DeepAI AI Chat
Log In Sign Up

Exploring Online Ad Images Using a Deep Convolutional Neural Network Approach

by   Michael Fire, et al.

Online advertising is a huge, rapidly growing advertising market in today's world. One common form of online advertising is using image ads. A decision is made (often in real time) every time a user sees an ad, and the advertiser is eager to determine the best ad to display. Consequently, many algorithms have been developed that calculate the optimal ad to show to the current user at the present time. Typically, these algorithms focus on variations of the ad, optimizing among different properties such as background color, image size, or set of images. However, there is a more fundamental layer. Our study looks at new qualities of ads that can be determined before an ad is shown (rather than online optimization) and defines which ads are most likely to be successful. We present a set of novel algorithms that utilize deep-learning image processing, machine learning, and graph theory to investigate online advertising and to construct prediction models which can foresee an image ad's success. We evaluated our algorithms on a dataset with over 260,000 ad images, as well as a smaller dataset specifically related to the automotive industry, and we succeeded in constructing regression models for ad image click rate prediction. The obtained results emphasize the great potential of using deep-learning algorithms to effectively and efficiently analyze image ads and to create better and more innovative online ads. Moreover, the algorithms presented in this paper can help predict ad success and can be applied to analyze other large-scale image corpora.


page 10

page 12


Predicting conversions in display advertising based on URL embeddings

Online display advertising is growing rapidly in recent years thanks to ...

Predicting Audio Advertisement Quality

Online audio advertising is a particular form of advertising used abunda...

How Much Ad Viewability is Enough? The Effect of Display Ad Viewability on Advertising Effectiveness

A large share of all online display advertisements (ads) are never seen ...

M2FN: Multi-step Modality Fusion for Advertisement Image Assessment

Assessing advertisements, specifically on the basis of user preferences ...

Deep CTR Prediction in Display Advertising

Click through rate (CTR) prediction of image ads is the core task of onl...

Learning Parameters for a Generalized Vidale-Wolfe Response Model with Flexible Ad Elasticity and Word-of-Mouth

In this research, we investigate a generalized form of Vidale-Wolfe (GVW...

Image Matters: Jointly Train Advertising CTR Model with Image Representation of Ad and User Behavior

Click Through Rate(CTR) prediction is vital for online advertising syste...