Towards Identifying Visitor Types in Virtual Museums Using Spatial and Interaction Data
Authors: 
Filippos Panos, 
George E. Raptis, Christina Katsini, 
Christos KatsanosAuthors Info & Claims
Filippos Panos, George E. Raptis, Christina Katsini, Christos KatsanosAuthors Info & ClaimsPages 505 - 509
Abstract
Understanding the visitors’ behaviors can shape more immersive museum visits by providing personalized experiences. The first step to providing personalized experiences is to identify visitor types with common visit behavior characteristics. Several attempts have been made with promising results focusing on physical museums. Given the rise of virtual museum visits, in this paper, we take the first step toward identifying visitor types in virtual museums. To this end, we leverage data captured while visitors move within a virtual museum and interact with its exhibits. Using a machine learning approach, we identified four well-defined and distinct clusters that describe different types of virtual museum visitors.
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- Towards Identifying Visitor Types in Virtual Museums Using Spatial and Interaction Data
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June 2024
662 pages
ISBN:9798400704666
DOI:10.1145/3631700
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Published: 28 June 2024
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UMAP '24: 32nd ACM Conference on User Modeling, Adaptation and Personalization
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