Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching. (arXiv:2304.03215v1 [cs.LG])

Cross-device user matching is a critical problem in numerous domains,
including advertising, recommender systems, and cybersecurity. It involves
identifying and linking different devices belonging to the same person,
utilizing sequence logs. Previous data mining techniques have struggled to
address the long-range dependencies and higher-order connections between the
logs. Recently, researchers have modeled this problem as a graph problem and
proposed a two-tier graph contextual embedding (TGCE) neural network
architecture, which outperforms previous methods. In this paper, we propose a
novel …

address advertising architecture attention connections critical cybersecurity data data mining dependencies device devices domains higher logs mining network neural network novel order problem recommender systems researchers systems techniques