Abstract
Social networks are increasingly used to exchange information. The social users are the main origin of the shared web resources and contents. However, they are also influenced by these shared data. The exchanges and interactions produced are an important element for defining the profiles of these users. In this paper, we investigate modeling of individuals using a user-centered model, in particular the activity and social pressure features. We propose a user profile enrichment approach based on extracted tags from shared resources. Our goal is to link similar users in order to build sub-networks according to users’ profiles. Thus, determining the central and important nodes in the network will establish basis for the web resources recommendation, information diffusion and community resuscitation. Our research will interest doctors’ communities to share their knowledge through network. It will teach the most basic health care information to the patients of certain chronic diseases such as diabetes.
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Hafidi, M., Abdelwahed, E.H., Qassimi, S., Lamrani, R. (2019). Clustering and Social Recommendation Applied in Health Community of Practice. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2018). AI2SD 2018. Advances in Intelligent Systems and Computing, vol 914. Springer, Cham. https://doi.org/10.1007/978-3-030-11884-6_7
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DOI: https://doi.org/10.1007/978-3-030-11884-6_7
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