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Title: Predicting Website's Visual Appeal using a Hybrid of Convolutional Neural Network and Support Vector Machine
Authors: Maristela, Reinier
Keywords: Website Visual Appeal
Deep Learning
Convolutional Neural Network
Support Vector Machine
Issue Date: May-2017
Abstract: In predicting a website's visual appeal, hand-crafted feature extractors may not be able to determine all the relevant features to extract from a screenshot of a website's homepage. Also, since it is hand-crafted, there is a need to determine what features to extract. This study aims to use a hybrid of convolutional neural network and support vector machine to predict a website's visual appeal. Using the hybrid CNN-SVM model, the AI system would extract features from an image of a website's homepage and determine its visual appeal with respect to the age, gender, country, and educational level of the target users.
Appears in Collections:Computer Science SP

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