A Scalable Similarity-Popularity Link Prediction Method.

ABSTRACT: Link prediction is the task of computing the likelihood that a link exists between two given nodes in a network. With countless applications in different areas of science and engineering, link prediction has received the attention of many researchers working in various disciplines. Considerable research efforts have been invested into the development of increasingly accurate prediction methods. Most of the proposed algorithms, however, have limited use in practice because of their high computational requirements. The aim of this work is to develop a scalable link prediction algorithm that offers a higher overall predictive power than existing methods. The proposed solution falls into the class of global, parameter-free similarity-popularity-based methods, and in it, we assume that network

SUBMITTER: Kerrache S 

PROVIDER: S-EPMC7156691 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature