Multimedia Tools and Applications

, Volume 50, Issue 3, pp 563–585 | Cite as

A multimedia recommender integrating object features and user behavior

  • Massimiliano Albanese
  • Angelo Chianese
  • Antonio d’Acierno
  • Vincenzo Moscato
  • Antonio Picariello


Despite the great amount of work done in the last decade, retrieving information of interest from a large multimedia repository still remains an open issue. In this paper, we propose an intelligent browsing system based on a novel recommendation paradigm. Our approach combines usage patters with low-level features and semantic descriptors in order to predict users’ behavior and provide effective recommendations. The proposed paradigm is very general and can be applied to any type of multimedia data. In order to make the recommender system even more flexible, we introduce the concept of multichannel browser, i.e. a browser that allows concurrent browsing of multiple media channels. We implemented a prototype of the proposed system and tested the effectiveness of our approach in a virtual museum scenario. Experimental results have proved that the system greatly enhances users’ experience, thus encouraging further research in this direction.


Recommender systems Browsing Information retrieval Multimedia databases 


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Massimiliano Albanese
    • 1
  • Angelo Chianese
    • 2
  • Antonio d’Acierno
    • 3
  • Vincenzo Moscato
    • 2
  • Antonio Picariello
    • 2
  1. 1.UMIACSUniversity of MarylandCollege ParkUSA
  2. 2.DISUniversity of Naples “Federico II”NaplesItaly
  3. 3.ISACNRAvellinoItaly

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