Path-based extensions of local link prediction methods for complex networks

Link prediction in a complex network is a problem of fundamental interest in network science and has attracted increasing attention in recent years. It aims to predict missing (or future) links between two entities in a complex system that are not already connected. Among existing methods, local similarity indices are most popular that take into account the information of common neighbours to estimate the likelihood of existence of a connection between two nodes. In this paper, we propose global and quasi-local extensions of some commonly used local similarity indices. We have performed extensive numerical simulations on publicly available datasets from diverse domains demonstrating that the proposed extensions not only give superior performance, when compared to their respective local indices, but also outperform some of the current, state-of-the-art, local and global link-prediction methods.

[1]  Linyuan Lü,et al.  Predicting missing links via local information , 2009, 0901.0553.

[2]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[3]  Pavel Yu. Chebotarev,et al.  The Matrix-Forest Theorem and Measuring Relations in Small Social Groups , 2006, ArXiv.

[4]  G. Makhatadze.  Linking computation and experiments to study the role of charge–charge interactions in protein folding and stability , 2017, Physical biology.

[5]  Linyuan Lu,et al.  Link Prediction in Complex Networks: A Survey , 2010, ArXiv.

[6]  Ciro Cattuto,et al.  What's in a crowd? Analysis of face-to-face behavioral networks , 2010, Journal of theoretical biology.

[7]  Caixia Liu,et al.  Extended resource allocation index for link prediction of complex network , 2017 .

[8]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Leo Katz,et al.  A new status index derived from sociometric analysis , 1953 .

[10]  Roger Guimerà,et al.  Extracting the hierarchical organization of complex systems , 2007, Proceedings of the National Academy of Sciences.

[11]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[12]  Linyuan Lü,et al.  Similarity index based on local paths for link prediction of complex networks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  P. Jaccard,et al.  Etude comparative de la distribution florale dans une portion des Alpes et des Jura , 1901 .

[14]  Jérôme Kunegis,et al.  KONECT: the Koblenz network collection , 2013, WWW.

[15]  S. Shen-Orr,et al.  Network motifs in the transcriptional regulation network of Escherichia coli , 2002, Nature Genetics.

[16]  Zhan Su,et al.  Link prediction in recommender systems based on multi-factor network modeling and community detection , 2019, EPL (Europhysics Letters).

[17]  H. White,et al.  “Structural Equivalence of Individuals in Social Networks” , 2022, The SAGE Encyclopedia of Research Design.

[18]  Wilhelm Rödder,et al.  An entropy-based framework to analyze structural power and power alliances in social networks , 2020, Scientific Reports.

[19]  Timothy Ravasi,et al.  From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks , 2013, Scientific Reports.

[20]  Xiao-Dong Zhang,et al.  Predicting missing links in complex networks based on common neighbors and distance , 2016, Scientific Reports.

[21]  Hairong Qi,et al.  Friendbook: A Semantic-Based Friend Recommendation System for Social Networks , 2015, IEEE Transactions on Mobile Computing.

[22]  T. Sørensen,et al.  A method of establishing group of equal amplitude in plant sociobiology based on similarity of species content and its application to analyses of the vegetation on Danish commons , 1948 .

[23]  A Díaz-Guilera,et al.  Self-similar community structure in a network of human interactions. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  Toni Vallès-Català,et al.  Consistencies and inconsistencies between model selection and link prediction in networks. , 2017, Physical review. E.

[25]  Ye Yuan,et al.  Link prediction via linear optimization , 2018, Physica A: Statistical Mechanics and its Applications.

[26]  M. E. J. Newman,et al.  Estimating network structure from unreliable measurements , 2018, Physical Review E.

[27]  Jing Zhao,et al.  Prediction of Links and Weights in Networks by Reliable Routes , 2015, Scientific Reports.

[28]  唐翌,et al.  Link prediction based on a semi-local similarity index , 2011 .

[29]  Mahdi Jalili,et al.  A hybrid method of link prediction in directed graphs , 2021, Expert Syst. Appl..

[30]  S. Weiss,et al.  Predicting miRNA-based disease-disease relationships through network diffusion on multi-omics biological data , 2020, Scientific Reports.

[31]  Muhammad Usman Akhtar,et al.  Missing Link Prediction using Common Neighbor and Centrality based Parameterized Algorithm , 2020, Scientific Reports.

[32]  W. Zachary,et al.  An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.

[33]  B. Snel,et al.  Comparative assessment of large-scale data sets of protein–protein interactions , 2002, Nature.

[34]  Alessandro Vespignani,et al.  Reaction–diffusion processes and metapopulation models in heterogeneous networks , 2007, cond-mat/0703129.

[35]  Anna Korhonen,et al.  Link prediction in drug-target interactions network using similarity indices , 2017, BMC Bioinformatics.

[36]  Konstantin Avrachenkov,et al.  Cooperative Game Theory Approaches for Network Partitioning , 2017, COCOON.

[37]  M. Newman,et al.  Vertex similarity in networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  Ryan A. Rossi,et al.  The Network Data Repository with Interactive Graph Analytics and Visualization , 2015, AAAI.

[39]  A. Arenas,et al.  Community detection in complex networks using extremal optimization. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  Jinseop S. Kim,et al.  From Caenorhabditis elegans to the human connectome: a specific modular organization increases metabolic, functional and developmental efficiency , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[41]  Lada A. Adamic,et al.  Friends and neighbors on the Web , 2003, Soc. Networks.

[42]  Roger Guimerà,et al.  Consistencies and inconsistencies between model selection and link prediction in networks. , 2017, Physical review. E.

[43]  M. E. J. Newman,et al.  Network structure from rich but noisy data , 2017, Nature Physics.

[44]  Hafida Benhidour,et al.  A Scalable Similarity-Popularity Link Prediction Method , 2020, Scientific Reports.

[45]  François Fouss,et al.  Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation , 2007, IEEE Transactions on Knowledge and Data Engineering.

[46]  Jennifer Widom,et al.  SimRank: a measure of structural-context similarity , 2002, KDD.

[47]  A. Barabasi,et al.  Universal resilience patterns in complex networks , 2016, Nature.

[48]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .