… of social networks, but the standard link prediction framework does not directly predict these
… new link prediction task called “pairwise link prediction” that directly targets the prediction of …

… pairwise learning neural link prediction framework in this paper, named PLNLP. The
framework adopts a pairwise … , ie, neighborhood encoder, link predictor, negative sampler and …

… of social networks, but the standard link prediction framework does not directly predict these
… new link prediction task called “pairwise link prediction” that directly targets the prediction of …

… patterns that can be associated with facts for link prediction. In this article, we propose a
Pairwise Factorization Model as a decoder for the link prediction task. The decoder is based on …

… the pairwise encodings for each link. LPFormer models the link factors via an attention module
that learns the pairwise … multiple factors integral to link prediction. Extensive experiments …

… systems by using a model of pairwise interactions. But much of … propose higher-order link
prediction as a benchmark problem … difference from traditional pairwise link prediction, with a …

… There exists a wide range of link prediction techniques like … To make it general, this review
also covers link prediction in … pairwise vertices from all the neighbors of either vertex. The …

… In this work, we instead regard it as a pairwise link prediction task. If for any … pairwise links
between time frames as belonging to the same section (or segment) or not. The resulting link …

… -of-the-art of the link prediction in social networks. A systematical category for link prediction
techniques and problems is presented. Then link prediction techniques and problems are …

… not preserve the original pairwise proximity at each hidden … link prediction method named
Pairwise Proximity Preserving Graph neural network (PPPG), which can preserve the pairwise …