Version 6.04 (002)

Metadata standard for interoperable Recommender Systems

Active project

The project is aimed at designing and implementing metadata standard for enabling interoperability between  different Recommendation Systems

To date, the user fruition can be strongly affected by vertical and possibly redundant recommendations coming from different service providers. Furthermore, in order to improve accuracy and appropriateness of cross-domain recommendations, standard descriptions about a given user and her context are needed, as well as interoperability between different recommendation results. Among available metadata standard, the project focuses on MPEG-21 User Description (MPEG-21 UD) potentialities.


Leveraging MPEG-21 UD,  the integration of recommendations provided by different engines is allowed, and, standard descriptions for the users, their context and the services providing potentially interesting (i.e. recommendable) items are described.  Adopting MPEG-21 UD standard descriptions, a service provider can properly integrate multiple recommendations thus enhancing its service and, likely, improving the
user experience.


ISO/IEC 21000-22:2016, Information technology — Multimedia framework (MPEG-21) — Part 22: User Description

Paolo Casagranda e Sabino Metta, Leggi questo articolo, una tua amica lo ha trovato interessante. Un’introduzione alle opportunità e criticità dei recommender system per la personalizzazione dei contenuti audiovisivi, Elettronica e Telecomunicazioni, LXV – N. 2/2016

Sabino Metta Paolo Casagranda Alberto Messina Maurizio Montagnuolo e Francesco Russo, Leveraging MPEG-21 User Description for Interoperable Recommender Systems, SAC 2016


Riccardo Di Massa, Maurizio Montagnuolo, Alberto Messina, Implicit News Recommendation Based on User Interest Models and Multimodal Content Analysis, 3rd ACM Workshop on Automated Information Extraction in Media Production ACM Multimedia 2010

Related Projects

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Recommender Systems for Audio and Video Contents

An investigation of the solutions to limit information overload for radio television media

The advent of the Internet and the proliferation of digital services have led to a radical change in the way people enjoy radio and television. The plethora of products, services and content available on the Internet has accustomed its users to interactivity, the ability to search and choose when and what media content to listen, transforming the traditional radio and television listeners into an active consumers, capable of expressing their tastes and preferences. Paradoxically, the vast amount of content available has created an informative overhead and created the problem of finding the most suitable content for each user.
Recommender Systems represent the technological response to the need of relevance. In this context, the broadcaster has the opportunity to evolve its communicative paradigm: in addition to broadcast its content, it can propose the most relevant to its users.

Active Project

Personalized Linear Radio

Personalized Radio and the Hybrid Content Radio Framework

Personalized Linear Radio is based on the idea of replacing part of the audio of linear radio with personalized and user-specific audio content. Audio content can be downloaded from the Internet or from other sources. The context can be the profile of the listener, her mood and activity she is doing, her position, the weather conditions, and all the factors that contribute to characterizing the listener’s status. The ultimate goal of the service is to improve listeners’ user experience, giving them targeted content, while optimizing the use of network resources.