BibSonomyburst/user/nepomuk/wp5BibSonomy RSS feed for /user/nepomuk/wp52012-02-16T00:41:05+01:00http://www.bibsonomy.org/bibtex/27eb26a177187ea8cf788cc897d66ee48/nepomuknepomuk2010-02-04T09:21:48+01:002008 engine folksonomy from:jaeschke l3s logsonomy myown search wp5 <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Krause">Beate Krause</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Proceedings of the Second International Conference on Weblogs and Social Media ICWSM 2008, </em><em>page 192--193. </em><em>Menlo Park, CA, USA, </em><em>AAAI Press, </em>(<em>2008</em>)Thu 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.http://www.bibsonomy.org/bibtex/2e64d14f3207766f4afc65983fa759ffe/nepomuknepomuk2009-05-13T09:36:02+02:002008 analysis engine from:jaeschke information l3s logsonomy myown network retrieval search social wp5 <span class="authorEditorList"><a href="/author/Krause">Beate Krause</a>, <a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>HT &#039;08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia, </em><em>page 157--166. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2008</em>)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.http://www.bibsonomy.org/bibtex/2b0ddf832fe0f348365b55c2a06d06789/nepomuknepomuk2009-01-21T11:18:18+01:0010 2008 from:demartini l3s lang:en wp5 <span class="authorEditorList"><a href="/author/Demartini">Gianluca Demartini</a>, and <a href="/author/Niederée">Claudia Niederée</a> </span> (<em>2008</em>)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.http://www.bibsonomy.org/bibtex/2cc713ef72448b44e2a00473bf39d2fc3/nepomuknepomuk2009-01-21T09:47:09+01:0011-2008 L3S WP5 from:stecher <span class="authorEditorList"><a href="/author/Stecher">Rodolfo Stecher</a>, <a href="/author/Demartini">Gianluca Demartini</a>, and <a href="/author/Niederée">Claudia Niederée</a> </span><em>10th International Conference Information Integration and Web-based Applications &amp; Services, </em><em>Linz, Austria, </em>(<em>November 2008</em>)Wed Jan 21 09:47:09 CET 2009Linz, Austria10th International Conference Information Integration and Web-based Applications & Services NovemberSocial Recommendations of Content and Metadata200811-2008 L3S WP5 from:stecher In this paper we present metadata based recommendation algorithms addressing two scenarios within social desktop communities: a) recommendation of resources from the co-worker's desktop, and b) recommendation of metadata for enriching the own annotation layer. Together with the algorithms we present first evaluation results as well as empirical evaluations showing that metadata based recommendations can be used in such distributed social desktop communities. http://www.bibsonomy.org/bibtex/254a249ca255a0fe2c67230eb2a484756/nepomuknepomuk2009-01-21T09:47:09+01:0010-2008 L3S WP5 from:stecher <span class="authorEditorList"><a href="/author/Stecher">Rodolfo Stecher</a>, <a href="/author/Niederée">Claudia Niederée</a>, and <a href="/author/Nejdl">Wolfgang Nejdl</a> </span><em>CIKM &#039;08: Proceeding of the 17th ACM conference on Information and knowledge management, </em><em>page 797--806. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2008</em>)Wed Jan 21 09:47:09 CET 2009New York, NY, USACIKM '08: Proceeding of the 17th ACM conference on Information and knowledge management797--806Wildcards for lightweight information integration in virtual desktops200810-2008 L3S WP5 from:stecher We present a flexible information integration approach which addresses the dynamic integration needs in a personal desktop environment where only partial mappings are defined between the sources to be integrated. Our approach is based on query rewriting using substitution rules. In addition to exploiting defined mappings, we employ substitution strategies, which are inspired by the idea of using wildcards in querying and filtering tasks. Starting from a triple based query language as used for querying RDF data, unmapped ontological elements are substituted in a controlled way with variables, leading to a controlled form of query relaxation. In addition, the approach also provides evidences for refining the existing mapping based on the results of executing the relaxed queries. Different strategies for replacing non-matched ontology elements with variables are presented and evaluated over real-world data sets.http://www.bibsonomy.org/bibtex/2006216392f06233f8888a67b222ae4a7/nepomuknepomuk2009-01-21T09:47:09+01:0011-2008 L3S WP5 from:stecher <span class="authorEditorList"><a href="/author/Stecher">Rodolfo Stecher</a>, <a href="/author/Niederée">Claudia Niederée</a>, and <a href="/author/Nejdl">Wolfgang Nejdl</a> </span><em>Digital Information Management, 2008. ICDIM 2008. Third International Conference on</em> (<em>November 2008</em>)Wed Jan 21 09:47:09 CET 2009Digital Information Management, 2008. ICDIM 2008. Third International Conference onNov.375-380Query rewriting for lightweight information integration200811-2008 L3S WP5 from:stecher Light-weight information integration has to be able to effectively deal with settings where only partial mappings between the information sources to be integrated are defined. In our query rewriting approach, such partial mappings are used as the basis for defining several strategies to substitute elements in the query, and for introducing wildcards for relaxing the query when mappings are missing. The approach also supports the extension and refinement of the existing mappings based on the achieved query results and optional feedback of the user. This paper presents the proposed rewriting strategies, focusing on strategies exploiting ontological knowledge, and a comparison and evaluation of the strategies for real-world datasets.http://www.bibsonomy.org/bibtex/218e8babe208fae2c0342438617b0ec31/nepomuknepomuk2009-01-05T13:51:02+01:002008 analysis concept folksonomy formal from:jaeschke l3s myown tagging trias wp5 <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Hotho">Andreas Hotho</a>, <a href="/author/Schmitz">Christoph Schmitz</a>, <a href="/author/Ganter">Bernhard Ganter</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Web Semantics: Science, Services and Agents on the World Wide Web</em> <em>6(1):38--53</em> (<em>February 2008</em>)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.ScienceDirect - Web Semantics: Science, Services and Agents on the World Wide Web : Discovering shared conceptualizations in folksonomieshttp://www.bibsonomy.org/bibtex/2f5e9298a72b40bad37e1d4ab19b88801/nepomuknepomuk2008-08-13T11:22:16+02:00from:demartini l3s nepomuk wp5 <span class="authorEditorList"><a href="/author/Demartini">Gianluca Demartini</a> </span><em>10th International Conference on Enterprise Information Systems, ICEIS 2008, </em>(<em>June 2008</em>)Wed Aug 13 11:22:16 CEST 200810th International Conference on Enterprise Information Systems, ICEIS 2008JuneComparing People in the Enterprise2008from:demartini l3s nepomuk wp5 Enterprise Search Systems are requested to provide more and more functionalities for supporting decision at the management level. An important aspect to consider is the human power and the knowledge which is available. For this reason, in this paper, after extracting a list of requirements out of a specific scenario, and presenting the previous work, we describe an improved approach to compare experts in order to retrieve and present to the user the most appropriate candidates for a given projecthttp://www.bibsonomy.org/bibtex/255d56872b4e905b6cf8612864b3bfa9b/nepomuknepomuk2008-08-13T11:22:16+02:00from:demartini l3s nepomuk wp5 <span class="authorEditorList"><a href="/author/Demartini">Gianluca Demartini</a> </span><em>FEWS 2007: Finding Experts on the Web with Semantics Workshop at ISWC 2007 + ASWC 2007</em> (<em>November 2007</em>)Wed Aug 13 11:22:16 CEST 2008FEWS 2007: Finding Experts on the Web with Semantics Workshop at ISWC 2007 + ASWC 2007NovemberFinding Experts Using Wikipedia2007from:demartini l3s nepomuk wp5 When we want to find experts on the Web we might want to search where the knowledge is created by the users. One of such knowledge repository is Wikipedia. People expertises are described in Wikipedia pages and also the Wikipedia users can be considered experts on the topics they produce content on. In this paper we propose algorithms to find experts in Wikipedia. The two different approaches are finding experts in the Wikipedia content or among the Wikipedia users. We also use semantics from WordNet and Yago in order to disambiguate expertise topics and to improve the retrieval effectiveness. In the end, we show how our methodology can be implemented in a system in order to improve the expert retrieval effectiveness.http://www.bibsonomy.org/bibtex/2b3084a6c64ccf9314a1441b6d05b9469/nepomuknepomuk2008-08-13T11:22:16+02:00from:demartini l3s nepomuk wp5 <span class="authorEditorList"><a href="/author/Demartini">Gianluca Demartini</a> </span><em>PIKM 2007: 1st ACM International Workshop for Ph.D. Students in Information and Knowledge Management</em> (<em>November 2007</em>)Wed Aug 13 11:22:16 CEST 2008PIKM 2007: 1st ACM International Workshop for Ph.D. Students in Information and Knowledge ManagementNovemberLeveraging Semantic Technologies for Enterprise Search2007from:demartini l3s nepomuk wp5 Enterprise search is very different from Web search (for example in the link structure or in the user’s needs and goal) and some steps have been already done to exploit these differences in order to improve the effectiveness of enterprise search. In this paper we present the state of the art of the enterprise search field with some open issues. We also present a research plan that aims at using Information Retrieval, Semantic Web, and User Modelling techniques to cope with these issues improving the current state of enterprise search.http://www.bibsonomy.org/bibtex/249e729a1b7509260f06929d0fb97f86a/nepomuknepomuk2008-08-13T11:22:16+02:00from:demartini l3s nepomuk wp5 <span class="authorEditorList"><a href="/author/Chernov">Sergey Chernov</a>, <a href="/author/Demartini">Gianluca Demartini</a>, <a href="/author/Herder">Eelco Herder</a>, <a href="/author/Kopycki">Michał Kopycki</a>, and <a href="/author/Nejdl">Wolfgang Nejdl</a> </span><em>Personal Information Management Workshop at CHI 2008, </em>(<em>April 2008</em>)Wed Aug 13 11:22:16 CEST 2008Personal Information Management Workshop at CHI 2008AprilEvaluating Personal Information Management Using an Activity Logs Enriched Desktop Dataset2008from:demartini l3s nepomuk wp5 The effective evaluation of Personal Information Management is a crucial problem for the research community. While evaluation methodologies for retrieval on the Web and in digital libraries are well-developed, the experiments with the advanced desktop tools are neither repeatable nor comparable. As privacy concerns do not allow to copy and distribute personal data outside the research lab, we suggest to overcome this problem by creation of desktop datasets within different research groups using a single methodology and a common set of tools. A dataset can include not only a static snapshot of the desktop documents, but also the logs of user activity on the desktop within several last months. We present the structure of the required dataset, a set of implemented tools and a sample dataset collected within the L3S Research Center.http://www.bibsonomy.org/bibtex/276d81124951ae39060a8bc98f4883435/nepomuknepomuk2008-06-20T14:42:46+02:00analysis engine from:jaeschke information l3s logsonomy network retrieval search social wp5 <span class="authorEditorList"><a href="/author/Krause">Beate Krause</a>, <a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>HT &#039;08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia, </em><em>page 157--166. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2008</em>)Fri Jun 20 14:42:46 CEST 2008New York, NY, USAHT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia157--166Logsonomy - Social Information Retrieval with Logdata2008analysis engine from:jaeschke information l3s logsonomy 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.http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/nepomuknepomuk2008-06-20T14:39:26+02:002008 engine folksonomy from:jaeschke l3s logsonomy myown search wp5 <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Krause">Beate Krause</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Proceedings of the Second International Conference on Weblogs and Social MediaICWSM 2008, </em><em>AAAI Press, </em>(<em>2008</em>)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.http://www.bibsonomy.org/bibtex/263901930c137df0c2dad84075c564b14/nepomuknepomuk2008-04-15T11:58:42+02:002008 analysis concept folksonomy formal from:jaeschke l3s myown tagging wp5 <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Hotho">Andreas Hotho</a>, <a href="/author/Schmitz">Christoph Schmitz</a>, <a href="/author/Ganter">Bernhard Ganter</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Web Semantics: Science, Services and Agents on the World Wide Web</em> <em>6(1):38--53</em> (<em>February 2008</em>)Tue Apr 15 11:58:42 CEST 2008Semantic 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 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.ScienceDirect - Web Semantics: Science, Services and Agents on the World Wide Web : Discovering shared conceptualizations in folksonomieshttp://www.bibsonomy.org/bibtex/2bb8ecec699a2f129322fe334747c6aef/nepomuknepomuk2007-11-12T12:55:47+01:002007 folksonomy from:jaeschke l3s myown recommender tagging wp5 <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Marinho">Leandro Balby Marinho</a>, <a href="/author/Hotho">Andreas Hotho</a>, <a href="/author/Schmidt-Thieme">Lars Schmidt-Thieme</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, </em><em>volume 4702 of Lecture Notes in Computer Science, </em><em>page 506-514. </em><em>Berlin, Heidelberg, </em><em>Springer, </em>(<em>2007</em>)Mon Nov 12 12:55:47 CET 2007Berlin, HeidelbergKnowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases506-514Lecture Notes in Computer ScienceTag Recommendations in Folksonomies470220072007 folksonomy from:jaeschke l3s myown recommender tagging wp5 Collaborative tagging systems allow users to assign keywords—so called “tags”—to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we evaluate and compare two recommendation algorithms on largescale real life datasets: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank. We show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.http://www.bibsonomy.org/bibtex/242cda5911e901eadd0ac6a106a6aa1dc/nepomuknepomuk2007-03-22T18:29:28+01:002006 UniK detection folkrank folksonomy from:pchirita hotho jaeschke l3s myown nepomuk pagerank schmitz stumme tagorapub trend triadic wp5 <span class="authorEditorList"><a href="/author/Hotho">Andreas Hotho</a>, <a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Schmitz">Christoph Schmitz</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Proc. First International Conference on Semantics And Digital Media Technology SAMT, </em><em>volume 4306 of LNCS, </em><em>page 56-70. </em><em>Heidelberg, </em><em>Springer, </em>(<em>December 2006</em>)Thu Mar 22 18:29:28 CET 2007HeidelbergProc. First International Conference on Semantics And Digital Media Technology (SAMT) dec56-70LNCSTrend Detection in Folksonomies430620062006 UniK detection folkrank folksonomy from:pchirita hotho jaeschke l3s myown nepomuk pagerank schmitz stumme tagorapub trend triadic wp5 As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.http://www.bibsonomy.org/bibtex/25854a71547051543dd3d3d5e2e2f2b67/nepomuknepomuk2007-03-22T18:29:28+01:002006 bibsonomy bookmarking folksonomy from:pchirita iccs l3s myown nepomuk social wp5 <span class="authorEditorList"><a href="/author/Hotho">Andreas Hotho</a>, <a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Schmitz">Christoph Schmitz</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures, </em><em>page 87-102. </em><em>Aalborg, </em><em>Aalborg Universitetsforlag, </em>(<em>2006</em>)Thu Mar 22 18:29:28 CET 2007AalborgProceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures87-102{BibSonomy}: A Social Bookmark and Publication Sharing System20062006 bibsonomy bookmarking folksonomy from:pchirita iccs l3s myown nepomuk social wp5 Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies and briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references in a kind of personal library.http://www.bibsonomy.org/bibtex/202e15bce218d3fae877316dbfb58e942/nepomuknepomuk2007-03-22T18:29:28+01:00desktopsearch distributed from:pchirita l3s nepomuk ranking wp5 <span class="authorEditorList"><a href="/author/Paiu">Raluca Paiu</a>, and <a href="/author/Costache">Stefania Costache</a> </span> (<em>2007</em>)Thu Mar 22 18:29:28 CET 2007Proc. of the 19th Intl. CAiSE ConferencePersonalizing PageRank-Based Ranking over Distributed Collections2007desktopsearch distributed from:pchirita l3s nepomuk ranking wp5 http://www.bibsonomy.org/bibtex/211b2a59a568d246d7f36cb68169a464a/nepomuknepomuk2007-03-22T18:29:28+01:002006 analysis folksonomies folksonomy from:pchirita l3s myown nepomuk network semantic wp5 <span class="authorEditorList"><a href="/author/Schmitz">Christoph Schmitz</a>, <a href="/author/Hotho">Andreas Hotho</a>, <a href="/author/Jäschke">Robert Jäschke</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Data Science and Classification. Proceedings of the 10th IFCS Conf., </em><em>page 261--270. </em><em>Heidelberg, </em><em>Springer, </em>(<em>July 2006</em>)Thu Mar 22 18:29:28 CET 2007HeidelbergData Science and Classification. Proceedings of the 10th IFCS Conf.July261--270Studies in Classification, Data Analysis, and Knowledge OrganizationMining Association Rules in Folksonomies20062006 analysis folksonomies folksonomy from:pchirita l3s myown nepomuk network semantic wp5 Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.http://www.bibsonomy.org/bibtex/205043cc20f1e0f5a612135c970e4f1ac/nepomuknepomuk2007-03-22T18:29:28+01:002006 UniK bibsonomy emergence emergent folksonomy from:pchirita hotho jaeschke l3s myown nepomuk schmitz semantics stumme tagorapub wp5 <span class="authorEditorList"><a href="/author/Hotho">Andreas Hotho</a>, <a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Schmitz">Christoph Schmitz</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Informatik 2006 - Informatik für Menschen. Band 2, </em><em>volume P-94 of Lecture Notes in Informatics, </em><em>Bonn, </em><em>Gesellschaft für Informatik, </em>(<em>October 2006</em>)<em>Proc. Workshop on Applications of Semantic Technologies, Informatik 2006 . </em>Thu Mar 22 18:29:28 CET 2007BonnInformatik 2006 - Informatik für Menschen. Band 2octProc. Workshop on Applications of Semantic Technologies, Informatik 2006Lecture Notes in InformaticsEmergent Semantics in BibSonomyP-9420062006 UniK bibsonomy emergence emergent folksonomy from:pchirita hotho jaeschke l3s myown nepomuk schmitz semantics stumme tagorapub wp5 Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.