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Recherche Sociale, Structurée et Sémantique

Abstract : Social content such as blogs, tweets, news etc. is a rich source of interconnected information. We identify a set of requirements for the meaningful exploitation of such rich content, and present a new data model, called S4, which is the first to satisfy them. S4 captures social relationships between users, and between users and content, but also the structure present in rich social content, as well as its semantics. We show how S4 instances are derived from content and relationships present in today's social media, and provide the first top-kB keyword search algorithm taking into account the social, structured, and semantic dimensions and formally establish its termination and correctness. Experiments on real social networks demonstrate the efficiency and qualitative advantage of our algorithm through the joint exploitation of the social, structured, and semantic dimensions of S4.
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Submitted on : Wednesday, January 4, 2017 - 4:06:19 PM
Last modification on : Monday, December 13, 2021 - 9:16:32 AM
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  • HAL Id : hal-01426532, version 1


Raphaël Bonaque, Bogdan Cautis, François Goasdoué, Ioana Manolescu. Recherche Sociale, Structurée et Sémantique. 32ème Conférence sur la Gestion de Données - Principes, Technologies et Applications, Nov 2016, Poitiers, France. ⟨hal-01426532⟩



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