A TV Program Recommender Framework

Na Chang, Mhd Irvan, Takao Terano
<span title="">2013</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cx3f4s3qmfe6bg4qvuy2cxezyu" style="color: black;">Procedia Computer Science</a> </i> &nbsp;
In the area of intelligent systems, research about recommender systems is a critical topic and has been applied in many fields. In this paper, we focus on TV program recommender systems. We give an overview of literature research about TV program recommender systems and propose a smart and social TV program recommender framework for Smart TV, which integrates the Internet and Web 2.0 features into television sets and set-top boxes. In addition, we also address several issues, such as accuracy,
more &raquo; ... iversity, novelty, explanation and group recommendations, which are important in building a TV program recommender system. The proposed framework could be used to help designers/developers to build TV program recommender systems/engines for smart TV.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.procs.2013.09.136">doi:10.1016/j.procs.2013.09.136</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dj2jdwrsjzecjnba4a2zfcb26m">fatcat:dj2jdwrsjzecjnba4a2zfcb26m</a> </span>
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