  Recovering and reconstructing networks by accurately identifying missing and
unreliable links is a vital task in the domain of network analysis and mining.
In this article, by studying a specific local structure, namely a degree block
having a node and its all immediate neighbors, we find it contains important
statistical features of link formation for complex networks. We therefore
propose a parameter-free local blocking (LB) predictor to quantitatively detect
link formation in given networks via local link density calculations. The
promising experimental results performed on six real-world networks suggest
that the new index can outperform other traditional local similarity-based
methods on most of tested networks. After further analyzing the scores'
correlations between LB and two other methods, we find that the features of LB
index are analogous to those of both PA index and short-path-based index, which
empirically verify that large degree principle and short path principle
simultaneously captured by the LB index are jointly driving link formation in
complex networks.
