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[DCD14] RecLand: A Recommender System for Social Networks
Atelier, Poster ou Démonstration dans une Conférence Internationale : International Conference on Conference on Information and Knowledge Management, November 2014, pp.2063-2065, Shanghai, China, (DOI: http://dx.doi.org/10.1145/2661829.2661850)Mots clés: Recommendation, Social Networks, Link Prediction
Résumé:
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.
Collaboration:
LIP6
BibTeX
| @inproceedings { | |||
| DCD14, | |||
| title | = | "{RecLand: A Recommender System for Social Networks}", | |
| author | = | " R. Dahimene and C. Constantin and C. du Mouza ", | |
| booktitle | = | "{International Conference on Conference on Information and Knowledge Management}", | |
| year | = | 2014, | |
| month | = | "November", | |
| pages | = | "2063-2065", | |
| address | = | "Shanghai, China", | |
| doi | = | "http://dx.doi.org/10.1145/2661829.2661850", | |
| } | |||
