The employment of Information and Communication Technologies helps Cultural Heritage enhancement and allows users' cultural experience improvement. In particular, multimedia content employment enables better involvement through Storytelling techniques aimed at capturing the users' attention. Moreover, to guarantee the personalization of the cultural experience, Digital Storytelling requires integrating tools for identifying the users' preferences in the specific environment in which the cultural experience evolves. Therefore, this paper aims to introduce an architecture in which a Context-Aware Recommender System is able to provide personalized paths in which each Point of Interest is presented according to Digital Storytelling techniques. The proposed architecture is validated via two experimental phases: the first aimed to evaluate the accuracy of the recommender system, and the second based on user experience. Obtained results are promising.

Cultural Heritage Enhancement through Digital Storytelling and Context-Aware Recommender System

Cecere L.;Colace F.;Lombardi M.;Lorusso A.;Santaniello D.;Valentino C.
2023-01-01

Abstract

The employment of Information and Communication Technologies helps Cultural Heritage enhancement and allows users' cultural experience improvement. In particular, multimedia content employment enables better involvement through Storytelling techniques aimed at capturing the users' attention. Moreover, to guarantee the personalization of the cultural experience, Digital Storytelling requires integrating tools for identifying the users' preferences in the specific environment in which the cultural experience evolves. Therefore, this paper aims to introduce an architecture in which a Context-Aware Recommender System is able to provide personalized paths in which each Point of Interest is presented according to Digital Storytelling techniques. The proposed architecture is validated via two experimental phases: the first aimed to evaluate the accuracy of the recommender system, and the second based on user experience. Obtained results are promising.
2023
9798400709128
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4856319
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