TY - GEN
T1 - Probabilistic modeling for context-aware service in Smart TV
AU - Yang, Kyon Mo
AU - Cho, Sung Bae
PY - 2013
Y1 - 2013
N2 - Smart TV services which have been provided a one-way or simple united content by content business mostly focus on content services. The smart TV contains a variety of functions causes a problem that the user has to learn the functions. To solve this problem, we propose context-aware service in the smart TV using modular Bayesian networks. Bayesian network can be designed by domain knowledge when there is not enough data. It has been emerged as a powerful technique for context-aware services. We verify the proposed method is useful. It is prove by measuring average of performance of service which gives the result 88% and conducting subjective test provide the result of 76.5.
AB - Smart TV services which have been provided a one-way or simple united content by content business mostly focus on content services. The smart TV contains a variety of functions causes a problem that the user has to learn the functions. To solve this problem, we propose context-aware service in the smart TV using modular Bayesian networks. Bayesian network can be designed by domain knowledge when there is not enough data. It has been emerged as a powerful technique for context-aware services. We verify the proposed method is useful. It is prove by measuring average of performance of service which gives the result 88% and conducting subjective test provide the result of 76.5.
UR - http://www.scopus.com/inward/record.url?scp=84877785530&partnerID=8YFLogxK
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U2 - 10.1109/ISMS.2013.64
DO - 10.1109/ISMS.2013.64
M3 - Conference contribution
AN - SCOPUS:84877785530
SN - 9780769549637
T3 - Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS
SP - 78
EP - 83
BT - Proceedings - 4th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2013
T2 - 4th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2013
Y2 - 29 January 2013 through 31 January 2013
ER -