PUMA publications for /user/jaeschke/communityhttps://puma.uni-kassel.de/user/jaeschke/communityPUMA RSS feed for /user/jaeschke/community2024-03-19T07:26:39+01:00A Social Mechanism of Reputation Management in Electronic Communitieshttps://puma.uni-kassel.de/bibtex/2337afcb67138b927b27a9687199e8568/jaeschkejaeschke2012-10-11T17:46:32+02:00collaborative community management network quality reputation search social trust web <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bin Yu" itemprop="url" href="/author/Bin%20Yu"><span itemprop="name">B. Yu</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Munindar Singh" itemprop="url" href="/author/Munindar%20Singh"><span itemprop="name">M. Singh</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Cooperative Information Agents IV - The Future of Information Agents in Cyberspace</span>, </em><em>Volume 1860 von Lecture Notes in Computer Science, </em><em><span itemprop="publisher">Springer</span>, </em><em>Berlin/Heidelberg, </em></span>(<em><span>2000<meta content="2000" itemprop="datePublished"/></span></em>)Thu Oct 11 17:46:32 CEST 2012Berlin/HeidelbergCooperative Information Agents IV - The Future of Information Agents in Cyberspace355--393Lecture Notes in Computer ScienceA Social Mechanism of Reputation Management in Electronic Communities18602000collaborative community management network quality reputation search social trust web Trust is important wherever agents must interact. We consider the important case of interactions in electronic communities, where the agents assist and represent principal entities, such as people and businesses. We propose a social mechanism of reputation management, which aims at avoiding interaction with undesirable participants. Social mechanisms complement hard security techniques (such as passwords and digital certificates), which only guarantee that a party is authenticated and authorized, but do not ensure that it exercises its authorization in a way that is desirable to others. Social mechanisms are even more important when trusted third parties are not available. Our specific approach to reputation management leads to a decentralized society in which agents help each other weed out undesirable players.Mapping Community Engagement with Urban Crowd-Sourcinghttps://puma.uni-kassel.de/bibtex/2f0a69ac56b94a471b470ebd56545fafd/jaeschkejaeschke2012-04-26T11:35:36+02:00community computer crowdsourcing sensing social urban <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Desislava Hristova" itemprop="url" href="/author/Desislava%20Hristova"><span itemprop="name">D. Hristova</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Afra Mashhadi" itemprop="url" href="/author/Afra%20Mashhadi"><span itemprop="name">A. Mashhadi</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Giovanni Quattrone" itemprop="url" href="/author/Giovanni%20Quattrone"><span itemprop="name">G. Quattrone</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Licia Capra" itemprop="url" href="/author/Licia%20Capra"><span itemprop="name">L. Capra</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proc. When the City Meets the Citizen Workshop (WCMCW)</span>, </em></span>(<em><span>Juni 2012<meta content="Juni 2012" itemprop="datePublished"/></span></em>)Thu Apr 26 11:35:36 CEST 2012Proc. When the City Meets the Citizen Workshop (WCMCW)junMapping Community Engagement with Urban Crowd-Sourcing2012community computer crowdsourcing sensing social urban Communities of people are better mappers if they are spatially clustered, as revealed in an interesting new paper by Hristova, Mashhadi, Quattrone and Capra from UCL. "This preliminary analysis inspires further inquiry because it shows a clear correlation between spatial affiliation, the internal community structure and the community’s engagement in terms of coverage", according to the authors. They have studied the similarity patterns among eight hundred contributors to OpenStreetMap, the well-known crowdmapping project and detected the hidden community structure. It is a very promising field of research, coupling a social network analysis of crowdsourced data. Participants to such projects are rarely independent individuals: in most cases, they involve communities more than single participants and it would be crucial to uncover how the underlying social structure reflects on the quantity and the quality of the collected data. It has the greatest relevance for citizen science projects, as data quality is often the key issue determining the success or the failure of the collective effort. The Emergence of Social and Community Intelligencehttps://puma.uni-kassel.de/bibtex/283e180e95544a7b35d0914de61e98621/jaeschkejaeschke2012-04-13T10:18:04+02:00cirg collective community computing intelligence social <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Daqing Zhang" itemprop="url" href="/author/Daqing%20Zhang"><span itemprop="name">D. Zhang</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bin Guo" itemprop="url" href="/author/Bin%20Guo"><span itemprop="name">B. Guo</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Zhiwen Yu" itemprop="url" href="/author/Zhiwen%20Yu"><span itemprop="name">Z. Yu</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Computer</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">44 </span></span>(<span itemprop="issueNumber">7</span>):
<span itemprop="pagination">21--28</span></em> </span>(<em><span>Juli 2011<meta content="Juli 2011" itemprop="datePublished"/></span></em>)Fri Apr 13 10:18:04 CEST 2012Computerjul721--28The Emergence of Social and Community Intelligence442011cirg collective community computing intelligence social Social and community intelligence research aims to reveal individual and group behaviors, social interactions, and community dynamics by mining the digital traces that people leave while interacting with Web applications, static infrastructure, and mobile and wearable devices.Publication Analysis of the Formal Concept Analysis Communityhttps://puma.uni-kassel.de/bibtex/29207cd4b1cf7d87c9ae959ac780e152c/jaeschkejaeschke2012-03-05T11:46:01+01:002012 analysis community concept fca formal icfca myown scientometrics <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stephan Doerfel" itemprop="url" href="/author/Stephan%20Doerfel"><span itemprop="name">S. Doerfel</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>, 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">Formal Concept Analysis</span>, </em></span><em>Volume 7278 von Lecture Notes in Artificial Intelligence, </em><em>Seite <span itemprop="pagination">77--95</span>. </em><em>Berlin/Heidelberg, </em><em><span itemprop="publisher">Springer</span>, </em>(<em><span>Mai 2012<meta content="Mai 2012" itemprop="datePublished"/></span></em>)Mon Mar 05 11:46:01 CET 2012Berlin/HeidelbergFormal Concept Analysismay77--95Lecture Notes in Artificial IntelligencePublication Analysis of the Formal Concept Analysis Community727820122012 analysis community concept fca formal icfca myown scientometrics We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history. Modularity and community structure in networkshttps://puma.uni-kassel.de/bibtex/25dd9d0c2155f242393e63547d8a2347f/jaeschkejaeschke2011-12-21T08:52:42+01:00clustering community graph modularity network structure <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="M. E. J. Newman" itemprop="url" href="/author/M.%20E.%20J.%20Newman"><span itemprop="name">M. Newman</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Proceedings of the National Academy of Sciences</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">103 </span></span>(<span itemprop="issueNumber">23</span>):
<span itemprop="pagination">8577--8582</span></em> </span>(<em><span>2006<meta content="2006" itemprop="datePublished"/></span></em>)Wed Dec 21 08:52:42 CET 2011Proceedings of the National Academy of Sciences238577--8582Modularity and community structure in networks1032006clustering community graph modularity network structure Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure is one of the outstanding issues in the study of networked systems. One highly effective approach is the optimization of the quality function known as “modularity” over the possible divisions of a network. Here I show that the modularity can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which I call the modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times. I illustrate the method with applications to several published network data sets.Collecting community wisdom: integrating social search & social navigationhttps://puma.uni-kassel.de/bibtex/293fecd064cd42e0ea5f9dc06a9458d3c/jaeschkejaeschke2011-12-06T11:15:12+01:00community navigation search social <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jill Freyne" itemprop="url" href="/author/Jill%20Freyne"><span itemprop="name">J. Freyne</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Rosta Farzan" itemprop="url" href="/author/Rosta%20Farzan"><span itemprop="name">R. Farzan</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Brusilovsky" itemprop="url" href="/author/Peter%20Brusilovsky"><span itemprop="name">P. Brusilovsky</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Barry Smyth" itemprop="url" href="/author/Barry%20Smyth"><span itemprop="name">B. Smyth</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maurice Coyle" itemprop="url" href="/author/Maurice%20Coyle"><span itemprop="name">M. Coyle</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 12th international conference on Intelligent user interfaces</span>, </em></span><em>Seite <span itemprop="pagination">52--61</span>. </em><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM</span>, </em>(<em><span>2007<meta content="2007" itemprop="datePublished"/></span></em>)Tue Dec 06 11:15:12 CET 2011New York, NY, USAProceedings of the 12th international conference on Intelligent user interfaces52--61Collecting community wisdom: integrating social search \& social navigation2007community navigation search social The goal of this paper is to detail the integration of two "social Web" technologies - social search and social navigation - and to highlight the benefits of such integration on two levels. Firstly, both technologies harvest and harness "community wisdom" and in an integrated system each of the search and navigation components can benefit from the additional community wisdom gathered by the other when assisting users to locate relevant information. Secondly, by integrating search and browsing we facilitate the development of a unique interface that effectively blends search and browsing functionality as part of a seamless social information access service. This service allows users to effectively combine their search and browsing behaviors. In this paper we will argue that this integration provides significantly more than the simple sum of the parts.Visit me, click me, be my friend: an analysis of evidence networks of user relationships in BibSonomyhttps://puma.uni-kassel.de/bibtex/26628bf43e3834ba147a22992f2f534e9/jaeschkejaeschke2010-08-12T15:01:57+02:00bibsonomy collaborative community detection evidence folksonomy network tagging <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Folke Mitzlaff" itemprop="url" href="/author/Folke%20Mitzlaff"><span itemprop="name">F. Mitzlaff</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Dominik Benz" itemprop="url" href="/author/Dominik%20Benz"><span itemprop="name">D. Benz</span></a></span>, <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>, und <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>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">HT '10: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia</span>, </em></span><em>Seite <span itemprop="pagination">265--270</span>. </em><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM</span>, </em>(<em><span>2010<meta content="2010" itemprop="datePublished"/></span></em>)Thu Aug 12 15:01:57 CEST 2010New York, NY, USAHT '10: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia265--270Visit me, click me, be my friend: an analysis of evidence networks of user relationships in BibSonomy2010bibsonomy collaborative community detection evidence folksonomy network tagging The ongoing spread of online social networking and sharing sites has reshaped the way how people interact with each other. Analyzing the relatedness of different users within the resulting large populations of these systems plays an important role for tasks like user recommendation or community detection. Algorithms in these fields typically face the problem that explicit user relationships (like friend lists) are often very sparse. Surprisingly, implicit evidences (like click logs) of user relations have hardly been considered to this end. Based on our long-time experience with running BibSonomy [4], we identify in this paper different evidence networks of user relationships in our system. We broadly classify each network based on whether the links are explicitly established by the users (e.g., friendship or group membership) or accrue implicitly in the running system (e.g., when user u copies an entry of user v). We systematically analyze structural properties of these networks and whether topological closeness (in terms of the length of shortest paths) coincides with semantic similarity between users.Modularity and community detection in bipartite networkshttps://puma.uni-kassel.de/bibtex/261f9d5839845d5d8fa1883a46a2f7744/jaeschkejaeschke2009-03-04T14:18:59+01:00bipartite clustering community detection graph modularity network <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="M. J. Barber" itemprop="url" href="/author/M.%20J.%20Barber"><span itemprop="name">M. Barber</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Physical Review E</em></span></span> </span>(<em><span>2007<meta content="2007" itemprop="datePublished"/></span></em>)Wed Mar 04 14:18:59 CET 2009Physical Review E6Modularity and community detection in bipartite networks762007bipartite clustering community detection graph modularity network The modularity of a network quantifies the extent, relative to a null model network, to which vertices cluster into community groups. We define a null model appropriate for bipartite networks, and use it to define a bipartite modularity. The bipartite modularity is presented in terms of a modularity matrix B; some key properties of the eigenspectrum of B are identified and used to describe an algorithm for identifying modules in bipartite networks. The algorithm is based on the idea that the modules in the two parts of the network are dependent, with each part mutually being used to induce the vertices for the other part into the modules. We apply the algorithm to real-world network data, showing that the algorithm successfully identifies the modular structure of bipartite networks.Module identification in bipartite and directed networkshttps://puma.uni-kassel.de/bibtex/26145a42fe04aee556fa7a68c7cea7db3/jaeschkejaeschke2009-03-04T14:17:17+01:00bipartite clustering community detection graph modularity module network <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="R. Guimerà" itemprop="url" href="/author/R.%20Guimer%7b%5c%60a%7d"><span itemprop="name">R. Guimerà</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="M. Sales-Pardo" itemprop="url" href="/author/M.%20Sales-Pardo"><span itemprop="name">M. Sales-Pardo</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="L.A.N. Amaral" itemprop="url" href="/author/L.A.N.%20Amaral"><span itemprop="name">L. Amaral</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Physical review. E, Statistical, nonlinear, and soft matter physics</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">76 </span></span>(<span itemprop="issueNumber">3 Pt 2</span>):
<span itemprop="pagination">036102</span></em> </span>(<em><span>2007<meta content="2007" itemprop="datePublished"/></span></em>)Wed Mar 04 14:17:17 CET 2009Physical review. E, Statistical, nonlinear, and soft matter physics3 Pt 2036102Module identification in bipartite and directed networks762007bipartite clustering community detection graph modularity module network Modularity is one of the most prominent properties of real-world complex networks. Here, we address the issue of module identification in two important classes of networks: bipartite networks and directed unipartite networks. Nodes in bipartite networks are divided into two non-overlapping sets, and the links must have one end node from each set. Directed unipartite networks only have one type of nodes, but links have an origin and an end. We show that directed unipartite networks can be conviniently represented as bipartite networks for module identification purposes. We report a novel approach especially suited for module detection in bipartite networks, and define a set of random networks that enable us to validate the new approach.Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomieshttps://puma.uni-kassel.de/bibtex/2645abd6b3191a2a6e844d7542651ed1c/jaeschkejaeschke2008-07-12T13:03:47+02:00clustering community detection <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Akshay Java" itemprop="url" href="/author/Akshay%20Java"><span itemprop="name">A. Java</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Anupam Joshi" itemprop="url" href="/author/Anupam%20Joshi"><span itemprop="name">A. Joshi</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tim Finin" itemprop="url" href="/author/Tim%20Finin"><span itemprop="name">T. Finin</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">WebKDD 2008 Workshop on Web Mining and Web Usage Analysis</span>, </em></span>(<em><span>August 2008<meta content="August 2008" itemprop="datePublished"/></span></em>)<em>To Appear.</em>Sat Jul 12 13:03:47 CEST 2008WebKDD 2008 Workshop on Web Mining and Web Usage AnalysisAugustTo AppearDetecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies2008clustering community detection Community detection in complex networks using Extremal Optimizationhttps://puma.uni-kassel.de/bibtex/236d905c5223e5516db9d08eb3e0bc9fc/jaeschkejaeschke2007-05-18T10:42:10+02:00community complex detection network <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="J. Duch" itemprop="url" href="/author/J.%20Duch"><span itemprop="name">J. Duch</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="A. Arenas" itemprop="url" href="/author/A.%20Arenas"><span itemprop="name">A. Arenas</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Physical Review E</em></span></span> </span>(<em><span>2005<meta content="2005" itemprop="datePublished"/></span></em>)Fri May 18 10:42:10 CEST 2007Physical Review E027104Community detection in complex networks using Extremal Optimization722005community complex detection network We propose a novel method to find the community structure in complex networks based on an extremal optimization of the value of modularity. The method outperforms the optimal modularity found by the existing algorithms in the literature. We present the results of the algorithm for computer simulated and real networks and compare them with other approaches. The efficiency and accuracy of the method make it feasible to be used for the accurate identification of community structure in large complex networks.Citebase - Community detection in complex networks using Extremal OptimizationUnterstützung der Formierung und Analyse von virtuellen Communitieshttps://puma.uni-kassel.de/bibtex/2683e13d82b21ff7ebb4afcc20958f762/jaeschkejaeschke2007-05-16T09:18:29+02:00analysis community support toread <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jürgen Hartmut Koch" itemprop="url" href="/author/J%c3%bcrgen%20Hartmut%20Koch"><span itemprop="name">J. Koch</span></a></span>. </span><em>Europäische Hochschulschriften </em><em><span itemprop="publisher">Peter Lang Publishing Group</span>, </em><em>Frankfurt am Main, </em>(<em><span>2003<meta content="2003" itemprop="datePublished"/></span></em>)<em>PhD Thesis (2002).</em>Wed May 16 09:18:29 CEST 2007Frankfurt am MainPhD Thesis (2002)39Europäische HochschulschriftenUnterstützung der Formierung und Analyse von virtuellen Communities412003analysis community support toread Systeme, die den Informationsaustausch in Communities unterstützen, sind heute allgegenwärtig. Eine zielgerichtete Analyse solcher Communities ist allerdings nur schwer möglich, denn es gibt bislang kein Verfahren zur formalen Beschreibung virtueller Communities, auf dem aufbauend eine Analyse stattfinden könnte. Es wird ein Konzept vorgestellt, das die Brücke schlägt zwischen den natürlichsprachlichen Beschreibungen von virtuellen Communities in der Soziologie und der Psychologie, und einer formalen Beschreibung, wie sie für die zielgerichtete Software-Entwicklung nötig ist. Neben einem formalen Modell von virtuellen Communities wird ein komponentenbasierter Ansatz vorgestellt, der beschreibt, wie mit diesem Modell gezielt Unterstützungs- und Analysesysteme entwickelt werden können.Community Space: Toward Flexible Support for Voluntary Knowledge Communitieshttps://puma.uni-kassel.de/bibtex/2a0abdf3ed0cac548f4dd5f8e073b6314/jaeschkejaeschke2007-05-16T09:08:27+02:00community knowledge <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Linda Carotenuto" itemprop="url" href="/author/Linda%20Carotenuto"><span itemprop="name">L. Carotenuto</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="William Etienne" itemprop="url" href="/author/William%20Etienne"><span itemprop="name">W. Etienne</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Fontaine" itemprop="url" href="/author/Michael%20Fontaine"><span itemprop="name">M. Fontaine</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jessica Friedman" itemprop="url" href="/author/Jessica%20Friedman"><span itemprop="name">J. Friedman</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Muller" itemprop="url" href="/author/Michael%20Muller"><span itemprop="name">M. Muller</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Helene Newberg" itemprop="url" href="/author/Helene%20Newberg"><span itemprop="name">H. Newberg</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Matthew Simpson" itemprop="url" href="/author/Matthew%20Simpson"><span itemprop="name">M. Simpson</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jason Slusher" itemprop="url" href="/author/Jason%20Slusher"><span itemprop="name">J. Slusher</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kenneth Stevenson" itemprop="url" href="/author/Kenneth%20Stevenson"><span itemprop="name">K. Stevenson</span></a></span>. </span><em>99-04. </em><em><span itemprop="producer">IBM Watson Research Center</span>, </em>(<em><span>April 1999<meta content="April 1999" itemprop="datePublished"/></span></em>)Wed May 16 09:08:27 CEST 2007April99-04Community Space: Toward Flexible Support for Voluntary Knowledge Communities1999community knowledge In this paper we describe CommunitySpace, a component of a project to support voluntary, electronic communities of practice. We detail some of our design decisions, emphasizing issues of flexibility, diversity, and democracy. These design decisions will have impact upon the user interface to CommunitySpace, but they have much more immediate impact upon the architecture, representation, and dynamics of usage of the system. Our work is in the requirements and design phase, and we are interested in the comments of our peers on our evolving ideas.provides definitions for c. of practice, interest, purpose and passion; highlights the value of c.; how to support c.; stages of c. formationCommunities of Interest: Learning through the Interaction of Multiple Knowledge Systemshttps://puma.uni-kassel.de/bibtex/22b58a1bff72a7440c43786fc4c1493b0/jaeschkejaeschke2007-05-16T09:03:13+02:00community interest knowledge learning practice <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerhard Fischer" itemprop="url" href="/author/Gerhard%20Fischer"><span itemprop="name">G. Fischer</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">24th annual Information Systems Research Seminar in Scandinavia</span>, </em></span><em>Seite <span itemprop="pagination">2001</span>. </em><em>Ulvik, Hardanger Fjord, Norway, </em>(<em><span>August 2001<meta content="August 2001" itemprop="datePublished"/></span></em>)Wed May 16 09:03:13 CEST 2007Ulvik, Hardanger Fjord, Norway24th annual Information Systems Research Seminar in ScandinaviaAugust2001Communities of Interest: Learning through the Interaction of Multiple Knowledge Systems2001community interest knowledge learning practice describes some differences between communities of practice and communities of interest; discusses learning environments for themOrtsbezug in kontext-sensitiven Diensten für mobile Communitieshttps://puma.uni-kassel.de/bibtex/287835f6fce05f443a4956673662734d2/jaeschkejaeschke2007-05-16T08:58:56+02:00community context geo mobile sensitive service <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Georg Groh" itemprop="url" href="/author/Georg%20Groh"><span itemprop="name">G. Groh</span></a></span>. </span><em><span itemprop="educationalUse">8. Münchner Fortbildungsseminar Geoinformationssysteme</span>, </em><em><span itemprop="producer">TU München</span>, </em>(<em><span>März 2003<meta content="März 2003" itemprop="datePublished"/></span></em>)Wed May 16 08:58:56 CEST 2007MarchOrtsbezug in kontext-sensitiven Diensten für mobile Communities8. Münchner Fortbildungsseminar Geoinformationssysteme2003community context geo mobile sensitive service contains some interesting references for definitions of "community"Wege zur Entdeckung von Communities in Folksonomieshttps://puma.uni-kassel.de/bibtex/22b6be3bd5daee7119973fcf69909956f/jaeschkejaeschke2007-02-01T14:04:37+01:002006 community detection folksonomy iccs_example l3s myown trias_example <span class="authorEditorList"><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>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christoph Schmitz" itemprop="url" href="/author/Christoph%20Schmitz"><span itemprop="name">C. Schmitz</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">Proc. 18. Workshop Grundlagen von Datenbanken</span>, </em></span><em>Seite <span itemprop="pagination">80-84</span>. </em><em>Halle-Wittenberg, </em><em><span itemprop="publisher">Martin-Luther-Universität</span>, </em>(<em><span>Juni 2006<meta content="Juni 2006" itemprop="datePublished"/></span></em>)Thu Feb 01 14:04:37 CET 2007Halle-WittenbergProc. 18. Workshop Grundlagen von DatenbankenJune80-84Wege zur Entdeckung von Communities in Folksonomies20062006 community detection folksonomy iccs_example l3s myown trias_example Ein wichtiger Baustein des neu entdeckten World Wide Web -- des "Web 2.0" -- stellen Folksonomies dar. In diesen Systemen können Benutzer gemeinsam Ressourcen verwalten und
mit Schlagwörtern versehen. Die dadurch entstehenden begrifflichen Strukturen stellen ein interessantes Forschungsfeld dar. Dieser Artikel untersucht Ansätze und Wege zur Entdeckung und Strukturierung von Nutzergruppen ("Communities") in Folksonomies.IT-supported Visualization and Evaluation of Virtual Knowledge Communities. Applying Social Network Intelligence Software in Knowledge Management to enable knowledge oriented People Network Managementhttps://puma.uni-kassel.de/bibtex/266eb70a04e6946077182446170dd6dcf/jaeschkejaeschke2006-09-14T08:49:50+02:00social detection knowledge management community network <meta content="thesis" itemprop="educationalUse"/><span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Matthias Trier" itemprop="url" href="/author/Matthias%20Trier"><span itemprop="name">M. Trier</span></a></span>. </span>(<em><span>2005<meta content="2005" itemprop="datePublished"/></span></em>)Thu Sep 14 08:49:50 CEST 2006IT-supported Visualization and Evaluation of Virtual Knowledge Communities. Applying Social Network Intelligence Software in Knowledge Management to enable knowledge oriented People Network Management2005social detection knowledge management community network The author-topic model for authors and documentshttps://puma.uni-kassel.de/bibtex/2a4dd688efe5778fb99ff94de104211aa/jaeschkejaeschke2006-07-27T11:36:09+02:00topicinference social socialnets network community <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michal Rosen-Zvi" itemprop="url" href="/author/Michal%20Rosen-Zvi"><span itemprop="name">M. Rosen-Zvi</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Thomas Griffiths" itemprop="url" href="/author/Thomas%20Griffiths"><span itemprop="name">T. Griffiths</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mark Steyvers" itemprop="url" href="/author/Mark%20Steyvers"><span itemprop="name">M. Steyvers</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Padhraic Smyth" itemprop="url" href="/author/Padhraic%20Smyth"><span itemprop="name">P. Smyth</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 20th conference on Uncertainty in artificial intelligence</span>, </em></span><em>Seite <span itemprop="pagination">487--494</span>. </em><em>Arlington, VA, USA, </em><em><span itemprop="publisher">AUAI Press</span>, </em>(<em><span>2004<meta content="2004" itemprop="datePublished"/></span></em>)Thu Jul 27 11:36:09 CEST 2006Arlington, VA, USAProceedings of the 20th conference on Uncertainty in artificial intelligence487--494The author-topic model for authors and documents2004topicinference social socialnets network community Online Analysis of Community Evolution in Data Streams.https://puma.uni-kassel.de/bibtex/2bb72c8baa786e98565c4a7448ecae59a/jaeschkejaeschke2006-05-16T12:18:19+02:00data detection stream analysis community <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Charu C. Aggarwal" itemprop="url" href="/author/Charu%20C.%20Aggarwal"><span itemprop="name">C. Aggarwal</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Philip S. Yu" itemprop="url" href="/author/Philip%20S.%20Yu"><span itemprop="name">P. Yu</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">SDM</span>, </em></span>(<em><span>2005<meta content="2005" itemprop="datePublished"/></span></em>)Tue May 16 12:18:19 CEST 2006SDMOnline Analysis of Community Evolution in Data Streams.2005data detection stream analysis community Design and evaluation of a user-based community discovery techniquehttps://puma.uni-kassel.de/bibtex/241d2e7ad7417153fa5cb257486468919/jaeschkejaeschke2006-05-16T12:15:36+02:00detection hits community network <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="R.B. Almeida" itemprop="url" href="/author/R.B.%20Almeida"><span itemprop="name">R. Almeida</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="V.A.F. Almeida" itemprop="url" href="/author/V.A.F.%20Almeida"><span itemprop="name">V. Almeida</span></a></span>. </span>(<em><span>2003<meta content="2003" itemprop="datePublished"/></span></em>)Tue May 16 12:15:36 CEST 2006Proceedings of the 4th International Conference on Internet Computing17--23Design and evaluation of a user-based community discovery technique2003detection hits community network