Link prediction in complex networks: A survey
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TLDR
Recent progress about link prediction algorithms is summarized, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods.Abstract:
Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labeled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.read more
Citations
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Experimental analyses on 2-hop-based and 3-hop-based link prediction algorithms
Tao Zhou,Yan-Li Lee,Guannan Wang +2 more
TL;DR: Wang et al. as mentioned in this paper implemented extensive experimental comparisons between 2-hop and 3-hop similarity indices on 137 real networks and found that 3-Hop-based indices are more suitable for disassortative networks with lower densities and lower average clustering coefficients.
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Measuring the complexity of complex network by Tsallis entropy
TL;DR: A novel structure entropy which is based on Tsallis entropy is introduced in this paper which combines the fractal dimension and local dimension which are both the significant property of network structure, and it would degenerate to the Shannon entropy based on the local dimension when fractaldimension equals to 1.
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A statistical infinite feature cascade-based approach to anomaly detection for dynamic social networks
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BookDOI
Advances in Artificial Intelligence: SBIA 2012
Leliane Nunes de Barros,Marcelo Finger,Aurora T. Pozo,Gustavo A. Gimenénez-Lugo,Marcos A. Castilho +4 more
TL;DR: This article proposes a formal methodology for knowledge representation in DeLP, that defines a set of guidelines to be used during this phase of knowledge representation, and results in an key tool to improve DeLP’s applicability to concrete domains.
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Evolving networks - Using past structure to predict the future
TL;DR: This study examines the use of links between a pair of nodes to predict their common neighbors and analyzes the relationship between the weight and the structure in static networks, evolving networks, and in the corresponding randomized networks.
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