Interaction Event Forecasting in Multi-Relational Recursive HyperGraphs: A Temporal Point Process Approach

arXiv:2404.17943v1 Announce Type: new
Abstract: Modeling the dynamics of interacting entities using an evolving graph is an essential problem in fields such as financial networks and e-commerce. Traditional approaches focus primarily on pairwise interactions, limiting their ability to capture the complexity of real-world interactions involving multiple entities and their intricate relationship structures. This work addresses the problem of forecasting higher-order interaction events in multi-relational recursive hypergraphs. This is done using a dynamic graph representation learning framework that can capture complex …

abstract arxiv commerce complexity cs.ai cs.lg cs.si dynamics e-commerce event event forecasting fields financial focus forecasting graph interactions modeling multiple networks process recursive relational temporal type world