Top-N Recommender System via Matrix Completion

Understand

Top-N recommender systems have been investigated widely both in industry and academia.

• However, the recommendation quality is far from satisfactory.
• In this paper, we propose a simple yet promising algorithm.
• We fill the user-item matrix based on a low-rank assumption and simultaneously keep the original information.