Social bookmarking is an emerging type of a Web service that
helps users share, classify, and discover interesting resources. In
this paper, we explore the concept of an enhanced search, in
which data from social bookmarking systems is exploited for
enhancing search in the Web. We propose combining the widely
used link-based ranking metric with the one derived using social
bookmarking data. First, this increases the precision of a standard
link-based search by incorporating popularity estimates from
aggregated data of bookmarking users. Second, it provides an
opportunity for extending the search capabilities of existing
search engines. Individual contributions of bookmarking users as
well as the general statistics of their activities are used here for a
new kind of a complex search where contextual, temporal or
sentiment-related information is used. We investigate the
usefulness of social bookmarking systems for the purpose of
enhancing Web search through a series of experiments done on
datasets obtained from social bookmarking systems. Next, we
show the prototype system that implements the proposed
approach and we present some preliminary results.
%0 Conference Paper
%1 paper:yanbe:2008
%A Heymann, Paul
%A Koutrika, Georgia
%A Garcia-Molina, Hector
%B WSDM '08: Proceedings of the international conference on Web search and web data mining
%C New York, NY, USA
%D 2008
%I ACM
%K 2008 bookmarking search search-engines tags to-read
%P 195--206
%R http://doi.acm.org/10.1145/1341531.1341558
%T Can social bookmarking improve web search?
%U http://portal.acm.org/citation.cfm?id=1341531.1341558
%X Social bookmarking is an emerging type of a Web service that
helps users share, classify, and discover interesting resources. In
this paper, we explore the concept of an enhanced search, in
which data from social bookmarking systems is exploited for
enhancing search in the Web. We propose combining the widely
used link-based ranking metric with the one derived using social
bookmarking data. First, this increases the precision of a standard
link-based search by incorporating popularity estimates from
aggregated data of bookmarking users. Second, it provides an
opportunity for extending the search capabilities of existing
search engines. Individual contributions of bookmarking users as
well as the general statistics of their activities are used here for a
new kind of a complex search where contextual, temporal or
sentiment-related information is used. We investigate the
usefulness of social bookmarking systems for the purpose of
enhancing Web search through a series of experiments done on
datasets obtained from social bookmarking systems. Next, we
show the prototype system that implements the proposed
approach and we present some preliminary results.
%@ 978-1-59593-927-9
@inproceedings{paper:yanbe:2008,
abstract = {Social bookmarking is an emerging type of a Web service that
helps users share, classify, and discover interesting resources. In
this paper, we explore the concept of an enhanced search, in
which data from social bookmarking systems is exploited for
enhancing search in the Web. We propose combining the widely
used link-based ranking metric with the one derived using social
bookmarking data. First, this increases the precision of a standard
link-based search by incorporating popularity estimates from
aggregated data of bookmarking users. Second, it provides an
opportunity for extending the search capabilities of existing
search engines. Individual contributions of bookmarking users as
well as the general statistics of their activities are used here for a
new kind of a complex search where contextual, temporal or
sentiment-related information is used. We investigate the
usefulness of social bookmarking systems for the purpose of
enhancing Web search through a series of experiments done on
datasets obtained from social bookmarking systems. Next, we
show the prototype system that implements the proposed
approach and we present some preliminary results.},
added-at = {2008-09-09T15:01:30.000+0200},
address = {New York, NY, USA},
author = {Heymann, Paul and Koutrika, Georgia and Garcia-Molina, Hector},
biburl = {https://www.bibsonomy.org/bibtex/27ffee89349e08beef1b55ab9d68ddd30/mschuber},
booktitle = {WSDM '08: Proceedings of the international conference on Web search and web data mining},
description = {Can social bookmarking improve web search?},
doi = {http://doi.acm.org/10.1145/1341531.1341558},
interhash = {3192b26a3b1394e24283766de46dc14b},
intrahash = {7ffee89349e08beef1b55ab9d68ddd30},
isbn = {978-1-59593-927-9},
keywords = {2008 bookmarking search search-engines tags to-read},
location = {Palo Alto, California, USA},
pages = {195--206},
publisher = {ACM},
timestamp = {2008-09-09T15:01:30.000+0200},
title = {Can social bookmarking improve web search?},
url = {http://portal.acm.org/citation.cfm?id=1341531.1341558},
year = 2008
}