基于节点表示和子图结构的动态网络链接预测

动态链接预测的关键是建模网络动态性和抽取局部结构特征.为此,文中提出基于节点表示和子图结构的动态链接预测方法.为了建模节点的动态演化特性,引入节点向量模型,按序拼接各个历史快照的节点表示.为了建模链接的局部子图结构信息,引入图同构算法,编码局部子图的拓扑结构.最终目标链接的特征表示融合每个历史快照中目标节点对的向量表征和局部子图的拓扑结构.实验表明文中方法性能较优.

Dynamic Network Link Prediction Based on Node Representation and Subgraph Structure

The key to dynamic link prediction is modeling network dynamics and extracting local structural features. Therefore, a method for dynamic network link prediction based on node representation and subgraph structure is proposed. To model node evolution dynamics, the node2vec model is introduced, and the node representations in historical snapshots are concatenated in temporal order. To model the local subgraph structure information, a graph isomorphism algorithm is employed to encode the topology structure of the local subgraph. In each historical snapshot, the node vectors of the target node pair and the topology structure of the local subgraph are fused by the ultimate feature representation of the target link. Extensive experiments demonstrate that the proposed method achieves better performance.