http://www.bibsonomy.org/burst/user/hotho/query+myownBibSonomy BuRST Feed for /user/hotho/query+myown2008-10-07T19:08:12+02:00http://www.bibsonomy.org/bibtex/2613f5c41ff759fc548c9085102d1c933/hothohotho2008-05-19T14:43:47+02:00search social bookmarking log 2008 query myown <span style="color:#555555;">Beate <a href="http://www.bibsonomy.org/author/Krause">Krause</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008, </em><em>4956, </em><em>Seite101-113. </em><em>Springer, </em>(<em>2008</em>)Mon May 19 14:43:47 CEST 2008Advances in Information Retrieval, 30th European Conference on IR Research, ECIR 2008101-113A Comparison of Social Bookmarking with Traditional Search49562008search social bookmarking log 2008 query myown 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 traditionalWeb 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.http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/hothohotho2008-04-05T17:54:56+02:00analysis logsonomy search myown icwsm 2008 log folksonomy query network <span style="color:#555555;">Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Beate <a href="http://www.bibsonomy.org/author/Krause">Krause</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008), </em><em>AAAI Press, </em>(<em>2008</em>)Sat Apr 05 17:54:56 CEST 2008Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)Logsonomy — A Search Engine Folksonomy2008analysis logsonomy search myown icwsm 2008 log folksonomy query network 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.