Toward Social, Structured and Semantic Search

Raphaël Bonaque 1, 2 Bogdan Cautis 1, 2 François Goasdoué 1 Ioana Manolescu 3, 1
1 OAK - Database optimizations and architectures for complex large data
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : Social content such as social network posts, tweets, news articles and more generally web page fragments is often structured. Such social content is also frequently enriched with annotations, most of which carry semantics, either by collaborative effort or from automatic tools. Searching for relevant informa-tion in this context is both a basic feature for the users and a challenging task. We present a data model and a preliminary approach for answering queries over such structured, social and semantic-rich content, taking into account all dimensions of the data in order to return the most meaningful results.
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Raphaël Bonaque, Bogdan Cautis, François Goasdoué, Ioana Manolescu. Toward Social, Structured and Semantic Search. Surfacing the Deep and the Social Web (SDSW), COST Action KEYSTONE, Oct 2014, Riva del Garda, Trentino, Italy. ⟨hal-01109123v2⟩

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