PUMA publications for /user/jaeschke/engine%20networkhttps://puma.uni-kassel.de/user/jaeschke/engine%20networkPUMA RSS feed for /user/jaeschke/engine%20network2024-03-29T10:37:48+01:00Logsonomy - Social Information Retrieval with Logdatahttps://puma.uni-kassel.de/bibtex/2e64d14f3207766f4afc65983fa759ffe/jaeschkejaeschke2011-01-27T12:08:28+01:002008 analysis engine information l3s logsonomy myown network retrieval search sna social wp5 <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Beate Krause" itemprop="url" href="/author/Beate%20Krause"><span itemprop="name">B. Krause</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Robert Jäschke" itemprop="url" href="/author/Robert%20J%c3%a4schke"><span itemprop="name">R. Jäschke</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Hotho" itemprop="url" href="/author/Andreas%20Hotho"><span itemprop="name">A. Hotho</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerd Stumme" itemprop="url" href="/author/Gerd%20Stumme"><span itemprop="name">G. Stumme</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia</span>, </em></span><em>Seite <span itemprop="pagination">157--166</span>. </em><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM</span>, </em>(<em><span>2008<meta content="2008" itemprop="datePublished"/></span></em>)Thu Jan 27 12:08:28 CET 2011New York, NY, USAHT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia157--166Logsonomy - Social Information Retrieval with Logdata20082008 analysis engine information l3s logsonomy myown network retrieval search sna social wp5 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.A community-aware search enginehttps://puma.uni-kassel.de/bibtex/233b448de19ddef891f2a4284b1cc42f1/jaeschkejaeschke2006-05-16T12:12:26+02:00search engine detection hits community network <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Rodrigo B. Almeida" itemprop="url" href="/author/Rodrigo%20B.%20Almeida"><span itemprop="name">R. Almeida</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Virgilio A. F. Almeida" itemprop="url" href="/author/Virgilio%20A.%20F.%20Almeida"><span itemprop="name">V. Almeida</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 13th international conference on World Wide Web</span>, </em></span><em>Seite <span itemprop="pagination">413--421</span>. </em><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM Press</span>, </em>(<em><span>2004<meta content="2004" itemprop="datePublished"/></span></em>)Tue May 16 12:12:26 CEST 2006New York, NY, USAProceedings of the 13th international conference on World Wide Web413--421A community-aware search engine2004search engine detection hits community network
Current search technologies work in a "one size fits all" fashion. Therefore, the answer to a query is independent of specific user information need. In this paper we describe a novel ranking technique for personalized search servicesthat combines content-based and community-based evidences. The community-based information is used in order to provide context for queries andis influenced by the current interaction of the user with the service. Ouralgorithm is evaluated using data derived from an actual service available on the Web an online bookstore. We show that the quality of content-based ranking strategies can be improved by the use of communityinformation as another evidential source of relevance. In our experiments the improvements reach up to 48% in terms of average precision.