Personalisation of digital museum guides through implicit recognition of visitor personas

Digital museum guides promise a transformed visitor experience through greater engagement with the museum content and activities. Realising that promise turns on the personalisation of digital guides, particularly in museum contexts where rich content is accessed by a highly diverse visitor population. Since users of a museum guide are typically first time users and since their usage is for a relatively short session, personalisation must use initial interaction data to associate the user with a particular persona and thereby infer other facts about the user’s preferences and needs. Two research aims follow: first to better understand the requirements of different visitor personas, and second, to develop methods for unobtrusively detecting a user’s persona from their interactions with a guide and their activity in the museum space. This paper presents the design of a research programme for: first, investigating mechanisms for automatic adaptation of digital museum guides based on identifying a visitor’s persona category from interaction data; second, exploring the requirements of different visitor categories to derive the user interface adaptation, and; third, investigating the effectiveness of this adaptation on the museum visitor’s experience.