TRANSFER LEARNING BASED CLASSIFICATION OF SEGMENTED LANDING PAGE COMPONENTS

Çağla ŞENEL; Gülşah AYHAN; Zeynep Eda URAN; Behçet Uğur TÖREYİN

Article Details

TRANSFER LEARNING BASED CLASSIFICATION OF SEGMENTED LANDING PAGE COMPONENTS

Authors:

Çağla ŞENEL | Gülşah AYHAN | Zeynep Eda URAN | Behçet Uğur TÖREYİN

Publisher:

İstanbul Technical University

Journal:

The Journal of Cognitive Systems 2018 Vol.3 Issue 2, pp.36-39

Document Type:

Article

Publication Date:

12/2018

Document Language:

English

Document ID (Org No.):

2000664878

Frequency:

Bi-Annual

pISSN:

2548-0650

Abstract:

 

The pages that appear in front of users on digital
platforms used for online advertising to attract attention to target product
are called landing pages. Landing pages aim to increase advertisement
conversion rate using the metrics like clicks, views or subscribes. In this
study, a method is presented to automatically classifier the most commonly used
components on landing pages which are buttons, texts, and checkboxes. Landing
page images given as inputs are segmented by morphological and threshold-based
image processing methods, and each segment is classified using a Transfer
Learning based method which combines pre-trained Inception v-3 networks and
Support Vector Classifier (SVM). Furthermore, different classifiers were
applied to compare the results. The proposed method is anticipated to be an
essential step in the process of designing landing pages automatically with
high advertisement conversion rates. Thanks to the proposed transfer learning
based method, this is achieved by using fewer number of training data.

Article Details

TRANSFER LEARNING BASED CLASSIFICATION OF SEGMENTED LANDING PAGE COMPONENTS

Authors: Çağla ŞENEL | Gülşah AYHAN | Zeynep Eda URAN | Behçet Uğur TÖREYİN

Publisher: İstanbul Technical University

Journal: The Journal of Cognitive Systems 2018 Vol.3 Issue 2, pp.36-39

Document Type: Article

Publication Date: 12/2018

Document Language: English

Document ID (Org No.): 2000664878

Frequency: Bi-Annual

pISSN: 2548-0650

Issues

Authors:

Çağla ŞENEL | Gülşah AYHAN | Zeynep Eda URAN | Behçet Uğur TÖREYİN

Publisher:

İstanbul Technical University

Journal:

The Journal of Cognitive Systems 2018 Vol.3 Issue 2, pp.36-39

Document Type:

Article

Publication Date:

12/2018

Document Language:

English

Document ID (Org No.):

2000664878

Frequency:

Bi-Annual

pISSN:

2548-0650