SIGformer: Sign-aware Graph Transformer for Recommendation

Understand

In recommender systems, most graph-based methods focus on positive user feedback, while overlooking the valuable negative feedback.

• Integrating both positive and negative feedback to form a signed graph can lead to a more comprehensive understanding of user preferences.
• However, the existing efforts to incorporate both types of feedback are sparse and face two main limitations: 1) They process positive and negative feedback separately, which fails to holistically leverage the collaborative information within the signed graph; 2) They rely on MLPs or GNNs for information extraction from negative feedback, which may not be effective.
• To overcome these limitations, we introduce SIGformer, a new method that employs the transformer architecture to sign-aware graph-based recommendation.