Abstract
In this paper, we propose a novel data model for Multimedia Social Networks, i.e. particular social media networks that combine information on users belonging to one or more social communities together with the content that is generated and used within the related environments. The proposed model relies on the hypergraph data structure to capture and represent in a simple way all the different kinds of relationships that are typical of social media networks, and in particular among users and multimedia content. We also introduce some user and multimedia ranking functions to enable different applications. Finally, some experiments concerning effectiveness of the approach for supporting relevant information retrieval activities are reported and discussed.
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Notes
- 1.
Such strategy is necessary in the ranking to penalize lurkers, i.e. users of a MSN that are quite inactive and not directly interact with multimedia content but through user to user relationships.
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Amato, F., Cozzolino, G., Moscato, F., Moscato, V., Picariello, A., Sperli, G. (2019). Data Mining in Social Network. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L., Vlacic, L. (eds) Intelligent Interactive Multimedia Systems and Services. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-319-92231-7_6
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DOI: https://doi.org/10.1007/978-3-319-92231-7_6
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