26 citations · 45 across the 3 of their papers we have counts for
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cs.LG2020★ 26 cited
Evolving Context-Aware Recommender Systems With Users in Mind
Amit Livne, Eliad Shem Tov, Adir Solomon +3
A context-aware recommender system (CARS) applies sensing and analysis of user context to provide personalized services. The contextual information can be driven from sensors in or…
cs.LG2020★ 3 cited
Iterative Boosting Deep Neural Networks for Predicting Click-Through Rate
Amit Livne, Roy Dor, Eyal Mazuz +3
The click-through rate (CTR) reflects the ratio of clicks on a specific item to its total number of views. It has significant impact on websites' advertising revenue. Learning soph…
cs.LG2019★ 16 cited
Deep Context-Aware Recommender System Utilizing Sequential Latent Context
Amit Livne, Moshe Unger, Bracha Shapira +1
Context-aware recommender systems (CARSs) apply sensing and analysis of user context in order to provide personalized services. Adding context to a recommendation model is challeng…