Abstract—The internet protocol television (IPTV) provide
thousands of video contents to the users. However, it is difficult
to each user to make selection from the amount of videos
especially for the group of users. For dealing with the problem,
the recommendation systems are developed to aid the users to
make selection. In this study, the group recommender named
“EyeTV” is proposed which is a multi-facial recognition
technique-aided IPTV system, and it is an improved version of
the 1st generation proposed in 2012. The EyeTV system applies
Microsoft Xbox’s IP camera - KINECT to be the eye of TV for
capturing facial features of users, and the multi-facial
recognition technique is employed to recognize the user’s
identity. The users who watch the videos together are taken as a
group, and then the system would memorize the watching
history for that group automatically. The interactions among the
group members can be predicted by the recommendation
algorithm of EyeTV, that is, the recommended results are taken
the members’ interactions into consideration, and the
recommended results may be more and more relevant to the
group after training. However, the members may be able to
guess what kinds of videos would be recommended to them at
the time, and the group recommender can be considered as an
ineffective service. For preventing the problem mentioned
before and providing the group members new watching
experience, the social network-based serendipity recommender
is employed to improve the EyeTV system. The improved EyeTV
system takes the recorded information from the social network
of each member, and the data from social network would be
combined with the group’s watching history for providing
serendipitous recommendations to the group.
Index Terms—IPTV, recommendation systems, group
recommender, social network, serendipity.
The authors are with the Information and Communications Research
Laboratories of Industrial Technology Research Institute of Taiwan, R.O.C
(e-mail: {kueihong990316, khchung, itri450839, DelphiChen}
@itri.org.tw).
[PDF]
Cite:Kuei-Hong Lin, Kuo-Huang Chung, Kai-Shun Lin, and Jia-Sin Chen, "Face Recognition-Aided IPTV Group Recommender with
Consideration of Serendipity," International Journal of Future Computer and Communication vol. 3, no. 2, pp. 141-147, 2014.
