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Recommender Systems for Museums: Evaluation on a Real Dataset

Authors:
Ivan Keller
Emmanuel Viennet

Keywords: Recommender Systems, Social Networks, Museum

Abstract:
This paper discusses the evaluation of several recommendation methods used to suggest relevant contents to museum visitors. We employed traditional recommender systems along with our versatile Social Filtering formalism to test different strategies on a genuine dataset, which was collected during a recent cultural exhibition that received significant interest in Paris, France. The results show the promising potential of recommendation techniques in the not so well explored application domain of museum visit. This work is part of the AMMICO ongoing research project that aims to develop “smart” audio guides for museums.

Pages: 65 to 71

Copyright: Copyright (c) IARIA, 2015

Publication date: June 21, 2015

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-415-2

Location: Brussels, Belgium

Dates: from June 21, 2015 to June 26, 2015