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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
References
Hariri, N.: Relevance ranking on Google: are top ranked results really considered more relevant by the users? Online Inf. Rev. 35(4), 598–610 (2011)
Hosseini, M., Cox, I.J., Milić-Frayling, N., Kazai, G., Vinay, V.: On aggregating labels from multiple crowd workers to infer relevance of documents. In: Baeza-Yates, R., Vries, A.P., Zaragoza, H., Cambazoglu, B.B., Murdock, V., Lempel, R., Silvestri, F. (eds.) ECIR 2012. LNCS, vol. 7224, pp. 182–194. Springer, Heidelberg (2012)
Lewandowski, D., Sünkler, S.: Designing search engine retrieval effectiveness tests with RAT. Inf. Serv. Use 33(1), 53–59 (2013)
Schaer, P.: Better than their reputation? On the reliability of relevance assessments with students. In: Catarci, T., Forner, P., Hiemstra, D., Peñas, A., Santucci, G. (eds.) CLEF 2012. LNCS, vol. 7488, pp. 124–135. Springer, Heidelberg (2012)
Sterling, G.: iProspect: blended search resulting in more clicks on news, images, and video (2008). http://searchengineland.com/iprospect-blended-search-resulting-in-more-clicks-on-news-images-and-video-13708
Zaragoza, H., Cambazoglu, B.B., Baeza-Yates, R.: Web search solved?: all result rankings the same? In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, CIKM 2010, pp. 529–538. ACM, New York (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-44564-9_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44563-2
Online ISBN: 978-3-319-44564-9
eBook Packages: Computer ScienceComputer Science (R0)