- Author
- Year
- 2017
- Title
- Busy versus Empty Museums
- Subtitle
- Effects of Visitors' Crowd on Users' Behaviors in Smart Museums
- Event
- UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization
- Book/source title
- UMAP'17
- Book/source subtitle
- adjunct publication of the 25th Conference on User Modeling, Adaptation and Personalization : July 9-12, 2017, Bratislava, Slovakia
- Pages (from-to)
- 333-334
- Publisher
- New York, NY: The Association for Computing Machinery
- ISBN
- 9781450346351
- ISBN (electronic)
- 9781450350679
- Document type
- Conference contribution
- Faculty
- Interfacultary Research
Faculty of Humanities (FGw)
Other - Institute
- Institute for Logic, Language and Computation (ILLC)
Universiteitsbibliotheek - 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. - URL
- go to publisher's site
- Language
- English
- Persistent Identifier
- https://hdl.handle.net/11245.1/f72976ed-857f-496f-a5f4-7a5046ebd6da
- Downloads
-
p333-hashemi(Final published version)
Disclaimer/Complaints regulations
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library, or send a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.