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.
%0 Conference Paper
%1 schaer_how_2016-1
%A Schaer, Philipp
%A Mayr, Philipp
%A Sünkler, Sebastian
%A Lewandowski, Dirk
%B Experimental IR Meets Multilinguality, Multimodality, and Interaction
%C Cham
%D 2016
%E Fuhr, Norbert
%E Quaresma, Paulo
%E Gonçalves, Teresa
%E Larsen, Birger
%E Balog, Krisztian
%E Macdonald, Craig
%E Cappellato, Linda
%E Ferro, Nicola
%I Springer International Publishing
%K information_retrieval
%P 227--233
%R 10.1007/978-3-319-44564-9_20
%T How relevant is the long tail?
%X 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.
%@ 978-3-319-44564-9
@inproceedings{schaer_how_2016-1,
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.},
added-at = {2023-01-14T15:28:29.000+0100},
address = {Cham},
author = {Schaer, Philipp and Mayr, Philipp and Sünkler, Sebastian and Lewandowski, Dirk},
biburl = {https://www.bibsonomy.org/bibtex/2878cde14dde898be3cbd932255f9c017/lepsky},
booktitle = {Experimental {IR} {Meets} {Multilinguality}, {Multimodality}, and {Interaction}},
doi = {10.1007/978-3-319-44564-9_20},
editor = {Fuhr, Norbert and Quaresma, Paulo and Gonçalves, Teresa and Larsen, Birger and Balog, Krisztian and Macdonald, Craig and Cappellato, Linda and Ferro, Nicola},
interhash = {28ec949f6d58d36c4447d96e0e7bdae8},
intrahash = {878cde14dde898be3cbd932255f9c017},
isbn = {978-3-319-44564-9},
keywords = {information_retrieval},
language = {en},
pages = {227--233},
publisher = {Springer International Publishing},
series = {Lecture {Notes} in {Computer} {Science}},
timestamp = {2023-01-14T15:35:37.000+0100},
title = {How relevant is the long tail?},
year = 2016
}