KIWI

Knowledge, Information and Web Intelligence

Department 5 : Complex systems, artificial intelligence and robotics

Team leader : Anne Boyer
Tél. : +33 3 54 95 85 02
Mail : anne.boyer@loria.fr

Website

Presentation

KIWI aims at increasing the quality of online services (intranet, e-commerce, etc.) brought to an identified or non-identified user. We focus on how to improve interactions between mass market users and e-access to pertinent items (documents, products, web sites, etc.). Our goal consists in providing each user with items likely to interest him, given his specific context or profile. One way to perform service personalization is to use recommender systems, which is KIWI’s main concern.

Research activities

  • Usage based approaches
  • Hybrid approaches
  • Human component
  • Behavioralnetworks,leadershipandmentorship
  • Miscellaneous

Software

  • vnToolkit

Collaborations

Industrial partners:

  • Sailendra (Preference project)
  • CERFAV ( E-Big project)
  • Alcatel Lucent (Cifre grant)

Academic partners

  • LORIA (Orpailleur, Score, MAIA)
  • J. Dinet (ETIC-Metz, e-learning)
  • D. Rey- mond (MICA-GRESIC-Bordeaux, usage mining)
  • I. Cherqui (LISEC-Nancy, elearning)
  • C. Francois (INIST, classification)
  • A. Antoine (IAE, Nancy 2, elearning)
  • R. Giquel (Ecole des Mines de Paris, e-learning)
  • D. Jannach (Dortmund University, sequential reommender),
  • P. Pu (EPFL, HCI)
  • M. Thelwall (University Wolferhampton, UK)
  • L. Chen (University Baptiste, Hong-Kong, HCI)
  • A. Habacha (ENSIT-Tunis, hybrid approach)
  • K. Bsaies (Faculté des Sciences, Tunis)
  • M. Ghenima (ESCE, Tunis)
  • P. Janecek (School of Engineering and Technology-Thailande, HCI)
  • L. Razmerita and H. Selsøe Sorensen (CBS-Danemark)

Keywords

Personalized recommenders, collaborative filtering, hybrid filtering, usage mining, users behavior modeling, statistical approach, social networks, clustering.

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