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RecLand: A Recommender System for Social Networks

Ryadh Dahimene 1 Camelia Constantin 2 Cedric Du Mouza 1
1 CEDRIC - ISID - CEDRIC. Ingénierie des Systèmes d'Information et de Décision
CEDRIC - Centre d'études et de recherche en informatique et communications
2 BD - Bases de Données
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : Social networks have become an important information source. Due to their unprecedented success, these systems have to face an exponentially increasing amount of user generated content. As a consequence, finding relevant users or data matching specific interests is a challenging. We present RecLand, a recommender system that takes advantage of the social graph topology and of the existing contextual information to recommend users. The graphical interface of RecLand shows recommendations that match the topical interests of users and allows to tune the parameters to adapt the recommendations to their needs.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01126503
Contributor : Laboratoire Cedric <>
Submitted on : Friday, March 6, 2015 - 11:59:03 AM
Last modification on : Monday, February 17, 2020 - 10:51:14 PM

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Ryadh Dahimene, Camelia Constantin, Cedric Du Mouza. RecLand: A Recommender System for Social Networks. International Conference on Information and Knowledge Management, Nov 2014, Shanghai, China. pp.2063-2065, ⟨10.1145/2661829.2661850⟩. ⟨hal-01126503⟩

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