Automatic response forecasting for news media plays a crucial role in enabling content
producers to efficiently predict the impact of news releases and prevent unexpected …

Attributed graph clustering aims to partition the nodes in a graph into groups such that the
nodes in the same group are close in terms of graph proximity and also have similar attribute …

Dynamic graph learning equips the edges with time attributes and allows multiple links
between two nodes, which is a crucial technology for understanding evolving data scenarios …

Many real-world applications can be formulated as event forecasting on Continuous Time
Dynamic Graphs (CTDGs) where the occurrence of a timed event between two entities is …

Temporal networks represent the evolving complex systems by regarding the contained
elements as nodes and their connections as edges, respectively, which are both time …

Dynamic graph link prediction is widely utilized in the complex web of the real world, such as
social networks, citation networks, recommendation systems, etc. Recent Transformer-based …

Dynamic link prediction aims to predict the future links on dynamic graphs, which can be
applied to wide scenarios such as recommender systems and social networks on the World …

Abstract Knowledge Graph Representation Learning has drawn great attention in the
Artificial Intelligence (AI) and Knowledge Graph (KG) domains. It aims to represent entities …