Abstract
The paper reports the findings from research aimed at the analysis of visitor behavior in the Herakleidon Museum in Athens - Greece, which hosts an ancient Greek technology exhibition. Based on behavioral data gathered by direct observation, we aim to implement services to assist museum curators and enhance the visitors’ experience. We describe the data collection, analysis and prediction of the visitors’ preferences concerning the exhibits of the museum given their past preferences.
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Acknowledgement
This work was supported by the \(T1E\varDelta K\)-00502 MuseLearn project, which is implemented within the framework of “Competitiveness, Entrepreneurship and Innovation” (EPAnEK) Operational Programme 2014–2020, funded by the EU and national funds (www.muselearn.gr).
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Kosmopoulos, D., Tzortzi, K. (2021). Visitor Behavior Analysis for an Ancient Greek Technology Exhibition. In: Maglogiannis, I., Macintyre, J., Iliadis, L. (eds) Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops. AIAI 2021. IFIP Advances in Information and Communication Technology, vol 628. Springer, Cham. https://doi.org/10.1007/978-3-030-79157-5_40
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DOI: https://doi.org/10.1007/978-3-030-79157-5_40
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