The NoTube BeanCounter: Aggregating user data for television programme recommendation

  • Van Aart C
  • Aroyo L
  • Brickley D
 et al. 
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Abstract

In this paper we present our current experience of aggregating user data from various Social Web applications and outline several key challenges in this area. The work is based on a concrete use case: reusing activity streams to determine a viewer's interests and generating television programme recommendations from these interests. Three system components are used to realise this goal: (1) an intelligent remote control: iZapper for capturing viewer activities in a cross-context television environment; (2) a backend: BeanCounter for aggregation of viewer activities from the iZapper and from different social web applications; and (3) a recommendation engine: iTube for recommending relevant television programmes. The focus of the paper is the BeanCounter as the first step to apply Social Web data for viewer and context modelling on the Web. This is work in progress of the NoTube project.

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Authors

  • Chris Van Aart

  • Lora Aroyo

  • Dan Brickley

  • Vicky Buser

  • Libby Miller

  • Michele Minno

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