Session-based Recommendation with Self-Attention Networks

Understand

Session-based recommendation aims to predict user's next behavior from current session and previous anonymous sessions.

• Capturing long-range dependencies between items is a vital challenge in session-based recommendation.
• A novel approach is proposed for session-based recommendation with self-attention networks (SR-SAN) as a remedy.
• The self-attention networks (SAN) allow SR-SAN capture the global dependencies among all items of a session regardless of their distance.