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Collaboration, Reputation and Recommender Systems in Social Web Search

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Recommender Systems Handbook

Abstract

Modern web search engines have come to dominate how millions of people find the information that they are looking for online. While the sheer scale and success of the leading search engines is a testimony to the scientific and engineering progress that has been made over the last two decades, mainstream search is not without its challenges. Mainstream search engines continue to provide a largely one-size-fits-all service to their user-base, ultimately limiting the relevance of their result-lists. And they have only very recently begun to consider how the rise of the social web may support novel approaches to search and discovery, or how such signals can be used to inform relevance. In this chapter we will explore recent research which aims to do just that: to make web search a more personal and collaborative experience and to leverage important information such as the reputation of searchers during result-ranking. In short we look towards a more social future for mainstream search.

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Notes

  1. 1.

    The Open Directory Project, http://dmoz.org.

  2. 2.

    http://lucene.apache.org.

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Acknowledgements

This work is supported by Science Foundation Ireland: through the CLARITY Centre for Sensor Web Technologies under grant number 07/CE/I1147; and through the Insight Centre for Data Analytics under grant number SFI/12/RC/2289.

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Authors and Affiliations

  1. Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland

    Barry Smyth, Kevin McNally & Michael P. O’Mahony

  2. HeyStaks Technologies Ltd, NovaUCD, University College Dublin, Dublin, Ireland

    Maurice Coyle & Peter Briggs

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  1. Barry Smyth
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  2. Maurice Coyle
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  5. Michael P. O’Mahony
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Correspondence to Barry Smyth .

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  1. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano - Bozen, Italy

    Francesco Ricci

  2. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Lior Rokach

  3. Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Bracha Shapira

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Smyth, B., Coyle, M., Briggs, P., McNally, K., O’Mahony, M.P. (2015). Collaboration, Reputation and Recommender Systems in Social Web Search. In: Ricci, F., Rokach, L., Shapira, B. (eds) Recommender Systems Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7637-6_17

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