Signed networks are such social networks having both positive and negative links. A lot of
theories and algorithms have been developed to model such networks (eg, balance theory) …

The maximum clique problem, which is to find the clique with the largest size, can find many
real-world applications and is notable for its capability of modeling many combinatorial …

Given that most of the link prediction algorithms for signed social networks can only
complete sign prediction, a novel algorithm is proposed aiming to achieve both link …

Community detection and link prediction are two basic tasks of complex network system
analysis, which are widely used in the detection of telecom fraud organizations and …

Graph representations have increasingly grown in popularity during the last years. Existing
representation learning approaches explicitly encode network structure. Despite their good …

Signed networks contain nodes connected by positive and negative signed links. Signed
network representation learning concentrates on learning the low-dimensional …

Signed network embedding concentrates on learning fixed-length representations for nodes
in signed networks with positive and negative links, which contributes to many downstream …