GMCM: Graph-based Micro-behavior Conversion Model for Post-click Conversion Rate Estimation
Wentian Bao, Hong Wen, Sha Li, Xiaoyang Liu, Quan Lin, Keping Yang
Abstract
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.
Topics & Concepts
Computer scienceCartProcess (computing)GraphEstimationNeglectArtificial intelligenceClick-through rateArtificial neural networkMachine learningHuman–computer interactionTheoretical computer scienceInformation retrievalPsychologyManagementMechanical engineeringPsychiatryOperating systemEconomicsEngineeringComplex Network Analysis TechniquesRecommender Systems and TechniquesImage and Video Quality Assessment