Multi-order hyperbolic graph convolution and aggregated attention for social event detection
Fig 5
The overall framework of this study: First, the data representation and its corresponding adjacency matrix are obtained.
Next, is mapped into hyperbolic space via the function, producing its hyperbolic representation. Then, the
function is applied to project onto its tangent space, yielding the representation
. On this basis, a multi-order graph convolution network is employed to derive the multi-order representation
. Subsequently, an attention-based network is used to generate the hyperbolic multi-order graph representation
. Finally, the convolution attention representation
is mapped into a new hyperbolic space through the
function, resulting in the hyperbolic representation
.