A Concept Knowledge Graph for User Next Intent Prediction at Alipay
This addresses user intent prediction for Alipay's life-service domain, representing an incremental improvement with domain-specific deployment.
The paper tackles user intent prediction at Alipay by proposing AlipayKG, a concept knowledge graph modeling user behaviors and content, and a Transformer-based model integrating expert rules from the graph. The deployed system serves over 100 million daily active users and enhances downstream task performance while retaining explainability.
This paper illustrates the technologies of user next intent prediction with a concept knowledge graph. The system has been deployed on the Web at Alipay, serving more than 100 million daily active users. To explicitly characterize user intent, we propose AlipayKG, which is an offline concept knowledge graph in the Life-Service domain modeling the historical behaviors of users, the rich content interacted by users and the relations between them. We further introduce a Transformer-based model which integrates expert rules from the knowledge graph to infer the online user's next intent. Experimental results demonstrate that the proposed system can effectively enhance the performance of the downstream tasks while retaining explainability.