Google published a research paper about helping recommender systems understand what users mean when they interact with them. Their goal with this new approach is to overcome the limitations inherent ...

This excerpt is taken from an MSiA student research blog posting. Each month, students in our program submit original extracurricular research as part of our blog competition. The winner(s) are ...

In the rapidly evolving digital era, the quest for personalized user experiences has led to an explosion in the development of recommender systems (RSs). These systems are the driving force behind the ...

Information Science Department Chair and Professor Robin Burke conducts research in personalized recommender systems, a field he helped found and develop. His most recent projects explore fairness, ...

One of the limitation of any recommender system is recommending a product to a new user. The user profile is built based on the ratings predicted from the tweets of the user about the restaurants. Now ...

Google has successfully utilized machine learning technology to create accurate personalized, situational app recommendation systems, having boosted the installation rate for apps at Google Play by ...

The rebellious growth of the mobile application market has made it a significant challenge for the users to find relevant applications in crowded application stores. To diminish this problem, existing ...