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Recommender Systems Lab

Welcome to the Recommender Systems Lab!

Our current focus is using deep learning techniques to build concise representations of the meanings of a user's context and use these powerful features to provide accurate personal recommendations.
We are doing projects with full cooperation with, KBC Bank, and the Israel Innovation Authority (IIA). 

We aim to improve existing recommendation systems by leveraging auxiliary side information that can provide additional
valuable insights.

Our main research topics are:

  1. New latent representation of sequential contextual side information within Context-Aware Recommendation Systems

  2. Boosting Recommendation Systems Using Side Information for CTR Prediction

  3. Context-Aware Recommendation System Utilizing Evolutionary Algorithms

  4. Incorporate Calibrated Reviews in Recommendation Systems

  5. Movie Recommendation Based on Movie Transcripts


We are always looking for new team members! If you are interested in our research, don't hesitate, and feel free to contact

Lab Research Team

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