Paper Abstract and Keywords |
Presentation |
2017-09-21 15:45
Predictions of Effectiveness of Television Advertising with Convolutional Neural Networks Shunsuke Nakamura (Univ. of Tokyo), Tatsuya Kawahara (VideoResearch), Toshihiko Yamasaki (Univ. of Tokyo) MVE2017-18 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Predicting the recognition rate of television advertising is a critical issue for advertisers, but factors that contribute to the recognition rate are still mysterious. In our preliminary experiments using 11,230 advertising videos and subjective evaluation by about 600 people for each content, we found that gross rating point (GRP), which is one of the most commonly used indicator, has little correlation with the recognition rate (correlation ratio between GRP and the recognition rate was 0.3). In this study, we show that even raw deep feature is more useful and can achieve the correlation value of 0.47. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
deep neural network / television advertising / video feature / video analysis / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 217, MVE2017-18, pp. 21-24, Sept. 2017. |
Paper # |
MVE2017-18 |
Date of Issue |
2017-09-14 (MVE) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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MVE2017-18 |
Conference Information |
Committee |
MVE |
Conference Date |
2017-09-21 - 2017-09-22 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Chiba Univ. |
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(See Japanese page) |
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Paper Information |
Registration To |
MVE |
Conference Code |
2017-09-MVE |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Predictions of Effectiveness of Television Advertising with Convolutional Neural Networks |
Sub Title (in English) |
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deep neural network |
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television advertising |
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video feature |
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video analysis |
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1st Author's Name |
Shunsuke Nakamura |
1st Author's Affiliation |
The university of Tokyo (Univ. of Tokyo) |
2nd Author's Name |
Tatsuya Kawahara |
2nd Author's Affiliation |
VideoResearch Ltd. (VideoResearch) |
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Toshihiko Yamasaki |
3rd Author's Affiliation |
The university of Tokyo (Univ. of Tokyo) |
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Speaker |
Author-1 |
Date Time |
2017-09-21 15:45:00 |
Presentation Time |
30 minutes |
Registration for |
MVE |
Paper # |
MVE2017-18 |
Volume (vol) |
vol.117 |
Number (no) |
no.217 |
Page |
pp.21-24 |
#Pages |
4 |
Date of Issue |
2017-09-14 (MVE) |
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