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The emergence of smartphones has given mobile computing access to everydayreality. More specifically, the context modeling offers users an effective wayto customize search results and even the recommended elements by limiting thedata space. Moreover, in recent years, many social sites have embraced thenotion of context in their recommendations. Indeed, with the availability ofmobile devices, these new mobile sites have the advantage of providing userswith more relevant elements based on their current situations. Thus, weintroduce a new approach of contextual IR in a mobile environment. We offer ahand, an approach called SA-IRI based on the prediction of users' interests,from DBpedia, given their current situations. This approach applies thetechnique of associative classification in order to enrich the users' queries.Secondly, we introduce an approach of communities discovering, calledFoaf-A-Walk, combining the random walk technique and the Foaf modeling, forfriend recommendation.

La pr\'ediction des int\'er\^ets des utilisateurs pour la RI contextuelle et la recommandation d'amis dans un environnement mobile