MODEL: Motif-Based Deep Feature Learning for Link Prediction

Lei Wang, Jing Ren, Bo Xu, Jianxin Li, Wei Luo, Feng Xia
2020 IEEE Transactions on Computational Social Systems  
Link prediction plays an important role in network analysis and applications. Recently, approaches for link prediction have evolved from traditional similarity-based algorithms into embedding-based algorithms. However, most existing approaches fail to exploit the fact that real-world networks are different from random networks. In particular, real-world networks are known to contain motifs, natural network building blocks reflecting the underlying network-generating processes. In this paper, we
more » ... propose a novel embedding algorithm that incorporates network motifs to capture higher-order structures in the network. To evaluate its effectiveness for link prediction, experiments were conducted on three types of networks: social networks, biological networks, and academic networks. The results demonstrate that our algorithm outperforms both the traditional similarity-based algorithms by 20% and the state-of-the-art embedding-based algorithms by 19%.
doi:10.1109/tcss.2019.2962819 fatcat:e2t5pzsu5zayhlawv5fe7j3lie