| Presentation | 2018-03-08 Banner Click Through Rate Classification Using Deep Neural Convolutional Network Nicolas Michel, Hayato Sakata, Keita Kurita, Toshihiko Yamasaki, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In banner advertising, Click Through Rate (CTR) is one of the most important indicators to evaluate oneadvertisement?s quality. Advertisers create massive number of banner candidates in empirical ways, then proceed to actual testsby delivering advertisement to measure each banner?s effectiveness. This process is expensive and therefore our CTR predictionhelps reducing online advertising costs. In this work, we propose a method to classify effective and ineffective advertisingbanners based on image processing using state-of-the-art CNN. We first focus only on images then conduct experiments includingmetadata (product, advertiser, etc) to increase the CTR prediction accuracy and demonstrate which metadata is the mostinfluential. Subsequently, each approach is compared to human performance. In the second part of our work, we detect whichparts of the image contribute predominantly to increase the CTR by generating heat maps for each classes. This work leads to adeeper understanding of a banner advertising success and helps making decisions on how to improve it. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Convolutional Neural Network / Click Through Rate / Deep Learning / Banner Advertising / Deep Learning |
| Paper # | IMQ2017-43,IE2017-135,MVE2017-85 |
| Date of Issue | 2018-03-01 (IMQ, IE, MVE) |
| Conference Information | |
| Committee | CQ / MVE / IE / IMQ |
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| Conference Date | 2018/3/8(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Industry Support Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Five Senses Media, Cooking and Eating Activities Media, Multimedia, Media Experience, Video Encoding, Image Media Quality, Network Quality and Reliability, etc. (Co-sponsor: Technical Committee on Multimedia on Cooking and Eating Activities (CEA)) |
| Chair | Takanori Hayashi(Hiroshima Inst. of Tech.) / Yoshinari Kameda(Univ. of Tsukuba) / Takayuki Hamamoto(Tokyo Univ. of Science) / Kenji Sugiyama(Seikei Univ.) |
| Vice Chair | Hideyuki Shimonishi(NEC) / Jun Okamoto(NTT) / Kenji Mase(Nagoya Univ.) / Kazuya Kodama(NII) / Hideaki Kimata(NTT) / Toshiya Nakaguchi(Chiba Univ.) / Mitsuru Maeda(Canon) |
| Secretary | Hideyuki Shimonishi(NTT) / Jun Okamoto(Keio Univ.) / Kenji Mase(Kyoto Univ.) / Kazuya Kodama(NTT) / Hideaki Kimata(Kyushu Univ.) / Toshiya Nakaguchi(Nagoya Univ.) / Mitsuru Maeda(KDDI Research) |
| Assistant | Kenko Ota(Nippon Inst. of Tech.) / Norihiro Fukumoto(KDDI Research Inc.) / Ryo Yamamoto(UEC) / Takatsugu Hirayama(Nagoya Univ.) / Ryosuke Aoki(NTT) / Yasutaka Matsuo(NHK) / Kazuya Hayase(NTT) / Masaru Tsuchida(NTT) / Gosuke Ohashi(Shizuoka Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Communication Quality / Technical Committee on Media Experience and Virtual Environment / Technical Committee on Image Engineering / Technical Committee on Image Media Quality |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Banner Click Through Rate Classification Using Deep Neural Convolutional Network |
| Sub Title (in English) | |
| Keyword(1) | Convolutional Neural Network |
| Keyword(2) | Click Through Rate |
| Keyword(3) | Deep Learning |
| Keyword(4) | Banner Advertising |
| Keyword(5) | Deep Learning |
| 1st Author's Name | Nicolas Michel |
| 1st Author's Affiliation | University Of Tokyo(Univ. Of Tokyo) |
| 2nd Author's Name | Hayato Sakata |
| 2nd Author's Affiliation | So-net Media Networks(SMN) |
| 3rd Author's Name | Keita Kurita |
| 3rd Author's Affiliation | University Of Tokyo(Univ. Of Tokyo) |
| 4th Author's Name | Toshihiko Yamasaki |
| 4th Author's Affiliation | University Of Tokyo(Univ. Of Tokyo) |
| Date | 2018-03-08 |
| Paper # | IMQ2017-43,IE2017-135,MVE2017-85 |
| Volume (vol) | vol.117 |
| Number (no) | IMQ-483,IE-484,MVE-485 |
| Page | pp.pp.101-106(IMQ), pp.101-106(IE), pp.101-106(MVE), |
| #Pages | 6 |
| Date of Issue | 2018-03-01 (IMQ, IE, MVE) |