Modeling impression discounting in large-scale recommender systems
Pei Lee, Laks V. S. Lakshmanan, Mitul Tiwari, Sam Shah · 2014
Recommender systems have become very important for many online activities, such as watching movies, shopping for products, and connecting with friends on social networks. User behavioral analysis and user feedback (both explicit and implicit) modeling are crucial for the improvement of any online recommender system. Widely adopted recommender systems at LinkedIn such as "People You May Know" and "Endorsements" are evolving by analyzing user behaviors on impressed recommendation items.