Classify the dynamic of users in a cultural heritage exhibition in order to infer information about the event fruition is a very interesting research field. In this paper, starting from real data, we investigate the user dynamics related to the interaction with artworks and how a spectator interacts with available technologies. Accordingly with the fact that the technology plays a crucial role in supporting spectators and enhancing their experiences, the starting point of this research has been the art exhibition named The Beauty or the Truth that was located in Naples (Italy), where event was equipped with several technological tools. Here, the collected log files, stored in a suitable expert software system, are used in a flexible framework in order to analyse how the supporting pervasive technology influence and modify behaviours and visiting styles. Finally, we carried out some experiments to exploit the clustering facilities for finding groups that reflect visiting styles. The obtained results have revealed interesting issues also to understand hidden aspects in the data and unattended in the analysis. © Springer International Publishing Switzerland 2016.

Classify visitor behaviours in a cultural heritage exhibition

Ponti, G.
2016

Abstract

Classify the dynamic of users in a cultural heritage exhibition in order to infer information about the event fruition is a very interesting research field. In this paper, starting from real data, we investigate the user dynamics related to the interaction with artworks and how a spectator interacts with available technologies. Accordingly with the fact that the technology plays a crucial role in supporting spectators and enhancing their experiences, the starting point of this research has been the art exhibition named The Beauty or the Truth that was located in Naples (Italy), where event was equipped with several technological tools. Here, the collected log files, stored in a suitable expert software system, are used in a flexible framework in order to analyse how the supporting pervasive technology influence and modify behaviours and visiting styles. Finally, we carried out some experiments to exploit the clustering facilities for finding groups that reflect visiting styles. The obtained results have revealed interesting issues also to understand hidden aspects in the data and unattended in the analysis. © Springer International Publishing Switzerland 2016.
9783319301617
Data mining;User profiling;Clustering
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/4101
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