Systems often try to give advice to users. Personalization and the use of personality in the use of recommendation systems is a very topical. Examining the Cultural Heritage Domain, we propose a framework how we can monitor visitor behavior on the go, something that is mildly volatile, to determine personality traits, something that is more stable. This knowledge can be then used along with context to give tailored advice. Methods of monitoring visitor behavior, converting that to traits and that to personality types are described. Different dimensions of how to give tailored advice based on personality are described.

Learning from Mobile Behavior: From Personality to Personalization: A Blueprint

Stock, Oliviero
2016

Abstract

Systems often try to give advice to users. Personalization and the use of personality in the use of recommendation systems is a very topical. Examining the Cultural Heritage Domain, we propose a framework how we can monitor visitor behavior on the go, something that is mildly volatile, to determine personality traits, something that is more stable. This knowledge can be then used along with context to give tailored advice. Methods of monitoring visitor behavior, converting that to traits and that to personality types are described. Different dimensions of how to give tailored advice based on personality are described.
978-1-4503-4413-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/309180
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