http://www.bibsonomy.org/burst/tag/communityBibSonomy BuRST Feed for /tag/community2008-07-21T00:36:28+02:00http://www.bibsonomy.org/bibtex/2645abd6b3191a2a6e844d7542651ed1c/jaeschkejaeschke2008-07-12T13:03:47+02:00detection clustering community <span style="color:#555555;">Akshay <a href="http://www.bibsonomy.org/author/Java">Java</a> and Anupam <a href="http://www.bibsonomy.org/author/Joshi">Joshi</a> and Tim <a href="http://www.bibsonomy.org/author/Finin">Finin</a> </span><em>WebKDD 2008 Workshop on Web Mining and Web Usage Analysis, </em><em>August2008. </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 Folksonomies2008detection clustering community http://www.bibsonomy.org/bibtex/2645abd6b3191a2a6e844d7542651ed1c/hothohotho2008-07-12T12:19:07+02:00clusterig folksonomy detection toread community <span style="color:#555555;">Akshay <a href="http://www.bibsonomy.org/author/Java">Java</a> and Anupam <a href="http://www.bibsonomy.org/author/Joshi">Joshi</a> and Tim <a href="http://www.bibsonomy.org/author/Finin">Finin</a> </span><em>WebKDD 2008 Workshop on Web Mining and Web Usage Analysis, </em><em>August2008. </em><em>To Appear . </em>Sat Jul 12 12:19:07 CEST 2008WebKDD 2008 Workshop on Web Mining and Web Usage AnalysisAugustTo Appear{Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies}2008clusterig folksonomy detection toread community dblphttp://www.bibsonomy.org/bibtex/201b437bb0bd72b0a99a9d30621b36f54/anaappelanaappel2008-07-09T20:25:58+02:00community networks. <span style="color:#555555;">Jure <a href="http://www.bibsonomy.org/author/Leskovec">Leskovec</a> and Kevin J. <a href="http://www.bibsonomy.org/author/Lang">Lang</a> and Anirban <a href="http://www.bibsonomy.org/author/Dasgupta">Dasgupta</a> and Michael W. <a href="http://www.bibsonomy.org/author/Mahoney">Mahoney</a> </span><em>WWW, </em><em>page695-704. </em><em>ACM, </em>(<em>2008</em>)Wed Jul 09 20:25:58 CEST 2008WWWconf/www/2008695-704Statistical properties of community structure in large social and information networks.2008community networks. http://www.bibsonomy.org/bibtex/2309e09e58dd9b8914dd5f19fda7e6a76/mkroellmkroell2008-07-08T02:11:05+02:00community LinearAlgebra clustering toread structure temporal <span style="color:#555555;">Yun <a href="http://www.bibsonomy.org/author/Chi">Chi</a> and Shenghuo <a href="http://www.bibsonomy.org/author/Zhu">Zhu</a> and Xiaodan <a href="http://www.bibsonomy.org/author/Song">Song</a> and Junichi <a href="http://www.bibsonomy.org/author/Tatemura">Tatemura</a> and Belle L. <a href="http://www.bibsonomy.org/author/Tseng">Tseng</a> </span><em>KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, </em><em>page163--172. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2007</em>)Tue Jul 08 02:11:05 CEST 2008New York, NY, USAKDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining163--172Structural and temporal analysis of the blogosphere through community factorization2007community LinearAlgebra clustering toread structure temporal http://www.bibsonomy.org/bibtex/2fe83d441d95c2f8ddd83fb9c4903cb4e/flint63flint632008-07-07T13:47:29+02:00v0805 interaction software application paper web community user ieee <span style="color:#555555;">Alfred C. <a href="http://www.bibsonomy.org/author/Weaver">Weaver</a> and Benjamin B. <a href="http://www.bibsonomy.org/author/Morrison">Morrison</a> </span><em>Computer</em><em>41(2):97-100</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Computer297-100Social Networking412008v0805 interaction software application paper web community user ieee The mass adoption of social-networking websites points to an evolution in human social interaction.http://www.bibsonomy.org/bibtex/267da4a697e8c8a191c2650efb69a6cb5/flint63flint632008-07-07T13:47:29+02:00v0805 web semantic paper management community ieee mobile device ai information <span style="color:#555555;">Rudi <a href="http://www.bibsonomy.org/author/Studer">Studer</a> and Anupriya <a href="http://www.bibsonomy.org/author/Ankolekar">Ankolekar</a> and Pascal <a href="http://www.bibsonomy.org/author/Hitzler">Hitzler</a> and York <a href="http://www.bibsonomy.org/author/Sure">Sure</a> </span><em>Intelligent Systems</em><em>21(4):8-9</em>(<em>2006</em>)Mon Jul 07 13:47:29 CEST 2008Intelligent Systems48-9A Semantic Future for AI212006v0805 web semantic paper management community ieee mobile device ai information Computing must become much more human centered--for example, by presenting personalized information to users and by respecting personal preferences when controlling multiple devices or invoking various services. Appropriate representation of the information's semantics and of the functionality of devices and services will be critical to such personalized computing. Symbolic artificial intelligence techniques provide the method of choice for the required semantic-representation and reasoning capabilities.http://www.bibsonomy.org/bibtex/28719535a1e41f0e09be8d18063ac0707/flint63flint632008-07-07T13:47:29+02:00knowledge book web v0805 adaptive software user recognition python management development community data ai pattern application <span style="color:#555555;">Toby <a href="http://www.bibsonomy.org/author/Segaran">Segaran</a> </span><em>O'Reilly, </em><em>Sebastopol, CA, USA, </em>(<em>2007</em>)Mon Jul 07 13:47:29 CEST 2008Sebastopol, CA, USAProgramming Collective Intelligence: Building Smart Web 2.0 Applications2007knowledge book web v0805 adaptive software user recognition python management development community data ai pattern application Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build web applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.http://www.bibsonomy.org/bibtex/2dddb0ddc7d53e1d03a2d21bb71c22f63/flint63flint632008-07-07T13:47:29+02:00application book web development ai adaptive v0805 management recognition user community data pattern python software knowledge <span style="color:#555555;">Toby <a href="http://www.bibsonomy.org/author/Segaran">Segaran</a> </span><em>O'Reilly, </em><em>K&#246;ln, </em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Köln{Kollektive Intelligenz analysieren, programmieren und nutzen}2008application book web development ai adaptive v0805 management recognition user community data pattern python software knowledge Sie wollen wissen, wie Rankings, Produktempfehlungen, Social Bookmarking und Online-Partnerbörsen technisch funktionieren? Dieses faszinierende Buch zeigt Ihnen, wie Sie Web 2.0-Applikationen bauen, mit denen Sie die riesigen Datenmengen durchsuchen und analysieren können, die von den Benutzern aktueller Webanwendungen täglich erzeugt werden. Es nimmt Sie mit in die Welt des maschinellen Lernens und der Statistik und erklärt, wie Sie Schlussfolgerungen aus User Experience, persönlichen Vorlieben und menschlichem Verhalten ziehen. Mit den ausgereiften Algorithmen in diesem Buch können Sie raffinierte Programme schreiben, mit denen Sie auf die "kollektive Intelligenz" der Website-Nutzer zugreifen können. Behandelt werden beispielsweise kollaborative Filtertechniken, Cluster-Methoden, Optimierungs-Algorithmen, das Bayes'sche Filtern oder Support-Vektor-Maschinen. Jeder Algorithmus ist kurz und prägnant durch Code beschrieben, den Sie direkt für Ihr Website-Projekt nutzen können.http://www.bibsonomy.org/bibtex/29379b41b7746768aeadfa5ea28fac4f6/flint63flint632008-07-07T13:47:29+02:00ieee wiki tagging blog software newsfeeds community web v0805 paper bookmark application <span style="color:#555555;">San <a href="http://www.bibsonomy.org/author/Murugesan">Murugesan</a> </span><em>IT Professional</em><em>9(4):34-41</em>(<em>2007</em>)Mon Jul 07 13:47:29 CEST 2008IT Professional434-41Understanding Web 2.092007ieee wiki tagging blog software newsfeeds community web v0805 paper bookmark application Web 2.0, the second phase in the Web's evolution, is attracting the attention of IT professionals, businesses, and Web users. Web 2.0 is also called the wisdom Web, people-centric Web, participative Web, and read/write Web. Web 2.0 harnesses the Web in a more interactive and collaborative manner, emphasizing peers' social interaction and collective intelligence, and presents new opportunities for leveraging the Web and engaging its users more effectively. Within the last two to three years, Web 2.0, ignited by successful Web 2.0 based social applications such as MySpace, Flickr, and YouTube, has been forging new applications that were previously unimaginable.http://www.bibsonomy.org/bibtex/202a122a03ba283e0b1678f4d13a8647a/flint63flint632008-07-07T13:47:29+02:00web ai community ontology tagging semantic bookmark software paper v0805 <span style="color:#555555;">Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> and Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> and Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> and Bernhard <a href="http://www.bibsonomy.org/author/Ganter">Ganter</a> and Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>Web Semantics</em><em>6(1):38-53</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics138-53Discovering Shared Conceptualizations in Folksonomies62008web ai community ontology tagging semantic bookmark software paper v0805 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/261090f22121de65626e62645cb1df240/flint63flint632008-07-07T13:47:29+02:00ai semantic management knowledge data software community v0805 processing ontology paper web <span style="color:#555555;">James <a href="http://www.bibsonomy.org/author/Hendler">Hendler</a> and Jennifer <a href="http://www.bibsonomy.org/author/Golbeck">Golbeck</a> </span><em>Web Semantics</em><em>6(1):14-20</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics114-20Metcalfe's Law, Web 2.0, and the Semantic Web62008ai semantic management knowledge data software community v0805 processing ontology paper web The power of the Web is enhanced through the network effect produced as resources link to each other with the value determined by Metcalfe's law. In Web 2.0 applications, much of that effect is delivered through social linkages realized via social networks online. Unfortunately, the associated semantics for Web 2.0 applications, delivered through tagging, is generally minimally hierarchical and sparsely linked. The Semantic Web suffers from the opposite problem. Semantic information, delivered through ontologies of varying amounts of expressivity, is linked to other terms (within or between resources) creating a link space in the semantic realm. However, the use of the Semantic Web has yet to fully realize the social schemes that provide the network of users. In this article, we discuss putting these together, with linked semantics coupled to linked social networks, to deliver a much greater effect.http://www.bibsonomy.org/bibtex/2477a34a49d6691944088021b066afe8a/flint63flint632008-07-07T13:47:29+02:00assist community data semantic v0805 rdf management web ai software paper <span style="color:#555555;">Tom <a href="http://www.bibsonomy.org/author/Heath">Heath</a> and Enrico <a href="http://www.bibsonomy.org/author/Motta">Motta</a> </span><em>Web Semantics</em><em>6(1):76-83</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics176-83Ease of Interaction plus Ease of Integration: Combining Web 2.0 and the Semantic Web in a Reviewing Site62008assist community data semantic v0805 rdf management web ai software paper Web 2.0 has enabled contributions to the Web on an unprecedented scale, through simple interfaces that provide engaging interactions. This wealth of data has spawned countless mashups that integrate heterogenous information, but using techniques that will not scale beyond a handful of sources. In contrast, the Semantic Web provides the key to large-scale data integration, yet still lacks approachable interfaces allowing contributions from non-specialists. In this paper we present Revyu, a reviewing and rating site in the Web 2.0 mould that is built on Semantic Web infrastructure and both publishes and consumes linked RDF data. This combination of approaches affords ease of interaction for regular users and ease of integration with external data sources.http://www.bibsonomy.org/bibtex/24ae270f8cb972f3a955b34c8cb8281fb/flint63flint632008-07-07T13:47:29+02:00v0805 management software semantic processing ontology community paper knowledge web data ai <span style="color:#555555;">Thomas R. <a href="http://www.bibsonomy.org/author/Gruber">Gruber</a> </span><em>Web Semantics</em><em>6(1):4-13</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics14-13Collective Knowledge Systems: Where the Social Web Meets the Semantic Web62008v0805 management software semantic processing ontology community paper knowledge web data ai What can happen if we combine the best ideas from the Social Web and Semantic Web? The Social Web is an ecosystem of participation, where value is created by the aggregation of many individual user contributions. The Semantic Web is an ecosystem of data, where value is created by the integration of structured data from many sources. What applications can best synthesize the strengths of these two approaches, to create a new level of value that is both rich with human participation and powered by well-structured information? This paper proposes a class of applications called collective knowledge systems, which unlock the collective intelligence of the Social Web with knowledge representation and reasoning techniques of the Semantic Web.http://www.bibsonomy.org/bibtex/2535799ca036857535cfcebe5717cee1d/flint63flint632008-07-07T13:47:29+02:00knowledge web semantic v0805 paper management wiki ai data community software processing <span style="color:#555555;">Michel <a href="http://www.bibsonomy.org/author/Buffa">Buffa</a> and Fabien <a href="http://www.bibsonomy.org/author/Gandon">Gandon</a> and Guillaume <a href="http://www.bibsonomy.org/author/Ereteo">Ereteo</a> and Peter <a href="http://www.bibsonomy.org/author/Sander">Sander</a> and Catherine <a href="http://www.bibsonomy.org/author/Faron">Faron</a> </span><em>Web Semantics</em><em>6(1):84-97</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics184-97{SweetWiki:} A Semantic Wiki62008knowledge web semantic v0805 paper management wiki ai data community software processing Everyone agrees that user interactions and social networks are among the cornerstones of Web 2.0. Web 2.0 applications generally run in a web browser, propose dynamic content with rich user interfaces, offer means to easily add or edit content of the web site they belong to and present social network aspects. Well-known applications that have helped spread Web 2.0 are blogs, wikis, and image/video sharing sites; they have dramatically increased sharing and participation among web users. It is possible to build knowledge using tools that can help analyze users’ behavior behind the scenes: what they do, what they know, what they want. Tools that help share this knowledge across a network, and that can reason on that knowledge, will lead to users who can better use the knowledge available, i.e., to smarter users. Wikipedia, a wildly successful example of web technology, has helped knowledge-sharing between people by letting individuals freely create and modify its content. But Wikipedia is designed for people---today's software cannot understand and reason on Wikipedia's content. In parallel, the semantic web, a set of technologies that help knowledge-sharing across the web between different applications, is starting to gain attraction. Researchers have only recently started working on the concept of a semantic wiki, mixing the advantages of the wiki and the technologies of the semantic web. In this paper we will present a state-of-the-art of semantic wikis, and we will introduce SweetWiki, an example of an application reconciling two trends of the future web: a semantically augmented web and a web of social applications where every user is an active provider as well as a consumer of information. SweetWiki makes heavy use of semantic web concepts and languages, and demonstrates how the use of such paradigms can improve navigation, search, and usability.http://www.bibsonomy.org/bibtex/2cd57c91799de60c437e8cf61282efd7a/flint63flint632008-07-07T13:47:29+02:00semantic ai software knowledge data rdf management v0805 web ontology paper community processing <span style="color:#555555;">Uldis <a href="http://www.bibsonomy.org/author/Bojars">Bojars</a> and John G. <a href="http://www.bibsonomy.org/author/Breslin">Breslin</a> and Aidan <a href="http://www.bibsonomy.org/author/Finn">Finn</a> and Stefan <a href="http://www.bibsonomy.org/author/Decker">Decker</a> </span><em>Web Semantics</em><em>6(1):21-28</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics121-28Using the Semantic Web for Linking and Reusing Data across Web 2.0 Communities62008semantic ai software knowledge data rdf management v0805 web ontology paper community processing Large volumes of content (bookmarks, reviews, videos, etc.) are currently being created on the Social Web, i.e. on Web 2.0 community sites, and this content is being annotated and commented upon. The ability to view an individual's entire contribution to the Social Web would be an interesting and valuable service, particularly important as social networks are often being formed through created content and things that people have in common (object-centred sociality). SIOC is a Semantic Web research project that aims to describe online communities on the Social Web. This paper describes how SIOC and the Semantic Web can enable linking and reuse scenarios of data from Web 2.0 community sites, and introduces a SIOC Types module to further specify the type of content items and act as a ´glue¡ between user posts and the content items created and annotated by users.http://www.bibsonomy.org/bibtex/23a93d226a46750e3882ee11851d6a9ae/flint63flint632008-07-07T13:47:29+02:00community rdf web software v0805 service retrieval rest paper semantic knowledge ai <span style="color:#555555;">Robert <a href="http://www.bibsonomy.org/author/Battle">Battle</a> and Edward <a href="http://www.bibsonomy.org/author/Benson">Benson</a> </span><em>Web Semantics</em><em>6(1):61-69</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics161-69Bridging the semantic Web and Web 2.0 with {Representational State Transfer (REST)}62008community rdf web software v0805 service retrieval rest paper semantic knowledge ai Semantic Web technologies must integrate with Web 2.0 services for both to leverage each others strengths. We argue that the REST-based design methodologies of the web present the ideal mechanism through which to align the publication of semantic data with the existing web architecture. We present the design and implementation of two solutions that combine REST-based design and RDF data access: one solution for integrating existing web services and one server-side solution for creating RDF REST services. Both of these solutions enable SPARQL to be a unifying data access layer for aligning the Semantic Web and Web 2.0.http://www.bibsonomy.org/bibtex/2ed40207f9bcd0b34cb5dae63a02e3ced/flint63flint632008-07-07T13:47:29+02:00ontology ai v0805 knowledge management community processing data web semantic blog software paper <span style="color:#555555;">Anupriya <a href="http://www.bibsonomy.org/author/Ankolekar">Ankolekar</a> and Markus <a href="http://www.bibsonomy.org/author/Krötzsch">Kr&#246;tzsch</a> and Thanh <a href="http://www.bibsonomy.org/author/Tran">Tran</a> and Denny <a href="http://www.bibsonomy.org/author/Vrande{\v{c}}i{\&#039;c}">Vrandevci'c</a> </span><em>Web Semantics</em><em>6(1):70-75</em>(<em>2008</em>)Mon Jul 07 13:47:29 CEST 2008Web Semantics170-75The Two Cultures: Mashing up Web 2.0 and the Semantic Web62008ontology ai v0805 knowledge management community processing data web semantic blog software paper A common perception is that there are two competing visions for the future evolution of the Web: the Semantic Web and Web 2.0. A closer look, though, reveals that the core technologies and concerns of these two approaches are complementary and that each field can and must draw from the other’s strengths. We believe that future Web applications will retain the Web 2.0 focus on community and usability, while drawing on Semantic Web infrastructure to facilitate mashup-like information sharing. However, there are several open issues that must be addressed before such applications can become commonplace. In this paper, we outline a semantic weblogs scenario that illustrates the potential for combining Web 2.0 and Semantic Web technologies, while highlighting the unresolved issues that impede its realization. Nevertheless, we believe that the scenario can be realized in the short-term. We point to recent progress made in resolving each of the issues as well as future research directions for each of the communities.http://www.bibsonomy.org/bibtex/296abfa5b8e09fde21a1faa654ec47d6a/flint63flint632008-07-07T13:47:29+02:00ai user management web interface community v0805 software knowledge paper springer semantic interaction adaptive <span style="color:#555555;">Amy <a href="http://www.bibsonomy.org/author/Soller">Soller</a> </span><em>The Adaptive Web: Methods and Strategies of Web Personalization, </em><em>volume4321ofLecture Notes in Computer Science, </em><em>chapter 19, </em><em>Springer, </em><em>Berlin, Heidelberg, </em>(<em>2007</em>)Mon Jul 07 13:47:29 CEST 2008Berlin, HeidelbergThe Adaptive Web: Methods and Strategies of Web Personalization19BrusilovskyKobsaNejdl2007573-595Lecture Notes in Computer ScienceAdaptive Support for Distributed Collaboration43212007ai user management web interface community v0805 software knowledge paper springer semantic interaction adaptive Through interaction with others, a person develops multiple perspectives that become the basis for innovation and the construction of new knowledge. This chapter discusses the challenges facing emerging web-based technologies that enable distributed users to discover and construct new knowledge collaboratively. Examples include advanced collaborative and social information filtering technology that not only helps users discover knowledge, peers, and relevant communities, but also plays a powerful role in facilitating and mediating their interaction. As the internet extends around the world and interconnects diverse cultures, the adaptive web will be challenged to provide a personalized knowledge interface that carries new perspectives to diverse communities. It will play the role of an interface for knowledge construction, a mediator for communication and understanding, and a structured channel through which knowledge is created, interpreted, used, and recreated by other users.http://www.bibsonomy.org/bibtex/21c611c2e32fb3b735c3adcd413e95201/flint63flint632008-07-07T13:47:29+02:00user assist application community web springer management information adaptive v0805 paper ai <span style="color:#555555;">J. <a href="http://www.bibsonomy.org/author/Ben Schafer">Ben Schafer</a> and Dan <a href="http://www.bibsonomy.org/author/Frankowski">Frankowski</a> and Jon <a href="http://www.bibsonomy.org/author/Herlocker">Herlocker</a> and Shilad <a href="http://www.bibsonomy.org/author/Sen">Sen</a> </span><em>The Adaptive Web: Methods and Strategies of Web Personalization, </em><em>volume4321ofLecture Notes in Computer Science, </em><em>chapter 9, </em><em>Springer, </em><em>Berlin, Heidelberg, </em>(<em>2007</em>)Mon Jul 07 13:47:29 CEST 2008Berlin, HeidelbergThe Adaptive Web: Methods and Strategies of Web Personalization9BrusilovskyKobsaNejdl2007291-324Lecture Notes in Computer ScienceCollaborative Filtering Recommender Systems43212007user assist application community web springer management information adaptive v0805 paper ai One of the potent personalization technologies powering the adaptive web is collaborative filtering. Collaborative filtering (CF) is the process of filtering or evaluating items through the opinions of other people. CF technology brings together the opinions of large interconnected communities on the web, supporting filtering of substantial quantities of data. In this chapter we introduce the core concepts of collaborative filtering, its primary uses for users of the adaptive web, the theory and practice of CF algorithms, and design decisions regarding rating systems and acquisition of ratings. We also discuss how to evaluate CF systems, and the evolution of rich interaction interfaces. We close the chapter with discussions of the challenges of privacy particular to a CF recommendation service and important open research questions in the field.http://www.bibsonomy.org/bibtex/2f916c6e3db74930384278976806c3c99/flint63flint632008-07-07T13:47:29+02:00web ai adaptive team springer information v0805 assist paper management semantic community <span style="color:#555555;">Anthony <a href="http://www.bibsonomy.org/author/Jameson">Jameson</a> and Barry <a href="http://www.bibsonomy.org/author/Smyth">Smyth</a> </span><em>The Adaptive Web: Methods and Strategies of Web Personalization, </em><em>volume4321ofLecture Notes in Computer Science, </em><em>chapter 20, </em><em>Springer, </em><em>Berlin, Heidelberg, </em>(<em>2007</em>)Mon Jul 07 13:47:29 CEST 2008Berlin, HeidelbergThe Adaptive Web: Methods and Strategies of Web Personalization20BrusilovskyKobsaNejdl2007596-627Lecture Notes in Computer ScienceRecommendation to Groups43212007web ai adaptive team springer information v0805 assist paper management semantic community Recommender systems have traditionally recommended items to individual users, but there has recently been a proliferation of recommenders that address their recommendations to groups of users. The shift of focus from an individual to a group makes more of a difference than one might at first expect. This chapter discusses the most important new issues that arise, organizing them in terms of four subtasks that can or must be dealt with by a group recommender: 1. acquiring information about the user’s preferences; 2. generating recommendations; 3. explaining recommendations; and 4. helping users to settle on a final decision. For each issue, we discuss how it has been dealt with in existing group recommender systems and what open questions call for further research.