TY - CHAP
T1 - A System to Select Reception Channel by Machine Learning in Hybrid Broadcasting Environments
AU - Yoshihisa, Tomoki
AU - Gotoh, Yusuke
AU - Kanzaki, Akimitsu
N1 - Funding Information:
Acknowledgments. A part of this work was supported by JSPS KAKENHI (Grant Number JP15H02702 and JP18K11316) and by Research Grant of Kayamori Foundation of Informational Science Advancement.
Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Due to the recent prevalence of the Internet, some TV broadcasting services deliver videos using both electric wave broadcasting systems and the Internet (hybrid broadcasting environments). Video players encounter playback interruptions when they cannot receive a part of video data (video data segment) until the time to play it. The probability to encounter playback interruptions can be reduced by receiving video data segments earlier. However, it is difficult for video players to find from which reception channel (broadcasting system or the Internet) they can receive video data segments earlier since the time required for receiving them depends on various factors such as broadcasting schedules, the number of receiving video players, and so on. To find appropriate reception channels for reducing playback interruptions, we propose a system to select reception channel by machine learning.
AB - Due to the recent prevalence of the Internet, some TV broadcasting services deliver videos using both electric wave broadcasting systems and the Internet (hybrid broadcasting environments). Video players encounter playback interruptions when they cannot receive a part of video data (video data segment) until the time to play it. The probability to encounter playback interruptions can be reduced by receiving video data segments earlier. However, it is difficult for video players to find from which reception channel (broadcasting system or the Internet) they can receive video data segments earlier since the time required for receiving them depends on various factors such as broadcasting schedules, the number of receiving video players, and so on. To find appropriate reception channels for reducing playback interruptions, we propose a system to select reception channel by machine learning.
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U2 - 10.1007/978-3-319-98530-5_74
DO - 10.1007/978-3-319-98530-5_74
M3 - Chapter
AN - SCOPUS:85083425974
T3 - Lecture Notes on Data Engineering and Communications Technologies
SP - 833
EP - 840
BT - Lecture Notes on Data Engineering and Communications Technologies
PB - Springer Science and Business Media Deutschland GmbH
ER -