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Found 8 papers, 2 papers with code
Recommending Themes for Ad Creative Design via Visual-Linguistic Representations
There is a perennial need in the online advertising industry to refresh ad creatives, i. e., images and text used for enticing online users towards a brand.
Learning from Multi-User Activity Trails for B2B Ad Targeting
Online purchase decisions in organizations can go through a complex journey with multiple agents involved in the decision making process.
Managing App Install Ad Campaigns in RTB: A Q-Learning Approach
The policy based on this state space is trained on past decisions and outcomes via a novel Q-learning algorithm which accounts for the delay in install notifications.
Non-linear Label Ranking for Large-scale Prediction of Long-Term User Interests
We consider the problem of personalization of online services from the viewpoint of ad targeting, where we seek to find the best ad categories to be shown to each user, resulting in improved user experience and increased advertisers' revenue.
Hierarchical Neural Language Models for Joint Representation of Streaming Documents and their Content
In particular, we exploit the context of documents in streams and use one of the language models to model the document sequences, and the other to model word sequences within them.
E-commerce in Your Inbox: Product Recommendations at Scale
In recent years online advertising has become increasingly ubiquitous and effective.
Gender and Interest Targeting for Sponsored Post Advertising at Tumblr
As one of the leading platforms for creative content, Tumblr offers advertisers a unique way of creating brand identity.
Entity-Specific Sentiment Classification of Yahoo News Comments
However, the problem of classifying the sentiment of user comments on news sites has not been addressed yet.
