Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi

Gulsah Ayhan; Cagla Senel; Zeynep Eda Uran; Behcet Ugur Toreyin

doi:10.1109/SIU.2018.8404789

Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi

Gulsah Ayhan
, Cagla Senel
, Zeynep Eda Uran
, Behcet Ugur Toreyin

Bilişim Enstitüsü

Cerebro Yazilim Hizmetleri

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

Özet

Pages on digital platforms used for online advertising in order to attract customer attention for a target product are called landing pages. The aim of landing pages is to increase advertisement conversion rates using metrics like clicks, views or subscriptions. In this study, a method is presented to automatically detect the most commonly used components on landing pages; buttons, texts and checkboxes. Landing page images given as inputs, are segmented by morphological and thresholding-based image analysis methods, and each segment is classified using Convolutional Neural Networks (CNN). The proposed method is anticipated to be an important step in the process of automatically designing landing pages with high advertisement conversion rates by segmenting pages into components that have higher performance metrics. In preliminary experiments, high accuracy is achieved in the test data set.

Tercüme edilen katkı başlığı	Landing page component classification with convolutional neural networks for online advertising
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	1-4
Sayfa sayısı	4
ISBN (Elektronik)	9781538615010
DOI'lar	https://doi.org/10.1109/SIU.2018.8404789
Yayın durumu	Yayınlandı - 5 Tem 2018
Etkinlik	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey Süre: 2 May 2018 → 5 May 2018

Yayın serisi

Adı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Ülke/Bölge	Turkey
Şehir	Izmir
Periyot	2/05/18 → 5/05/18

Bibliyografik not

Publisher Copyright:
© 2018 IEEE.

Keywords

Convolutional neural networks (CNN)
Image segmentation
Landing page
Online advertising

Belgeye Erişim

10.1109/SIU.2018.8404789

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Ayhan, G., Senel, C., Uran, Z. E., & Toreyin, B. U. (2018). Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 (pp. 1-4). (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2018.8404789

Ayhan, Gulsah ; Senel, Cagla ; Uran, Zeynep Eda et al. / Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

@inproceedings{bc5328f485604b04a90ca0700688e498,

title = "{\c C}evrimi{\c c}i reklamcilik i{\c c}in kar{\c s}ilama sayfasi bile{\c s}enlerinin evri{\c s}imsel sinir aǧlari ile siniflandirilmasi",

abstract = "Pages on digital platforms used for online advertising in order to attract customer attention for a target product are called landing pages. The aim of landing pages is to increase advertisement conversion rates using metrics like clicks, views or subscriptions. In this study, a method is presented to automatically detect the most commonly used components on landing pages; buttons, texts and checkboxes. Landing page images given as inputs, are segmented by morphological and thresholding-based image analysis methods, and each segment is classified using Convolutional Neural Networks (CNN). The proposed method is anticipated to be an important step in the process of automatically designing landing pages with high advertisement conversion rates by segmenting pages into components that have higher performance metrics. In preliminary experiments, high accuracy is achieved in the test data set.",

keywords = "Convolutional neural networks (CNN), Image segmentation, Landing page, Online advertising",

author = "Gulsah Ayhan and Cagla Senel and Uran, \{Zeynep Eda\} and Toreyin, \{Behcet Ugur\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 ; Conference date: 02-05-2018 Through 05-05-2018",

year = "2018",

month = jul,

day = "5",

doi = "10.1109/SIU.2018.8404789",

language = "T{\"u}rk{\c c}e",

series = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--4",

booktitle = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

address = "United States",

}

Ayhan, G, Senel, C, Uran, ZE & Toreyin, BU 2018, Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi. in 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Izmir, Turkey, 2/05/18. https://doi.org/10.1109/SIU.2018.8404789

Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi. / Ayhan, Gulsah; Senel, Cagla; Uran, Zeynep Eda et al.
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi

AU - Ayhan, Gulsah

AU - Senel, Cagla

AU - Uran, Zeynep Eda

AU - Toreyin, Behcet Ugur

PY - 2018/7/5

Y1 - 2018/7/5

N2 - Pages on digital platforms used for online advertising in order to attract customer attention for a target product are called landing pages. The aim of landing pages is to increase advertisement conversion rates using metrics like clicks, views or subscriptions. In this study, a method is presented to automatically detect the most commonly used components on landing pages; buttons, texts and checkboxes. Landing page images given as inputs, are segmented by morphological and thresholding-based image analysis methods, and each segment is classified using Convolutional Neural Networks (CNN). The proposed method is anticipated to be an important step in the process of automatically designing landing pages with high advertisement conversion rates by segmenting pages into components that have higher performance metrics. In preliminary experiments, high accuracy is achieved in the test data set.

AB - Pages on digital platforms used for online advertising in order to attract customer attention for a target product are called landing pages. The aim of landing pages is to increase advertisement conversion rates using metrics like clicks, views or subscriptions. In this study, a method is presented to automatically detect the most commonly used components on landing pages; buttons, texts and checkboxes. Landing page images given as inputs, are segmented by morphological and thresholding-based image analysis methods, and each segment is classified using Convolutional Neural Networks (CNN). The proposed method is anticipated to be an important step in the process of automatically designing landing pages with high advertisement conversion rates by segmenting pages into components that have higher performance metrics. In preliminary experiments, high accuracy is achieved in the test data set.

KW - Convolutional neural networks (CNN)

KW - Image segmentation

KW - Landing page

KW - Online advertising

UR - https://www.scopus.com/pages/publications/85050795470

U2 - 10.1109/SIU.2018.8404789

DO - 10.1109/SIU.2018.8404789

M3 - Konferans katkısı

AN - SCOPUS:85050795470

T3 - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

SP - 1

EP - 4

BT - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

Y2 - 2 May 2018 through 5 May 2018

ER -

Ayhan G, Senel C, Uran ZE, Toreyin BU. Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-4. (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). doi: 10.1109/SIU.2018.8404789

Çevrimiçi reklamcilik için karşilama sayfasi bileşenlerinin evrişimsel sinir aǧlari ile siniflandirilmasi

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap