Busy versus Empty Museums Effects of Visitors' Crowd on Users' Behaviors in Smart Museums

Open Access
Authors
Publication date 2017
Book title UMAP'17
Book subtitle adjunct publication of the 25th Conference on User Modeling, Adaptation and Personalization : July 9-12, 2017, Bratislava, Slovakia
ISBN
  • 9781450346351
ISBN (electronic)
  • 9781450350679
Event UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization
Pages (from-to) 333-334
Publisher New York, NY: The Association for Computing Machinery
Organisations
  • Faculty of Humanities (FGw)
  • Other - Universiteitsbibliotheek
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract
There is a growing interests in integration of Internet of Things (IoT) in smart environments, which creates an opportunity to understand users’ information needs using onsite physical sensor logs. However, the physical context creates numerous external factors that play a role in users’ information interactions, thus creating new external biases in the collected information interaction logs. In order to provide an effective personalized experiences for users in smart environment, we need to take care of these external biases in the behavioral user models. Our general aim is to understand users’ onsite physical behaviors for providing online and onsite personalized services like personalized tour guides. We focus on the cultural heritage domain and collect onsite users’ physical information interaction logs of visits in a museum. This prompts the question: How to understand users’ behavior in the existence of external biases? Our main finding is that users behave differently in their solitude in comparison to a busy museum situation. Specifically, visitors’ crowd bias has a considerable effect on users’ following position rank bias based check-in behavior. Our study investigates on understanding users’ onsite physical behavior accurately, which
can improve the state-of-the-art onsite behavioral user models.
Document type Conference contribution
Language English
Published at https://doi.org/10.1145/3099023.3099088
Downloads
p333-hashemi (Final published version)
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