BibSonomy publications for /user/nepomuk/2008Thu Feb 04 09:21:48 CET 2010Menlo Park, CA, USAProceedings of the Second International Conference on Weblogs and Social Media (ICWSM 2008)192--193Logsonomy -- A Search Engine Folksonomy20082008 engine folksonomy from:jaeschke l3s logsonomy myown search wp5 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.Wed May 13 09:36:02 CEST 2009New York, NY, USAHT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia157--166Logsonomy - Social Information Retrieval with Logdata20082008 analysis engine from:jaeschke information l3s logsonomy myown network retrieval search 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.Wed Jan 21 11:18:18 CET 2009Finding Experts on the Semantic Desktop200810 2008 from:demartini l3s lang:en wp5 Expert retrieval has attracted deep attention because of the huge economical impact it can have on enterprises. The classical dataset on which to perform this task is company intranet (i.e., personal pages, e-mails, documents). We propose a new system for nding experts in the user's desktop content. Looking at private documents and e-mails of the user, the system builds expert proles for all the people named in the desktop. This allows the search system to focus on the user's topics of interest thus generating satisfactory results on topics well represented on the desktop. We show, with an articial test collection, how the desktop content is appropriate for nding experts on the topic the user is interested in.Tue Jan 20 12:21:05 CET 2009Talk12Talk: The Semantic Desktop - a new hope for Personal Information Management200812 2008 dfki from:leobard lang:en wp2 wp7 With today's operating systems it is possible to store a file to a folder, but not to a project or a person. Applications do not share concepts of persons or projects. In the Semantic Web effort, the W3C has proposed standards for the management of metadata. This talk is about a merge of Semantic Web and Personal Computers resulting in the Semantic Desktop. Existing data sources are adapted to RDF, enabling integration across applications. Different projects aim at implementing the new paradigm, in the talk the open source frameworks published by the NEPOMUK project are presented.Mon Jan 05 13:51:02 CET 2009New YorkSemantic Web and Web 2.0Web Semantics: Science, Services and Agents on the World Wide WebFeb138--53Discovering Shared Conceptualizations in Folksonomies620082008 analysis concept folksonomy formal from:jaeschke l3s myown tagging trias wp5 Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.Thu Nov 13 14:32:38 CET 2008Tutorial: Semantic Desktop Solutions200810 2008 deri dfki from:leobard lang:en nepomuk wp1 wp2 wp7 Thu Nov 13 14:32:38 CET 2008NEPOMUK Nexus Exhibition at the ISWC2008200810 2008 DERI DFKI FZI from:leobard wp7 Thu Nov 13 14:32:38 CET 2008Talk: The Semantic Desktop - Semantic Web in Applications200809 2008 dfki from:leobard lang:en nepomuk wp2 wp7 Wed Nov 05 17:13:43 CET 2008Proc. ISWC Conferencepp 467-482LNCSEvaluating long-term use of the Gnowsis Semantic Desktop for PIM5318200810 2008 dfki from:leobard imported iswc iswc2008 lang:en nepomuk semanticdesktop semanticweb semdesk wp2 The Semantic Desktop is a means to support users in Personal Information Management (PIM). Using the open source software prototype Gnowsis, we evaluated the approach in a two month case study in 2006 with eight participants. Two participants continued using the prototype and were interviewed after two years in 2008 to show their long-term usage patterns. This allows us to analyse how the system was used for PIM. Contextual interviews gave insights on behaviour, while questionnaires and event logging did not. We discovered that in the personal environment, simple has-Part and is-related relations are sufficient for users to file and re-find information, and that the personal semantic wiki was used creatively to note information.Mon Oct 13 10:42:29 CEST 2008Berlin, HeidelbergSocial Semantic Web18363--391X.media.pressSocial Bookmarking am Beispiel BibSonomy20092008 bibsonomy bookmarking from:jaeschke l3s myown social BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitung der Universität Kassel. Es erlaubt das Speichern und Organisieren von Web-Lesezeichen und Metadaten für wissenschaftlichePublikationen. In diesem Beitrag beschreiben wir die von BibSonomy bereitgestellte Funktionalität, die dahinter stehende Architektursowie das zugrunde liegende Datenmodell. Ferner erläutern wir Anwendungsbeispiele und gehen auf Methoden zur Analyse der inBibSonomy und ähnlichen Systemen enthaltenen Daten ein.Wed Oct 08 16:12:30 CEST 2008New York, NY, USAHT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia157--166Logsonomy - social information retrieval with logdata20082008 from:jaeschke l3s logsonomy myown Tue Sep 02 11:14:18 CEST 2008Proc. of ESWCJune569-583Combining Metadata and Document Search with Spreading Activation for Semantic Desktop Search200806 2008 dfki from:leobard imported lang:en wp2 The Semantic Desktop is a means to support users in Personal Information Management (PIM). It provides an excellent test bed for Semantic Web technology: resources (e. g., persons, projects, messages, documents) are distributed amongst multiple systems, ontologies are used to link and annotate them. Finding information is a core element in PIM. For the end user, the search interface has to be intuitive to use, natural language queries provide a simple mean to express requests. State of the art semantic search engines focus on fact retrieval or on semantic document retrieval. We combine both approaches to search the Semantic Desktop exploiting all available information. Our semantic search engine, built on semantic teleporting and spreading activation, is able to answer natural language queries with facts, e. g., a specific phone number, and/or relevant documents. We evaluated our approach on ESWC 2007 data in comparison with Google site search.Thu Jul 24 17:14:09 CEST 2008IJWIS2198-214Adaptive ontology re-use: finding and re-using sub-ontologies420082008 L3S from:stecher lang:en ontologies reuse The discovery of the "right" ontology or ontology part is a central ingredient for effective ontology re-use. We present an approach for supporting a form of adaptive re-use of sub-ontologies, where the ontologies are deeply integrated beyond pure referencing.Thu Jul 24 00:24:34 CEST 2008AAAI Spring Symposium on AI Meets Business Rules and Process Management, Stanford Univ.99-104Business Process Modeling, Task Management, and the Semantic Link200804 2008 SAP WP3 businessprocess from:uvriss lang:en semanticwebservices webservice Thu Jul 24 00:15:47 CEST 2008Multikonferenz Wirtschaftsinformatikconf/mkwi/2008KASIMIR - Work process embedded task management leveraging the Semantic Desktop.200802 2008 SAP WP10 from:uvriss lang:en taskmanagement Fri Jun 20 14:39:26 CEST 2008Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)Logsonomy — A Search Engine Folksonomy20082008 engine folksonomy from:jaeschke l3s logsonomy myown search wp5 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.Wed Jun 18 21:26:52 CEST 200803Leo Sauermann was invited to present slides about NEPOMUK at the Studecki Festiwal Informatyczny, an bigger event organized by polish students. http://www.sfi.org.pl/Presentation of NEPOMUK at Krakow Student Festival200803 2008 dfki from:leobard lang:en nepomuk wp2 Wed Jun 18 21:26:52 CEST 2008Proc. of ESWCJune569-583Combining Metadata and Document Search with Spreading Activation for Semantic Desktop Search200806 2008 dfki from:leobard imported lang:en wp2 The Semantic Desktop is a means to support users in Personal Information Management (PIM). It provides an excellent test bed for Semantic Web technology: resources (e. g., persons, projects, messages, documents) are distributed amongst multiple systems, ontologies are used to link and annotate them. Finding information is a core element in PIM. For the end user, the search interface has to be intuitive to use, natural language queries provide a simple mean to express requests. State of the art semantic search engines focus on fact retrieval or on semantic document retrieval. We combine both approaches to search the Semantic Desktop exploiting all available information. Our semantic search engine, built on semantic teleporting and spreading activation, is able to answer natural language queries with facts, e. g., a specific phone number, and/or relevant documents. We evaluated our approach on ESWC 2007 data in comparison with Google site search.Wed Jun 18 21:26:52 CEST 200804Presentation of NEPOMUK and Case Studies at Oil Industry Norway Semantic Web Days200804 2008 dfki from:leobard nepomuk wp2 Presentation of case studies of successfull Semantic Web use, NEPOMUK is one of them. Audience are Oil Industry and Defence Industry IT Executives.Fri May 30 11:43:56 CEST 2008W3C SWEO Case Study05SWEO Case studies include descriptions of systems that have been deployed within an organization, and are now being used within a production environment.Case Study: KDE 4.0 Semantic Desktop Search and Tagging200805 2008 dfki from:leobard lang:en mandriva wp12 wp2 KDE version 4.0 is a significant release that has been available since January 11, 2008. The libraries, desktop, applications, and artwork have been improved and adapted, and it now runs natively on a wider set of operating systems that include Linux, BSD, Solaris, Windows and Mac OS X. As part of this release, the search engine was overhauled and desktop annotation introduced. Based on standards and technologies developed in the NEPOMUK Semantic Desktop project, the search engine is now based on RDF and allows users to annotate and search for their files using Semantic Web standards.