EAN: 9783031007750

Bilder-Quelle: discount24.de - Sport-Freizeit

What does the Web look like? How can we find patterns communities outliers in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings for example in social networks computer-communication networks (intrusion detection traffic management) protein-protein interaction networks in biology document-text bipartite graphs in text retrieval person-account graphs in financial fraud detection and others. In this work first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important because they can help with what if scenarios extrapolations and anonymization. Then we provide a list of powerful tools for graph analysis and specifically spectral methods (Singular Value Decomposition (SVD)) tensors and case studies like the famous pageRank algorithm and the HITS algorithm for ranking web search results. Finally we conclude with a survey of tools and observations from related fields like sociology which provide complementary viewpoints. Table of Contents: Introduction Patterns in Static Graphs Patterns in Evolving Graphs Patterns in Weighted Graphs Discussion: The Structure of Specific Graphs Discussion: Power Laws and Deviations Summary of Patterns Graph Generators Preferential Attachment and Variants Incorporating Geographical Information The RMat Graph Generation by Kronecker Multiplication Summary and Practitioner's Guide SVD Random Walks and Tensors Tensors Community Detection Influence Virus Propagation and Immunization Case Studies Social Networks Other Related Work Conclusions

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30.03.2025 um 23:42 Uhr

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