The 3A contextual ranking system: simultaneously recommending actors, assets, and group activities

  • Authors:
  • Sandy El Helou;Christophe Salzmann;Stéphane Sire;Denis Gillet

  • Affiliations:
  • Swiss Federal Institute of Lausanne, Lausanne, Switzerland;Swiss Federal Institute of Lausanne, Lausanne, Switzerland;Swiss Federal Institute of Lausanne, Lausanne, Switzerland;Swiss Federal Institute of Lausanne, Lausanne, Switzerland

  • Venue:
  • Proceedings of the third ACM conference on Recommender systems
  • Year:
  • 2009

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Abstract

In this paper, we propose a personalized and contextual ranking algorithm implemented on top of the 3A interaction model. The latter is a generic model intended for designing and describing social and collaborative learning platforms integrating Actors, Assets and group Activities (the 3 "A"). The target user's interactions with his/her environment are modeled in a heterogeneous graph. Then, the algorithm is applied to simultaneously rank actors, assets and group activities taking into account the target user and his/her context. As an illustrative application and a preliminary evaluation, we apply the algorithm on data related to the activities carried out in a European Research Project, especially the collaboration between its members through the joint production of deliverables in workpackages.