title: Local degree blocking model for link prediction in complex networks.
abstract: 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 LB index simultaneously captures the features of both PA index and short-path-based index, which empirically verifies that LB index is a multiple-mechanism-driven link predictor.
authors: Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors: Zhen
authors: Z
authors: Liu
authors: Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors: Weike
authors: W
authors: Dong
authors: Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors: Yan
authors: Y
authors: Fu