南京大学学报（自然科学版）2019，Vol.55Issue(4)：573-580,8.DOI:10.13232/j.cnki.jnju.2019.04.007
基于路径相互关注的网络嵌入算法
Path?based mutual attention algorithm for network embedding
摘要
Abstract
Network embedding, or network representation learning, aims to map nodes in the network into the representation space and generate low?dimensional dense vectors to represent the nodes in the network while preserving the network structure information, then solve downstream tasks such as link prediction, node classification, community discovery and network visualization through existing machine learning methods. The random walk algorithm can well explore the structure of nodes in the network. However,the previous representation learning algorithm based on random walk can only generate one kind of embedding for one node,without considering that the nodes play different roles when interacting with different neighbors. Therefore, this paper proposes a network embedding algorithm based on mutual attention of paths. Through the context information generated by random walks of nodes, each node generates a node embedding in which contexts are of mutual attention. And our algorithm has better performance than the three classic network embedding algorithms.关键词
网络表示学习/随机游走/相互关注/注意力机制Key words
network representation learning/random walk/mutual attention/attention mechanism分类
信息技术与安全科学引用本文复制引用
钱付兰,黄鑫,赵姝,张燕平..基于路径相互关注的网络嵌入算法[J].南京大学学报（自然科学版）,2019,55(4):573-580,8.基金项目
国家重点研究与发展项目(2017YFB1401903),国家自然科学基金(61673020,61702003,61876001),安徽省自然科学基金(1808085MF175) （2017YFB1401903）
