2015/02/15 by Maosheng Jiang, Jiang, Maosheng, Yonxiang Chen +3 · 1 citation
Computer Science · Physics and Astronomy · #Advanced Clustering Algorithms Research #Advanced Graph Neural Networks #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #cs.SI #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1502.04380
13 pages, 2 tables. arXiv admin note: text overlap with arXiv:1112.3265 by other authors
arxiv created 2015/02/15 · openalex publication_date 2015/02/15 · arxiv updated 2015/02/17 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
The problem of link prediction has attracted considerable recent attention from various domains such as sociology, anthropology, information science, and computer sciences. A link prediction algorithm is proposed based on link similarity score propagation by a random walk in networks with nodes attributes. In the algorithm, each link in the network is assigned a transmission probability according to the similarity of the attributes on the nodes connected by the link. The link similarity score between the nodes are then propagated via the links according to their transmission probability. Our experimental results show that it can obtain higher quality results on the networks with node attributes than other algorithms.