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GMCM: Graph-based Micro-behavior Conversion Model for Post-click Conversion Rate Estimation
Wentian Bao (Alibaba Group (China)), Hong Wen (Alibaba Group (China)), Sha Li (University of Illinois Urbana-Champaign), Xiaoyang Liu (Columbia University), Quan Lin (Alibaba Group (China)), Keping Yang (Alibaba Group (China))
Résumé : Purchase-related micro-behaviors, e.g., favorite, add to cart, read reviews, etc., provide implicit feedback of users' decision-making process. Such informative feedback can lead to fine-grained post-click conversion rate (CVR) modeling of the buying process. However, most existing works on CVR estimation either neglect these informative feedback, or model them as a sequential pattern with Recurrent Neural Networks. We argue such modeling could be inappropriate since different orders of micro-behaviors may represent similar user buying intention, and micro-behaviors often correlate with each other.