@inproceedings{92ba8b97968146a0b8d467dfff8b110d,
title = "A museum visitors classification based on behavioral and demographic features",
abstract = "This paper describes an exploratory study that attempts to classify museum visitors by taking into consideration indoor behavior and demographic features. We discuss different approaches of using such data for improving the user experience in the museum. Moreover, we try to explain user's behavior by creating different user groups using a novel data set. Our findings indicate that knowing user age, education and her museum visits frequency, together with the current visit signals (total standing time and listening to a mobile guide time) can be used for visitors classification that might be useful in designing new intelligent user interfaces that can improve the visitor's indoor experience.",
keywords = "Clustering, Cultural Heritage, Museum Interactions, User Modeling",
author = "Moayad Mokatren and Alan Wecker and Veronika Bogina and Tsvi Kuflik",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019 ; Conference date: 09-06-2019 Through 12-06-2019",
year = "2019",
month = jun,
day = "6",
doi = "10.1145/3314183.3323864",
language = "אנגלית",
series = "ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization",
publisher = "Association for Computing Machinery, Inc",
pages = "383--386",
booktitle = "ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization",
}