Publication: A methodology of personalized recommendation system on mobile device for digital television viewers
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2017
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en
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item.page.harrt.identifier.callno
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Proceedings of the 6th International Conference on Computing and Informatics (ICOCI 2017)
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305
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310
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A methodology of personalized recommendation system on mobile device for digital television viewers
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Abstract
With the increasing of the number of digital television (TV) channels in Thailand; this becomes a problem of information overload for TV viewers. There are mass numbers of TV programs to watch but the information about these programs is poor. Therefore; this work presents a personalized recommendation system on mobile device to recommend a TV program that matches viewer’s interests and/or needs.The main mechanism of the system is content-based similarity analysis (CBSA).Initially; the viewer defines favorite programs; and then the system utilize this list as query to find their annotations on the WWW.These annotations will be used to find other programs that are similar by using CBSA.Finally; all similar programs are grouped to the same class and stored as a dataset in a personal mobile device. For the usage; if a TV program matches the interest and specified time of viewer; the system on mobile device will notify the viewer individually.