Social, Structured, and Semantic Search

Raphaël Bonaque 1, 2 Bogdan Cautis 1, 3, 2 François Goasdoué 4, 1 Ioana Manolescu 1, 2
1 OAK - Database optimizations and architectures for complex large data
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
4 SHAMAN - Symbolic and Human-centric view of dAta MANagement
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
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 S3, which is the first to satisfy them. S3 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 provide the first top-k 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 S3.
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Raphaël Bonaque, Bogdan Cautis, François Goasdoué, Ioana Manolescu. Social, Structured, and Semantic Search. [Research Report] RR-8797, Inria Saclay Ile de France. 2015, 38 p. ⟨hal-01218116⟩

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