CDC: Causal Domain Clustering for Multi-Domain Recommendation

TL;DR

This paper introduces Causal Domain Clustering (CDC), a novel method for effectively grouping multiple domains in recommendation systems by modeling transfer patterns with causal discovery, leading to improved performance across diverse domains.

Contribution

CDC is the first approach to model domain transfer effects using causal discovery, enabling adaptive clustering and source domain selection for multi-domain recommendation.

Findings

Achieved a 4.9% increase in online eCPM.

Significantly improved recommendation performance across 50+ domains.

Demonstrated effectiveness in both public datasets and industrial settings.

Abstract

Multi-domain recommendation leverages domain-general knowledge to improve recommendations across several domains. However, as platforms expand to dozens or hundreds of scenarios, training all domains in a unified model leads to performance degradation due to significant inter-domain differences. Existing domain grouping methods, based on business logic or data similarities, often fail to capture the true transfer relationships required for optimal grouping. To effectively cluster domains, we propose Causal Domain Clustering (CDC). CDC models domain transfer patterns within a large number of domains using two distinct effects: the Isolated Domain Affinity Matrix for modeling non-interactive domain transfers, and the Hybrid Domain Affinity Matrix for considering dynamic domain synergy or interference under joint training. To integrate these two transfer effects, we introduce causal discovery to calculate a cohesion-based coefficient that adaptively balances their contributions. A Co-Optimized Dynamic Clustering algorithm iteratively optimizes target domain clustering and source domain selection for training. CDC significantly enhances performance across over 50 domains on public datasets and in industrial settings, achieving a 4.9% increase in online eCPM. Code is available at https://github.com/Chrissie-Law/Causal-Domain-Clustering-for-Multi-Domain-Recommendation