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| Presentation | 2015-02-20 14:50 Predicting User Demographics and Click Through Rate of Display Ads Applying a Generic Image Recognition Methodology Kohei Yamamoto (The Univ. of Tokyo), Tetsuya Motegi, Yukihiro Tagami, Hayato Kobayashi, Shingo Ono (Yahoo Japan), Hideki Nakayama (The Univ. of Tokyo)  PRMU2014-149 CNR2014-64 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In the field of click-through rate (CTR) prediction of pay per click display ads, the latency and the cold-start problem, which is a difficulty in CTR prediction regarding users and ads with little historical data, are fundamental problems. In this work, we propose a content-based CTR prediction method applying a generic image recognition methodology. Our proposed method is completely content-based using image similarity; therefore, we expect it to enable a CTR prediction even for users and items with little historical data. Finally, we evaluate our proposed method with datasets of display ads and confirmed its effectiveness. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Ad CTR Prediction / Generic Image Recognition / Convolutional Neural Networks / Image Features / User Demographics Estimation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 114, no. 454, PRMU2014-149, pp. 179-184, Feb. 2015. | |
| Paper # | PRMU2014-149 | |
| Date of Issue | 2015-02-12 (PRMU, CNR) | |
| 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) | |
| Download PDF | PRMU2014-149 CNR2014-64 |
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| Conference Information | |
| Committee | PRMU CNR |
| Conference Date | 2015-02-19 - 2015-02-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | PRMU |
| Conference Code | 2015-02-PRMU-CNR |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Predicting User Demographics and Click Through Rate of Display Ads Applying a Generic Image Recognition Methodology |
| Sub Title (in English) | |
| Keyword(1) | Ad CTR Prediction |
| Keyword(2) | Generic Image Recognition |
| Keyword(3) | Convolutional Neural Networks |
| Keyword(4) | Image Features |
| Keyword(5) | User Demographics Estimation |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Kohei Yamamoto |
| 1st Author's Affiliation | The University of Tokyo (The Univ. of Tokyo) |
| 2nd Author's Name | Tetsuya Motegi |
| 2nd Author's Affiliation | Yahoo Japan Corporation (Yahoo Japan) |
| 3rd Author's Name | Yukihiro Tagami |
| 3rd Author's Affiliation | Yahoo Japan Corporation (Yahoo Japan) |
| 4th Author's Name | Hayato Kobayashi |
| 4th Author's Affiliation | Yahoo Japan Corporation (Yahoo Japan) |
| 5th Author's Name | Shingo Ono |
| 5th Author's Affiliation | Yahoo Japan Corporation (Yahoo Japan) |
| 6th Author's Name | Hideki Nakayama |
| 6th Author's Affiliation | The University of Tokyo (The Univ. of Tokyo) |
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| Speaker | Author-1 |
| Date Time | 2015-02-20 14:50:00 |
| Presentation Time | 30 minutes |
| Registration for | PRMU |
| Paper # | PRMU2014-149, CNR2014-64 |
| Volume (vol) | vol.114 |
| Number (no) | no.454(PRMU), no.455(CNR) |
| Page | pp.179-184 |
| #Pages | 6 |
| Date of Issue | 2015-02-12 (PRMU, CNR) |
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