Self-supervised multi-stages set expansion for session-based recommendation

Key Points

• Enhanced accuracy in session-based recommendation systems through self-supervised approaches.
• The method significantly reduces reliance on traditional collaborative filtering techniques for improving recommendations.
• Implementation of a multi-stage set expansion strategy demonstrates noteworthy improvements in user engagement.
• The findings suggest a necessary shift towards self-supervised techniques in recommendation system development.