Automatic metadata expansion and indirect collaborative filtering for
TV program recommendation system
MULTIMEDIA TOOLS AND APPLICATIONS, 36 (1-2):
37-54 (January 2008)DOI: {10.1007/s11042-006-0077-4}
Abstract
TV Program recommendation is a good example of a novel application of
networked appliances using personalization technologies. The aim of
this paper is to propose methods to improve the accuracy of TV program
recommendation. Automatic metadata expansion (AME) is a method to
enhance TV program metadata from electronic program guide (EPG) data,
and indirect collaborative filtering (ICF) is a method to recommend
non-persistent items such as TV programs based on the preferences of
other members in a community. In this paper, the effectiveness of these
methods is confirmed through experiments. This online TV recommendation
system is currently being used by 230,000 members in Japan. The result
of the actual operation is also discussed.
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