Predicting future user behaviour in interactive live TV

Martin Gude, Stefan M. Grünvogel and Andreas Pütz (2008)
In: Tscheligi, M., Obrist, M. and Lugmayr, A. (edt.), Changing Television Environments, Lecture Notes in Computer Science , Vol. 5066, pp. 117-121, Springer Verlag

Abstract

Recommender systems are a means of personalisation providing
their users with personalised recommendations of items that would
possibly suit the users needs. They are used in a broad area of contexts
where items are somehow linked to users. The creation of recommendations
of interactive live TV suers from several inherent problems, e.g.
the impossibility to foresee the contents of the next items or the reactions
of the user to the changing programme.
This paper proposes an algorithm for building personalised streams within
interactive live TV. The development of the algorithm comprises a basic
model for users and media items. A rst preliminary evaluation of the
alogithm is executed and the results discussed.