%0 
%0 Conference Proceedings
%A Jäschke, Robert; Krause, Beate; Hotho, Andreas & Stumme, Gerd
%D 2008
%T Logsonomy -- A Search Engine Folksonomy
%E 
%B Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)
%C 
%I AAAI Press
%V 
%6
%N 
%P 
%& 
%Y 
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%7
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%9
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%! 
%Z 
%@ 
%(
%)
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%1 
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%3 inproceedings
%4 
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%$ 
%F jaeschke2008logsonomy
%K 2008, itegpub, folksonomies, engine, tagorapub, folksonomy, myown, logsonomy, search, logsonomies
%X In social bookmarking systems users describe bookmarksby keywords called tags. The structure behindthese social systems, called folksonomies, can beviewed as a tripartite hypergraph of user, tag and resourcenodes. This underlying network shows specificstructural properties that explain its growth and the possibilityof serendipitous exploration.Search engines filter the vast information of the web.Queries describe a user’s information need. In responseto the displayed results of the search engine, users clickon the links of the result page as they expect the answerto be of relevance. The clickdata can be represented as afolksonomy in which queries are descriptions of clickedURLs. This poster analyzes the topological characteristicsof the resulting tripartite hypergraph of queries,users and bookmarks of two query logs and compares ittwo a snapshot of the folksonomy del.icio.us.
%Z 
%U http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf
%+
%^

%0 
%0 Conference Proceedings
%A Jäschke, Robert; Krause, Beate; Hotho, Andreas & Stumme, Gerd
%D 2008
%T Logsonomy -- A Search Engine Folksonomy
%E 
%B Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)
%C 
%I AAAI Press
%V 
%6
%N 
%P 
%& 
%Y 
%S 
%7
%8 
%9
%? 
%! 
%Z 
%@ 
%(
%)
%*
%L
%M
%1 
%2 
%3 inproceedings
%4 
%# 
%$ 
%F jaeschke2008logsonomy
%K 2008, itegpub, folksonomies, engine, tagorapub, folksonomy, logsonomy, search, logsonomies
%X In social bookmarking systems users describe bookmarksby keywords called tags. The structure behindthese social systems, called folksonomies, can beviewed as a tripartite hypergraph of user, tag and resourcenodes. This underlying network shows specificstructural properties that explain its growth and the possibilityof serendipitous exploration.Search engines filter the vast information of the web.Queries describe a user’s information need. In responseto the displayed results of the search engine, users clickon the links of the result page as they expect the answerto be of relevance. The clickdata can be represented as afolksonomy in which queries are descriptions of clickedURLs. This poster analyzes the topological characteristicsof the resulting tripartite hypergraph of queries,users and bookmarks of two query logs and compares ittwo a snapshot of the folksonomy del.icio.us.
%Z 
%U http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf
%+
%^

%0 
%0 Conference Proceedings
%A Jäschke, Robert; Krause, Beate; Hotho, Andreas & Stumme, Gerd
%D 2008
%T Logsonomy -- A Search Engine Folksonomy
%E 
%B Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)
%C 
%I AAAI Press
%V 
%6
%N 
%P 
%& 
%Y 
%S 
%7
%8 
%9
%? 
%! 
%Z 
%@ 
%(
%)
%*
%L
%M
%1 
%2 Publications of Gerd Stumme
%3 inproceedings
%4 
%# 
%$ 
%F Jaeschke2008logsonomy
%K 2008, itegpub, folksonomies, engine, tagorapub, folksonomy, myown, logsonomy, search, logsonomies
%X In social bookmarking systems users describe bookmarks
by keywords called tags. The structure behind
these social systems, called folksonomies, can be
viewed as a tripartite hypergraph of user, tag and resource
nodes. This underlying network shows specific
structural properties that explain its growth and the possibility
of serendipitous exploration.
Search engines filter the vast information of the web.
Queries describe a user’s information need. In response
to the displayed results of the search engine, users click
on the links of the result page as they expect the answer
to be of relevance. The clickdata can be represented as a
folksonomy in which queries are descriptions of clicked
URLs. This poster analyzes the topological characteristics
of the resulting tripartite hypergraph of queries,
users and bookmarks of two query logs and compares it
two a snapshot of the folksonomy del.icio.us.
%Z 
%U http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf
%+
%^

%0 
%0 Conference Proceedings
%A Krause, Beate; Jäschke, Robert; Hotho, Andreas & Stumme, Gerd
%D 2008
%T Logsonomy - Social Information Retrieval with Logdata
%E 
%B HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia
%C New York, NY, USA
%I ACM
%V 
%6
%N 
%P 157--166
%& 
%Y 
%S 
%7
%8 
%9
%? 
%! 
%Z 
%@ 978-1-59593-985-2
%(
%)
%*
%L
%M
%1 
%2 
%3 inproceedings
%4 
%# 
%$ 
%F krause2008logsonomy
%K information, web20, 2008, 2.0, web2.0, analysis, myown, retrieval, network, web, itegpub, tagorapub, social, folksonomy, logsonomy, search
%X Social bookmarking systems constitute an established
part of the Web 2.0. In such systems
users describe bookmarks by keywords
called tags. The structure behind these social
systems, called folksonomies, can be viewed
as a tripartite hypergraph of user, tag and resource
nodes. This underlying network shows
specific structural properties that explain its
growth and the possibility of serendipitous
exploration.
Today’s search engines represent the gateway
to retrieve information from the World Wide
Web. Short queries typically consisting of
two to three words describe a user’s information
need. In response to the displayed
results of the search engine, users click on
the links of the result page as they expect
the answer to be of relevance.
This clickdata can be represented as a folksonomy
in which queries are descriptions of
clicked URLs. The resulting network structure,
which we will term logsonomy is very
similar to the one of folksonomies. In order
to find out about its properties, we analyze
the topological characteristics of the tripartite
hypergraph of queries, users and bookmarks
on a large snapshot of del.icio.us and
on query logs of two large search engines.
All of the three datasets show small world
properties. The tagging behavior of users,
which is explained by preferential attachment
of the tags in social bookmark systems, is
reflected in the distribution of single query
words in search engines. We can conclude
that the clicking behaviour of search engine
users based on the displayed search results
and the tagging behaviour of social bookmarking
users is driven by similar dynamics.
%Z 
%U http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia
%+
%^

%0 
%0 Conference Proceedings
%A Krause, Beate; Jäschke, Robert; Hotho, Andreas & Stumme, Gerd
%D 2008
%T Logsonomy - Social Information Retrieval with Logdata
%E 
%B HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia
%C New York, NY, USA
%I ACM
%V 
%6
%N 
%P 157--166
%& 
%Y 
%S 
%7
%8 
%9
%? 
%! 
%Z 
%@ 978-1-59593-985-2
%(
%)
%*
%L
%M
%1 
%2 
%3 inproceedings
%4 
%# 
%$ 
%F krause2008logsonomy
%K information, web20, 2008, 2.0, web2.0, analysis, myown, retrieval, network, web, itegpub, tagorapub, social, folksonomy, logsonomy, search
%X Social bookmarking systems constitute an established
part of the Web 2.0. In such systems
users describe bookmarks by keywords
called tags. The structure behind these social
systems, called folksonomies, can be viewed
as a tripartite hypergraph of user, tag and resource
nodes. This underlying network shows
specific structural properties that explain its
growth and the possibility of serendipitous
exploration.
Today’s search engines represent the gateway
to retrieve information from the World Wide
Web. Short queries typically consisting of
two to three words describe a user’s information
need. In response to the displayed
results of the search engine, users click on
the links of the result page as they expect
the answer to be of relevance.
This clickdata can be represented as a folksonomy
in which queries are descriptions of
clicked URLs. The resulting network structure,
which we will term logsonomy is very
similar to the one of folksonomies. In order
to find out about its properties, we analyze
the topological characteristics of the tripartite
hypergraph of queries, users and bookmarks
on a large snapshot of del.icio.us and
on query logs of two large search engines.
All of the three datasets show small world
properties. The tagging behavior of users,
which is explained by preferential attachment
of the tags in social bookmark systems, is
reflected in the distribution of single query
words in search engines. We can conclude
that the clicking behaviour of search engine
users based on the displayed search results
and the tagging behaviour of social bookmarking
users is driven by similar dynamics.
%Z 
%U http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia
%+
%^