We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
This paper examines important factors for link prediction in networks and provides a general, high-performance framework for the prediction task. Link prediction in sparse network...
Ryan Lichtenwalter, Jake T. Lussier, Nitesh V. Cha...
In the traditional link prediction problem, a snapshot of a social network is used as a starting point to predict, by means of graph-theoretic measures, the links that are likely ...
Vincent Leroy, Berkant Barla Cambazoglu, Francesco...
Abstract—Many important real-world systems, modeled naturally as complex networks, have heterogeneous interactions and complicated dependency structures. Link prediction in such ...
Darcy A. Davis, Ryan Lichtenwalter, Nitesh V. Chaw...
— The quality of end-to-end services over wireless communication networks highly depends on the error characteristics of the wireless links. By utilizing the link error character...