An Architecture for Cultural Heritage enhancement based on the Internet of Things and a Hybrid Context-Aware Recommender System

Cultural heritage represents one of the areas with a growing interest in applying new technologies because of the wide variety of offered content. In particular, a significant application for new technologies involves enhancing the user's cultural experience by providing personalized content selected according to the user's preferences. For this purpose, one of the most commonly exploited tools is Recommender Systems, which can filter and analyze data to support users according to their preferences. Moreover, in the personalization phase, the application to cultural heritage requires the consideration of the environmental situation experienced by the user. Therefore, Recommender Systems evolve into Context-Aware Recommender Systems integrating data acquired through sensors. As a result, the objective of this work consists of describing a four-layer architecture for improving cultural experience through the Internet of Things and Context-Aware Recommender Systems. In particular, the proposed recommendation approach is tested on a dataset in the literature, yielding promising results in accuracy.