A Comparison of Social Bookmarking with Traditional Search
B. Krause, A. Hotho, and G. Stumme. Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008, 4956, page 101-113. Springer, (2008)
Abstract
Social bookmarking systems allow users to store links to internet
resources on a web page. As social bookmarking systems are growing
in popularity, search algorithms have been developed that transfer the idea
of link-based rankings in the Web to a social bookmarking system’s data
structure. These rankings differ from traditional search engine rankings in
that they incorporate the rating of users.
In this study, we compare search in social bookmarking systems with traditional
Web search. In the first part, we compare the user activity and
behaviour in both kinds of systems, as well as the overlap of the underlying
sets of URLs. In the second part, we compare graph-based and vector
space rankings for social bookmarking systems with commercial search engine
rankings.
Our experiments are performed on data of the social bookmarking system
Del.icio.us and on rankings and log data from Google, MSN, and AOL. We
will show that part of the difference between the systems is due to different
behaviour (e. g., the concatenation of multi-word lexems to single terms
in Del.icio.us), and that real-world events may trigger similar behaviour
in both kinds of systems. We will also show that a graph-based ranking
approach on folksonomies yields results that are closer to the rankings of
the commercial search engines than vector space retrieval, and that the
correlation is high in particular for the domains that are well covered by
the social bookmarking system.
%0 Conference Paper
%1 paper:krause:2008a
%A Krause, Beate
%A Hotho, Andreas
%A Stumme, Gerd
%B Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008
%D 2008
%I Springer
%K 2008 bookmarking del.icio.us folksonomy log search search-engines social tags
%P 101-113
%T A Comparison of Social Bookmarking with Traditional Search
%U http://www.kde.cs.uni-kassel.de/hotho/pub/2008/ecir2008krause.pdf
%V 4956
%X Social bookmarking systems allow users to store links to internet
resources on a web page. As social bookmarking systems are growing
in popularity, search algorithms have been developed that transfer the idea
of link-based rankings in the Web to a social bookmarking system’s data
structure. These rankings differ from traditional search engine rankings in
that they incorporate the rating of users.
In this study, we compare search in social bookmarking systems with traditional
Web search. In the first part, we compare the user activity and
behaviour in both kinds of systems, as well as the overlap of the underlying
sets of URLs. In the second part, we compare graph-based and vector
space rankings for social bookmarking systems with commercial search engine
rankings.
Our experiments are performed on data of the social bookmarking system
Del.icio.us and on rankings and log data from Google, MSN, and AOL. We
will show that part of the difference between the systems is due to different
behaviour (e. g., the concatenation of multi-word lexems to single terms
in Del.icio.us), and that real-world events may trigger similar behaviour
in both kinds of systems. We will also show that a graph-based ranking
approach on folksonomies yields results that are closer to the rankings of
the commercial search engines than vector space retrieval, and that the
correlation is high in particular for the domains that are well covered by
the social bookmarking system.
@inproceedings{paper:krause:2008a,
abstract = {Social bookmarking systems allow users to store links to internet
resources on a web page. As social bookmarking systems are growing
in popularity, search algorithms have been developed that transfer the idea
of link-based rankings in the Web to a social bookmarking system’s data
structure. These rankings differ from traditional search engine rankings in
that they incorporate the rating of users.
In this study, we compare search in social bookmarking systems with traditional
Web search. In the first part, we compare the user activity and
behaviour in both kinds of systems, as well as the overlap of the underlying
sets of URLs. In the second part, we compare graph-based and vector
space rankings for social bookmarking systems with commercial search engine
rankings.
Our experiments are performed on data of the social bookmarking system
Del.icio.us and on rankings and log data from Google, MSN, and AOL. We
will show that part of the difference between the systems is due to different
behaviour (e. g., the concatenation of multi-word lexems to single terms
in Del.icio.us), and that real-world events may trigger similar behaviour
in both kinds of systems. We will also show that a graph-based ranking
approach on folksonomies yields results that are closer to the rankings of
the commercial search engines than vector space retrieval, and that the
correlation is high in particular for the domains that are well covered by
the social bookmarking system.},
added-at = {2008-09-09T11:15:22.000+0200},
author = {Krause, Beate and Hotho, Andreas and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/2613f5c41ff759fc548c9085102d1c933/mschuber},
booktitle = {Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008},
interhash = {37598733b747093d97a0840a11beebf5},
intrahash = {613f5c41ff759fc548c9085102d1c933},
keywords = {2008 bookmarking del.icio.us folksonomy log search search-engines social tags},
pages = {101-113},
publisher = {Springer},
timestamp = {2008-09-09T11:15:22.000+0200},
title = {A Comparison of Social Bookmarking with Traditional Search},
url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/ecir2008krause.pdf},
volume = 4956,
year = 2008
}