Title: Self and social network behaviours of users in cultural spaces

Authors: Angelo Chianese; Salvatore Cuomo; Pasquale De Michele; Francesco Piccialli

Addresses: Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy ' Department of Mathematics and Applications 'Renato Caccioppoli', University of Naples Federico II, Naples, Italy ' Department of Mathematics and Applications 'Renato Caccioppoli', University of Naples Federico II, Naples, Italy ' Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy

Abstract: Many cultural spaces offer their visitors the use of ICT tools to enhance their visit experience. Data collected within such spaces can be analysed in order to discover hidden information related to visitors' behaviours and needs. In this paper, a computational model inspired by neuroscience simulating the personalised interactions of users with cultural heritage objects is presented. We compare a strengthened validation approach for neural networks based on classification techniques with a novel proposal one, based on clustering strategies. Such approaches allow us to identify natural users' groups in data and to verify the model responses in terms of user interests. Finally, the presented model has been extended to simulate social behaviours in a community, through the sharing of interests and opinions related to cultural heritage assets. This data propagation has been further analysed in order to reproduce applicative scenarios on social networks.

Keywords: social network; clustering techniques; cultural heritage; internet of things; IoT; user behaviours.

DOI: 10.1504/IJCSE.2018.091770

International Journal of Computational Science and Engineering, 2018 Vol.16 No.3, pp.265 - 281

Received: 30 Dec 2015
Accepted: 28 May 2016
Published online: 16 May 2018 *

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