Link prediction algorithm based on the Choquet fuzzy integral

Abstract

Link prediction is a fundamental problem in network data analysis, which has attracted increasing attention from many fields, with many new advances. In particular, many structure similarity-based algorithms that only use network topology information have been applied because of their simple framework. The prediction accuracy of these methods depends on the compatibility between the algorithm definition and the structural characteristics of the target network, so the stability of structure similarity-based algorithms is low. Thus, these algorithms may obtain good results with some networks but fail with others. Given the ambiguous relationships between these algorithms, we propose a Choquet fuzzy integral-based link prediction method, which integrates structure similarity-based algorithms via the Choquet fuzzy integral to improve the prediction accuracy and achieve more stable prediction performance. Empirical experiments using six real networks demonstrated that the proposed method outperformed the mainstream link prediction baseline methods.