2020
DOI: 10.1145/3423186
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Museum Mobile Guide Preferences of Different Visitor Personas

Abstract: Personalising museum mobile guides is widely acknowledged as being important for enhancing the visitor experience. Due to the lack of information about an individual visitor and the relatively limited time of his or her visit, adapting the user interface based on a museum visitor's type is a promising approach to personalisation. This approach first requires a mechanism to identify the visitor type (‘persona’) and, second, knowledge of the preferences and needs of different types to apply personalisation. In t… Show more

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Cited by 5 publications
(1 citation statement)
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“…Almeshari et al investigated the preferences and needs of different visitors to a museum through a questionnaire, distinguishing six groups of users representing different user types through two distinctive characteristics: motivation for visiting, and success criteria for visiting. Differences in characteristic preferences between different user types can help optimize museum visit guides and provide a better personalized user experience [59]. Yoo et al found that meaningful user groups could be formed using the distribution characteristics of listeners' play rates, and used two clustering algorithms to eventually form four user groups to respond to users' listening behavior.…”
Section: User Groupsmentioning
confidence: 99%
“…Almeshari et al investigated the preferences and needs of different visitors to a museum through a questionnaire, distinguishing six groups of users representing different user types through two distinctive characteristics: motivation for visiting, and success criteria for visiting. Differences in characteristic preferences between different user types can help optimize museum visit guides and provide a better personalized user experience [59]. Yoo et al found that meaningful user groups could be formed using the distribution characteristics of listeners' play rates, and used two clustering algorithms to eventually form four user groups to respond to users' listening behavior.…”
Section: User Groupsmentioning
confidence: 99%