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Structural Coupling in Web 2.0 Applications


Affiliations
1 Department of Computer Science, Notre Dame University Louaize, Lebanon
 

The evolution of the Web and its applications has undergone in the last few years a mutation towards technologies that include the social dimension as a first class entity in which the users, their interactions and the emerging social networks are the center of this evolution. The web is growing and evolving the intelligibility of its resources and data, the connectivity of its parts and its autonomy as a whole system. The social dimension of the current and future web is being at the ischolar_mains of its dynamics and evolution. It is thus, fundamental to propose new underlying infrastructure to the web and applications on the web, to make more explicit this social dimension and facilitate its exploitation. The work presented is this paper contributes to this initiative by proposing a multi-agent modeling based on the system coupling to its environment through its social dimension. Applied to a collaborative tagging system, the exploitation of the social dimension of tagging allows an intelligent and better sharing of resources and enhancing social learning between users.

Keywords

Multi-Agent Systems, Collaborative Tagging Systems, Social Learning.
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  • Structural Coupling in Web 2.0 Applications

Abstract Views: 211  |  PDF Views: 113

Authors

Maya Samaha Rupert
Department of Computer Science, Notre Dame University Louaize, Lebanon

Abstract


The evolution of the Web and its applications has undergone in the last few years a mutation towards technologies that include the social dimension as a first class entity in which the users, their interactions and the emerging social networks are the center of this evolution. The web is growing and evolving the intelligibility of its resources and data, the connectivity of its parts and its autonomy as a whole system. The social dimension of the current and future web is being at the ischolar_mains of its dynamics and evolution. It is thus, fundamental to propose new underlying infrastructure to the web and applications on the web, to make more explicit this social dimension and facilitate its exploitation. The work presented is this paper contributes to this initiative by proposing a multi-agent modeling based on the system coupling to its environment through its social dimension. Applied to a collaborative tagging system, the exploitation of the social dimension of tagging allows an intelligent and better sharing of resources and enhancing social learning between users.

Keywords


Multi-Agent Systems, Collaborative Tagging Systems, Social Learning.