http://www.bibsonomy.org/burst/user/jaeschke/folksonomyBibSonomy BuRST Feed for /user/jaeschke/folksonomy2008-10-07T18:48:55+02:00http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/jaeschkejaeschke2008-06-20T14:39:26+02:00search 2008 wp5 engine l3s logsonomy for:nepomuk myown folksonomy <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>)Fri Jun 20 14:39:26 CEST 2008Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)Logsonomy — A Search Engine Folksonomy2008search 2008 wp5 engine l3s logsonomy for:nepomuk myown folksonomy 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.Analysis of topological characteristics of huge online social networking serviceshttp://www.bibsonomy.org/bibtex/2441b644b330fec7951c274a502c26e58/jaeschkejaeschke2008-05-20T17:48:35+02:00network folksonomy analysis online social <span style="color:#555555;">Yong-Yeol <a href="http://www.bibsonomy.org/author/Ahn">Ahn</a> und Seungyeop <a href="http://www.bibsonomy.org/author/Han">Han</a> und Haewoon <a href="http://www.bibsonomy.org/author/Kwak">Kwak</a> und Sue <a href="http://www.bibsonomy.org/author/Moon">Moon</a> und Hawoong <a href="http://www.bibsonomy.org/author/Jeong">Jeong</a> </span><em>Proceedings of the 16th international conference on World Wide Web, </em><em>Seite835--844. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2007</em>)Tue May 20 17:48:35 CEST 2008New York, NY, USAProceedings of the 16th international conference on World Wide Web835--844Analysis of topological characteristics of huge online social networking services2007network folksonomy analysis online social ScienceDirect - Web Semantics: Science, Services and Agents on the World Wide Web : Discovering shared conceptualizations in folksonomieshttp://www.bibsonomy.org/bibtex/263901930c137df0c2dad84075c564b14/jaeschkejaeschke2008-04-15T11:57:08+02:002008 wp5 concept l3s formal folksonomy trias tagging analysis myown for:nepomuk <span style="color:#555555;">Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> und Bernhard <a href="http://www.bibsonomy.org/author/Ganter">Ganter</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Web Semantics: Science, Services and Agents on the World Wide Web</em><em>6(1):38--53</em><em>feb2008. </em>Tue Apr 15 11:57:08 CEST 2008Semantic Web and Web 2.0Web Semantics: Science, Services and Agents on the World Wide Webfeb138--53Discovering Shared Conceptualizations in Folksonomies620082008 wp5 concept l3s formal folksonomy trias tagging analysis myown for:nepomuk 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.http://www.bibsonomy.org/bibtex/2da6c676c5664017247c7564fc247b190/jaeschkejaeschke2008-03-14T08:51:30+01:00network folksonomy property <span style="color:#555555;">Ciro <a href="http://www.bibsonomy.org/author/Cattuto">Cattuto</a> und Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> und Andrea <a href="http://www.bibsonomy.org/author/Baldassarri">Baldassarri</a> und Vito D. P. <a href="http://www.bibsonomy.org/author/Servedio">Servedio</a> und Vittorio <a href="http://www.bibsonomy.org/author/Loreto">Loreto</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Miranda <a href="http://www.bibsonomy.org/author/Grahl">Grahl</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>AI Communications Journal, Special Issue on &quot;Network Analysis in Natural Sciences and Engineering&quot;</em><em>20(4):245-262</em>(<em>2007</em>)Fri Mar 14 08:51:30 CET 2008AI Communications Journal, Special Issue on "Network Analysis in Natural Sciences and Engineering"4245-262Network Properties of Folksonomies202007network folksonomy property IEEEXplore# Using PersonalizedWeb Search for Enhancing Common Sense and Folksonomy Based Intelligent Search Systemshttp://www.bibsonomy.org/bibtex/2b19748937563c477de5f1b845111d0af/jaeschkejaeschke2008-02-13T10:49:41+01:00search folksonomy web <span style="color:#555555;">Mohammad <a href="http://www.bibsonomy.org/author/Nauman">Nauman</a> und Shahbaz <a href="http://www.bibsonomy.org/author/Khan">Khan</a> </span><em>Web Intelligence, IEEE/WIC/ACM International Conference on, </em><em>Seite423-426. </em>(<em>2007</em>)Wed Feb 13 10:49:41 CET 2008Web Intelligence, IEEE/WIC/ACM International Conference on423-426Using PersonalizedWeb Search for Enhancing Common Sense and Folksonomy Based Intelligent Search Systems2007search folksonomy web A large part of the modern web is characterized by usergenerated content categorized using collaborative tagging or folksonomy. It becomes difficult to search for relevant content because of ambiguity in lexical representation of concepts and variances in preferences of users. With more and more services relying on tags for content categorization, it is important that search techniques evolve to better suit the scenario. A promising approach towards solving these problems is to use machine common sense in conjunction with folksonomy. A past attempt to use this approach has shown positive results in finding relevant content but it does not address the issue of noise in search results. In this paper, we use the personalized web search technique of traditional web search systems to address the issue of irrelevant search results in common sense and folksonomy based search systems. In personalized web search, results are reflective of user's preferences, which are decided by search history and categories of interest. We propose modifications to personalized web search technique. Using this modified approach, we extend the basic common sense and folksonomy based search systems to address the issue of noise in search results.http://www.bibsonomy.org/bibtex/2bfc43dfe59f9c0935ac3364b12e6d795/jaeschkejaeschke2008-01-17T13:52:39+01:00kdml folksonomy recommender l3s 2007 tagging for:nepomuk myown lwa <span style="color:#555555;">Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Leandro <a href="http://www.bibsonomy.org/author/Marinho">Marinho</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Lars <a href="http://www.bibsonomy.org/author/Schmidt-Thieme">Schmidt-Thieme</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivit&#228;t (LWA 2007), </em><em>Seite13-20. </em><em>Martin-Luther-Universit&#228;t Halle-Wittenberg, </em><em>sep2007. </em>Thu Jan 17 13:52:39 CET 2008Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)sep13-20Tag Recommendations in Folksonomies2007kdml folksonomy recommender l3s 2007 tagging for:nepomuk myown lwa 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 present two tag recommendation algorithms: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank, an adaptation of the well-known PageRank algorithm that can cope with undirected triadic hyperedges. We evaluate and compare both algorithms on large-scale real life datasets and 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/2bb8ecec699a2f129322fe334747c6aef/jaeschkejaeschke2008-01-17T13:51:14+01:00folksonomy for:nepomuk wp5 l3s myown tagging recommender 2007 <span style="color:#555555;">Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Leandro Balby <a href="http://www.bibsonomy.org/author/Marinho">Marinho</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Lars <a href="http://www.bibsonomy.org/author/Schmidt-Thieme">Schmidt-Thieme</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, </em><em>Volume4702vonLecture Notes in Computer Science, </em><em>Seite506-514. </em><em>Berlin, Heidelberg, </em><em>Springer, </em>(<em>2007</em>)Thu Jan 17 13:51:14 CET 2008Berlin, 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 Folksonomies47022007folksonomy for:nepomuk wp5 l3s myown tagging recommender 2007 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/20c2b212b9ea3d822bf4729fd5fe6b6e1/jaeschkejaeschke2008-01-17T13:49:53+01:00l3s folksonomy 2007 analysis fca bibsonomy myown iccs trias social bookmarking <span style="color:#555555;">Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007), </em><em>Volume4604vonLecture Notes in Artificial Intelligence, </em><em>Seite283--295. </em><em>Berlin, Heidelberg, </em><em>Springer-Verlag, </em><em>July2007. </em>Thu Jan 17 13:49:53 CET 2008Berlin, HeidelbergProceedings of the 15th International Conference on Conceptual Structures (ICCS 2007)July283--295Lecture Notes in Artificial IntelligenceAnalysis of the Publication Sharing Behaviour in {BibSonomy}46042007l3s folksonomy 2007 analysis fca bibsonomy myown iccs trias social bookmarking BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.http://www.bibsonomy.org/bibtex/25fbd24f07fe8784b516e69b0eb3192f3/jaeschkejaeschke2007-11-16T11:49:53+01:00recommender folksonomy <span style="color:#555555;">Yanfei <a href="http://www.bibsonomy.org/author/Xu">Xu</a> und Liang <a href="http://www.bibsonomy.org/author/Zhang">Zhang</a> und Wei <a href="http://www.bibsonomy.org/author/Liu">Liu</a> </span><em>Frontiers of WWW Research and Development - APWeb 2006</em>(<em>2006</em>)Fri Nov 16 11:49:53 CET 2007Frontiers of WWW Research and Development - APWeb 2006733--738Cubic Analysis of Social Bookmarking for Personalized Recommendation2006recommender folksonomy Personalized recommendation is used to conquer the information overload problem, and collaborative filtering recommendation (CF) is one of the most successful recommendation techniques to date. However, CF becomes less effective when users have multiple interests, because users have similar taste in one aspect may behave quite different in other aspects. Information got from social bookmarking websites not only tells what a user likes, but also why he or she likes it. This paper proposes a division algorithm and a CubeSVD algorithm to analysis this information, distill the interrelations between different users’ various interests, and make better personalized recommendation based on them. Experiment reveals the superiority of our method over traditional CF methods. ER -http://www.bibsonomy.org/bibtex/242cda5911e901eadd0ac6a106a6aa1dc/jaeschkejaeschke2007-10-31T16:04:27+01:00myown 2006 folksonomy trend detection l3s <span style="color:#555555;">Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Proc. First International Conference on Semantics And Digital Media Technology (SAMT), </em><em>Volume4306vonLNCS, </em><em>Seite56-70. </em><em>Heidelberg, </em><em>Springer, </em><em>dec2006. </em>Wed Oct 31 16:04:27 CET 2007HeidelbergProc. First International Conference on Semantics And Digital Media Technology (SAMT) dec56-70LNCSTrend Detection in Folksonomies43062006myown 2006 folksonomy trend detection l3s 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.[0705.1013] Tracking User Attention in Collaborative Tagging Communitieshttp://www.bibsonomy.org/bibtex/2785df87d0942d1cb6da9b944df902730/jaeschkejaeschke2007-09-06T17:17:46+02:00tagging folksonomy collaborative bibsonomy <span style="color:#555555;">Elizeu <a href="http://www.bibsonomy.org/author/Santos-Neto">Santos-Neto</a> und Matei <a href="http://www.bibsonomy.org/author/Ripeanu">Ripeanu</a> und Adriana <a href="http://www.bibsonomy.org/author/Iamnitchi">Iamnitchi</a> </span>(<em>2007</em>)Thu Sep 06 17:17:46 CEST 2007Tracking User Attention in Collaborative Tagging Communities2007tagging folksonomy collaborative bibsonomy dblphttp://www.bibsonomy.org/bibtex/24b0512091911843390f88699d3ea3bb9/jaeschkejaeschke2007-08-09T08:03:23+02:00social knowledge folksonomy <span style="color:#555555;">Harris <a href="http://www.bibsonomy.org/author/Wu">Wu</a> und Mohammad <a href="http://www.bibsonomy.org/author/Zubair">Zubair</a> und Kurt <a href="http://www.bibsonomy.org/author/Maly">Maly</a> </span><em>Hypertext, </em><em>Seite111-114. </em><em>ACM, </em>(<em>2006</em>)Thu Aug 09 08:03:23 CEST 2007Hypertextconf/ht/2006111-114Harvesting social knowledge from folksonomies.2006social knowledge folksonomy http://www.bibsonomy.org/bibtex/22e40f8be9de6920e49f86ec960b7ccc7/jaeschkejaeschke2007-08-08T16:23:05+02:00study bibsonomy social folksonomy tagging <span style="color:#555555;">Katharina <a href="http://www.bibsonomy.org/author/Regulski">Regulski</a> </span>(<em>2007</em>)Wed Aug 08 16:23:05 CEST 2007Aufwand und Nutzen beim Einsatz von Social Bookmarking Services als Nachweisinstrument für wissenschaftliche Forschungsartikel am Beispiel von BibSonomy2007study bibsonomy social folksonomy tagging Authors of scientific article have numerous options to search for background material for their research projects. With our article, we want to show that the use of Social-Bookmarking-Services as part of the web 2.0 (O’Reilly, 2005)/library 2.0 (Danowski, 2006) technology is a useful supplement to conventional reference databases. http://www.bibsonomy.org/bibtex/235842f5deb96573cc24e818697d4bbc8/jaeschkejaeschke2007-07-16T12:51:23+02:00web folksonomy semantic 2007 eswc <span style="color:#555555;">Lucia <a href="http://www.bibsonomy.org/author/Specia">Specia</a> und Enrico <a href="http://www.bibsonomy.org/author/Motta">Motta</a> </span><em>Proceedings of the European Semantic Web Conference (ESWC2007), </em><em>Volume4519vonLNCS, </em><em>Seite624-639. </em><em>Berlin Heidelberg, Germany, </em><em>Springer-Verlag, </em><em>July2007. </em>Mon Jul 16 12:51:23 CEST 2007Berlin Heidelberg, GermanyProceedings of the European Semantic Web Conference (ESWC2007)July624-639LNCSIntegrating Folksonomies with the Semantic Web45192007web folksonomy semantic 2007 eswc While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the Del.icio.us and Flickr tag sets showed that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies, and meaningful relationships among subsets of these tags can be identified.http://www.bibsonomy.org/bibtex/22cbd8e3236adea7c54779605a5aa4fd6/jaeschkejaeschke2007-07-10T16:17:49+02:00iccs bookmarking myown bibsonomy l3s trias_example 2006 social iccs_example folksonomy <span style="color:#555555;">Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Proceedings of the Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures, </em><em>Aalborg, Denmark, </em><em>Aalborg University Press, </em><em>July2006. </em>Tue Jul 10 16:17:49 CEST 2007Aalborg, DenmarkProceedings of the Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual StructuresJuly{BibSonomy}: A Social Bookmark and Publication Sharing System2006iccs bookmarking myown bibsonomy l3s trias_example 2006 social iccs_example folksonomy http://www.bibsonomy.org/bibtex/24440c3ca148004f3759456eac34e84fa/jaeschkejaeschke2007-07-05T14:56:08+02:00analysis folksonomy fca tagging social network formal concept mining <span style="color:#555555;">Hak Lae <a href="http://www.bibsonomy.org/author/Kim">Kim</a> und Suk Hyung <a href="http://www.bibsonomy.org/author/Hwang">Hwang</a> und Hong Gee <a href="http://www.bibsonomy.org/author/Kim">Kim</a> </span><em>SAC '07: Proceedings of the 2007 ACM symposium on Applied computing, </em><em>Seite1340--1345. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2007</em>)Thu Jul 05 14:56:08 CEST 2007New York, NY, USASAC '07: Proceedings of the 2007 ACM symposium on Applied computing1340--1345FCA-based approach for mining contextualized folksonomy2007analysis folksonomy fca tagging social network formal concept mining http://www.bibsonomy.org/bibtex/299ffb0c3a76afe508f5ff6b219f72515/jaeschkejaeschke2007-05-18T11:34:48+02:00visual cloud interface folksonomy tagging tag <span style="color:#555555;">Y. <a href="http://www.bibsonomy.org/author/Hassan-Montero">Hassan-Montero</a> und V. <a href="http://www.bibsonomy.org/author/Herrero-Solana">Herrero-Solana</a> </span><em>Proc. InSciT 2006, </em><em>Merida, Spain, </em><em>Oct2006. </em>Fri May 18 11:34:48 CEST 2007Merida, SpainProc. InSciT 2006Oct{Improving Tag-Clouds as Visual Information Retrieval Interfaces}2006visual cloud interface folksonomy tagging tag 25--28http://www.bibsonomy.org/bibtex/25a9065e96237a69d95edebc03ccac92d/jaeschkejaeschke2007-05-16T09:38:12+02:00folksonomy ontology flickr <span style="color:#555555;">Patrick <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> </span><em>Collaborative Web Tagging Workshop at WWW 2006, </em><em>Edinburgh, Scotland, </em><em>May2006. </em>Wed May 16 09:38:12 CEST 2007Edinburgh, ScotlandCollaborative Web Tagging Workshop at WWW 2006MayInducing Ontology from Flickr Tags.2006folksonomy ontology flickr http://www.bibsonomy.org/bibtex/27f502f47bd0e584190337e3e2d4eba9e/jaeschkejaeschke2007-02-01T14:04:37+01:00l3s iccs_example 2006 folksonomy association trias_example myown rule mining <span style="color:#555555;">Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> und Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Data Science and Classification, </em><em>Seite261--270. </em><em>Berlin, Heidelberg, </em><em>Springer, </em>(<em>2006</em>)Thu Feb 01 14:04:37 CET 2007Berlin, HeidelbergData Science and Classification261--270Studies in Classification, Data Analysis, and Knowledge OrganizationMining Association Rules in Folksonomies2006l3s iccs_example 2006 folksonomy association trias_example myown rule mining http://www.bibsonomy.org/bibtex/205043cc20f1e0f5a612135c970e4f1ac/jaeschkejaeschke2007-02-01T14:04:37+01:00semantic folksonomy 2006 iccs_example bibsonomy trias_example l3s myown emergent <span style="color:#555555;">Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> und Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> und Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> und Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Informatik 2006 - Informatik f&#252;r Menschen. Band 2, </em><em>VolumeP-94vonLecture Notes in Informatics, </em><em>Bonn, </em><em>oct2006. </em><em>Proc. Workshop on Applications of Semantic Technologies, Informatik 2006 . </em>Thu Feb 01 14:04:37 CET 2007BonnInformatik 2006 - Informatik für Menschen. Band 2octProc. Workshop on Applications of Semantic Technologies, Informatik 2006Lecture Notes in InformaticsEmergent Semantics in BibSonomyP-942006semantic folksonomy 2006 iccs_example bibsonomy trias_example l3s myown emergent 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.