Research Article
User Behaviour Analysis and Personalized TV Content Recommendation
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@INPROCEEDINGS{10.1007/978-3-030-16447-8_13, author={Ana Ribeiro and Rui Fraz\"{a}o and Jorge Oliveira e S\^{a}}, title={User Behaviour Analysis and Personalized TV Content Recommendation}, proceedings={Intelligent Technologies for Interactive Entertainment. 10th EAI International Conference, INTETAIN 2018, Guimar\"{a}es, Portugal, November 21-23, 2018, Proceedings}, proceedings_a={INTETAIN}, year={2019}, month={4}, keywords={Recommender systems Machine learning User behaviour analytics}, doi={10.1007/978-3-030-16447-8_13} }- Ana Ribeiro
Rui Frazão
Jorge Oliveira e Sá
Year: 2019
User Behaviour Analysis and Personalized TV Content Recommendation
INTETAIN
Springer
DOI: 10.1007/978-3-030-16447-8_13
Abstract
Nowadays, there are many channels and television (TV) programs available, and when the viewer is confronted with this amount of information has difficulty in deciding which wants to see. However, there are moments of the day that viewers see always the same channels or programs, that is, viewers have TV content consumption habits. The aim of this paper was to develop a recommendation system that to be able to recommend TV content considering the viewer profile, time and weekday.
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