2-5 复杂认知图神经网络及其应用.pdf

1、复杂认知图神经网络金弟2022.6.25图机器学习峰会图机器学习峰会20222022：复杂图论坛：复杂图论坛Outline1.面向复杂图的图神经网络2.认知图神经网络2GNN on Universal NetworksGNN on Text-rich NetworksGNN on Attribute Missing HINsGNN on Higher-order Dependency NetworksGNN on Complex Networks31.GNN on Universal Networksbeyond topological limitationsZacharys Karate C

2、lubHomophily Social Networks Citation NetworksMajority of linked nodes are similarAuction Network Protein Structures Transaction NetworksMajority of linked nodes are differentHeterophily Railway NetworksRandomnessER Random NetworkMajority of linked nodes are randomWhether networks with different str

3、uctural properties should adopt different propagation mechanisms?Di Jin,et al,Universal Graph Convolutional Networks,NeurIPS 20214MotivationD.Brockmann and D.Helbing.The hidden geometry of complex,network-driven contagion phenomena.Science,342(6164):1337-1342,2013.5Motivating Observations6MethodA un

4、iversal GCN model may not only consider the 1-hop network neighbors,but also the 2-hop neighbors andkNN for direct information propagation.More importantly,considering different network properties can be morecorrelated with one of them or even their combinations,the model itself should adaptively le

5、arn theircorresponding importance,so as to achieve feature fusion more effectively.Multi-type Convolution MechanismDiscriminativeAggregationFor 2-hop adjacency matrix,considering that the number of neighbors at exactly 2-hops away may raiseexponentially with the increase of network scale,we introduc

6、e a constraint,i.e.,select node pairs connected by atleast two different paths for each node to set edges.For kNN adjacency matrix,we adopt the cosine value of the angle between two vectors to measure the similarity.We perform a discriminative aggregation utilizing the attention mechanism,so as to l