. 2.Microsoft Research Ltd.CambridgeUK

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