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- item-1 hasContent gema-bello-orgaz.
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- item-2 hasContent david-f-barrero.
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- item-3 hasContent david-camacho.
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- item-4 hasContent maria-d-r-moreno.
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- 11 creator christophe-gravier.
- 11 creator muhammad-fahad.
- 11 creator olivier-boissier.
- 11 creator pierre-maret.
- 11 type InProceedings.
- 11 label "Smart Places: Multi-Agent based Virtual Community Management System".
- 11 sameAs 11.
- 11 abstract "Virtual Communities (VC) are synergetic digital spaces to build collaborations and exchange knowledge between people sharing similar interests or goals. They respond to human needs such as information sharing, friendship, and recreation. In this paper, we present a VC Management System, based on a Multi-Agent Oriented Programming (MAOP) approach. Using the MAOP JaCaMo platform, we make possible to install a decentralized and open management of those communities in a context of smart cities. Participants of a virtual community are each supported by a Jason agent that encapsulates the logic and the control of the user participation to a VC (such as publishing posts, notifying members, etc.). A set of CArtAgO artifacts provides the basic functionalities and operations giving access to the basic functionalities for knowledge exchange in such VC. Agents can exploit those artifacts to execute their tasks while achieving their individual and collective goals. The global coordination strategies enforcing behaviors of the participants of a VC are expressed as multi-agent normative organizations managed by the Moise framework.".
- 11 hasAuthorList authorList.
- 11 isPartOf proceedings.
- 11 keyword "Cartago".
- 11 keyword "Information Exchange".
- 11 keyword "JaCaMo".
- 11 keyword "Jason".
- 11 keyword "Multi-Agent programming".
- 11 keyword "Virtual communities".
- 11 title "Smart Places: Multi-Agent based Virtual Community Management System".
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- item-1 hasContent muhammad-fahad.
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- item-2 hasContent olivier-boissier.
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- item-4 hasContent christophe-gravier.
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- 3 creator ning-zhong.
- 3 creator xu-ren.
- 3 creator yan-wang.
- 3 creator yi-zeng.
- 3 type InProceedings.
- 3 label "User Interests Driven Web Personalization Based on Multiple Social Networks".
- 3 sameAs 3.
- 3 abstract "User related data indicate user interests in a certain environment. In the context of massive data from the Web, if an application wants to provide more personalized service (e.g. search) for users, an investigation on user interests is needed. User interests are usually distributed in different sources. In order to provide a more comprehensive understanding, user related data from multiple sources need to be integrated together for deeper analysis. Web based social networks have become typical platforms for extracting user interests. In addition, there are various types of interests from these social networks. In this paper, we provide an algorithmic framework for retrieving semantic data based on user interests from multiple sources (such as multiple social networking sites). We design several algorithms to deal with interests based retrieval based on single and multiple types of interests. We utilize publication data from Semantic Web Dog Food (which can be considered as an academic collaboration based social network), and microblogging data from Twitter to validate our framework. The Active Academic Visit Recommendation Application (AAVRA) are developed as a concrete usecase to show the potential effectiveness of the proposed framework for user interests driven Web personalization based on multiple social networks.".
- 3 hasAuthorList authorList.
- 3 isPartOf proceedings.
- 3 keyword "Web personalization".
- 3 keyword "interest analysis".
- 3 keyword "search refinement".
- 3 title "User Interests Driven Web Personalization Based on Multiple Social Networks".
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- item-1 hasContent yi-zeng.
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- item-2 hasContent ning-zhong.
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- item-3 hasContent xu-ren.
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- 4 creator frederic-amblard.
- 4 creator leguistin-maud.
- 4 creator remy-cazabet.
- 4 type InProceedings.
- 4 label "Automated Community Detection on Social Networks: Useful ? Efficient ? Asking the users".
- 4 sameAs 4.
- 4 abstract "In most online social networks, with the increasing num- ber of users and content, the problem of contact filtering becomes more and more present. Either to find the most in- teresting publications, or to control the diffusion of their own information, users need do distinguish between several cate- gories of contacts. The recent introduction of such features in online social networks – for instance, Circles in Google+ or Facebook Smart lists – shows that it is a problem they are confronted to. In this paper, we explore this question through multidisciplinary aspects. First, we discuss about this issue of groups management in the context of social net- works, relying on sociological studies and results of a survey done to a panel of Facebook users. Then, we present sev- eral techniques from the state of the art to automatically find meaningful groups of contacts in a user’s contact list. Finally, we asked Facebook users to evaluate these solutions on their own Facebook network, both to compare the so- lutions among themselves and to assess how pertinent the best ones are according to them. The conclusions of this study are, on the one hand, that few people use existing group management tools on Facebook, whereas they deem it necessary to differentiate their communication depending on their audience. On the other hand, the study shows that a network analysis approach can strongly improve the ef- ficiency of an automated detection of groups on networks, which could be used, combined with profile data extraction, to design intelligent management of groups of contacts.".
- 4 hasAuthorList authorList.
- 4 isPartOf proceedings.
- 4 keyword "community detection".
- 4 keyword "groups of friends".
- 4 keyword "social networks".
- 4 title "Automated Community Detection on Social Networks: Useful ? Efficient ? Asking the users".