A survey on influence maximization: From an ml-based combinatorial optimization
Influence Maximization (IM) is a classical combinatorial optimization problem, which can be
widely used in mobile networks, social computing, and recommendation systems. It aims at …
widely used in mobile networks, social computing, and recommendation systems. It aims at …
Minimizing the influence of misinformation via vertex blocking
Information cascade in online social networks can be rather negative, eg, the spread of
rumors may trigger panic. To limit the influence of misinformation in an effective and efficient …
rumors may trigger panic. To limit the influence of misinformation in an effective and efficient …
Graph neural rough differential equations for traffic forecasting
Traffic forecasting is one of the most popular spatio-temporal tasks in the field of machine
learning. A prevalent approach in the field is to combine graph convolutional networks and …
learning. A prevalent approach in the field is to combine graph convolutional networks and …
HCCKshell: A heterogeneous cross-comparison improved Kshell algorithm for Influence Maximization
Influence maximization (IM) has been extensively researched in the information propagation
field and applied in various domains. However, existing studies on the IM have primarily …
field and applied in various domains. However, existing studies on the IM have primarily …