Predicting the probability that a user will click on a specific advertisement has been a
prevalent issue in online advertising, attracting much research attention in the past decades …

This work conducts a systematic literature review about the domain of personalized
advertisement, and more specifically, about the techniques that are used for this purpose …

Click-through rate (CTR) prediction is essential in the modelling of a recommender system.
Previous studies mainly focus on user behavior modelling, while few of them consider …

Click-through rate (CTR) is a positive feedback of user preferences or product purchases,
and its small increase can bring huge benefits. Therefore, CTR prediction plays a key role in …

Click-through rate is a central issue in ad recommendation and has recently received
extensive research attention in academia and industry. Research shows that the accuracy of …

Due to the requirements of privacy protection and data asset ownership, recommender
systems (RSs) based on centralized training process may be infeasible in some practical …

A domain that has gained popularity in the past few years is personalized advertisement.
Researchers and developers collect user contextual attributes (eg, location, time, history …

A recommendation system is often used to recommend items that may be of interest to users.
One of the main challenges is that the scarcity of actual interaction data between users and …

Online advertisements have a significant influence over the success or failure of your
business. Therefore, it is important to somehow measure the impact of your advertisement …

In order to overcome the problems of low accuracy, time-consuming and low user
satisfaction in traditional methods, a digital English teaching materials recommendation …