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How Relevant is the Long Tail?

A Relevance Assessment Study on Million Short

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Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9822))

Abstract

Users of web search engines are known to mostly focus on the top ranked results of the search engine result page. While many studies support this well known information seeking pattern only few studies concentrate on the question what users are missing by neglecting lower ranked results. To learn more about the relevance distributions in the so-called long tail we conducted a relevance assessment study with the Million Short long-tail web search engine. While we see a clear difference in the content between the head and the tail of the search engine result list we see no statistical significant differences in the binary relevance judgments and weak significant differences when using graded relevance. The tail contains different but still valuable results. We argue that the long tail can be a rich source for the diversification of web search engine result lists but it needs more evaluation to clearly describe the differences.

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Notes

  1. 1.

    https://millionshort.com/about.html.

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Correspondence to Philipp Schaer .

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Schaer, P., Mayr, P., Sünkler, S., Lewandowski, D. (2016). How Relevant is the Long Tail?. In: Fuhr, N., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2016. Lecture Notes in Computer Science(), vol 9822. Springer, Cham. https://doi.org/10.1007/978-3-319-44564-9_20

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  • DOI: https://doi.org/10.1007/978-3-319-44564-9_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44563-2

  • Online ISBN: 978-3-319-44564-9

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