Fiora project aims at designing and developing of a customized recommendation engine. This engine will provide the most relevant content for a given user with maximum reliability. For this, the results returned will be tailored to each user depending on several factors such as contextual data related to those users and their environment and the available semantic information.

The main result of this project will be to reconcile within the same engine approaches like case-based reasoning, technical recommendations using collaborative filtering, and the management/validation techniques of recommendations using data mining. A key step for this reconciliation between disjointed disciplines is the construction of a formal application where data and knowledge are handled and processed. In addition, the Fiora project will develop “scalable” technical recommendations coupled with Big Data technologies and formatting data (trellis or ontologies) in order to implement a non-intrusive, scalable and distributed recommendation system.

Finally, the proof of concept will be provided within two distinct domains: “Nutrition & Health” and “e-tourism” applications.


36 months (December 2012 – November 2015)


  • ISEP: Raja Chiky, Matthieu Manceny, Zakia Kazi-Aoul
  • Kiolis (leader)
  • Éditions Solar
  • Centrale Recherche SA
  • Paris XIII University