  Information entropy has been proved to be an effective tool to quantify the
structural importance of complex networks. In the previous work (Xu et al, 2016
\cite{xu2016}), we measure the contribution of a path in link prediction with
information entropy. In this paper, we further quantify the contribution of a
path with both path entropy and path weight, and propose a weighted prediction
index based on the contributions of paths, namely Weighted Path Entropy (WPE),
to improve the prediction accuracy in weighted networks. Empirical experiments
on six weighted real-world networks show that WPE achieves higher prediction
accuracy than three typical weighted indices.
