Catch-up TV recommendations: show old favourites and find new ones

Authors:
Mengxi Xu;Shlomo Berkovsky;Sebastien Ardon;Sipat Triukose;Anirban Mahanti;Irena Koprinska
Affiliations:
University of Sydney and NICTA, Sydney, Australia;NICTA, Sydney, Australia;NICTA, Sydney, Australia;NICTA, Sydney, Australia;NICTA, Sydney, Australia;University of Sydney, Sydney, Australia
Venue:
Proceedings of the 7th ACM conference on Recommender systems
Year:
2013

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Abstract

Web-based catch-up TV has revolutionised watching habits as it provides users the opportunity to watch programs at their preferred time and place, using a variety of devices. With the increasing offer of TV content, there is an emergent need for personalised recommendation solutions, which help users to select programs of interest. In this work, we study the watching patterns of users of an Australian nation-wide catch-up TV service provider and develop a suite of approaches for a catch-up recommendation scenario. We evaluate these approaches using a new large-scale dataset gathered by the Web-based catch-up portal deployed by the provider. The evaluation allows us to compare the performance of several recommenders that address the discovery of both TV programs already watched by users and new programs that users may find relevant.