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 [1]. 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 [2]. 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.