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A Novel Strategy for Recommending Multimedia Objects and its Application in the Cultural Heritage Domain

Massimiliano Albanese (George Mason University, USA), Antonio d’Acierno (ISA, National Research Council, Italy), Vincenzo Moscato (University of Naples, Italy), Fabio Persia (University of Naples, Italy) and Antonio Picariello (University of Naples, Italy)

Source Title: International Journal of Multimedia Data Engineering and Management (IJMDEM) 2(4)

DOI: 10.4018/jmdem.2011100101

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Abstract

One of the most important challenges in the information access field, especially for multimedia repositories, is information overload. To cope with this problem, in this paper, the authors present a strategy for a recommender system that computes customized recommendations for users’ accessing multimedia collections, using semantic contents and low-level features of multimedia objects, past behaviour of individual users, and social behaviour of the users’ community as a whole. The authors implement their strategy in a recommender prototype for browsing image digital libraries in the Cultural Heritage domain. They then investigate the effectiveness of the proposed approach, based on the users’ satisfaction. The preliminary experimental results show that the approach is promising and encourages further research in this direction.

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2. Motivating Examples

In this section we report two typical scenarios in the Cultural Heritage domain that aim at showing how a recommendation system could desirably work during both a virtual -- but also a real -- visit of an art gallery.

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A Novel Strategy for Recommending Multimedia Objects and its Application in the Cultural Heritage Domain

Abstract

2. Motivating Examples

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