Graph Mining
eBook - PDF

Graph Mining

Laws, Tools, and Case Studies

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Graph Mining

Laws, Tools, and Case Studies

Book details
Table of contents
Citations

About This Book

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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Yes, you can access Graph Mining by Deepayan Chakrabarti,Christos Faloutsos in PDF and/or ePUB format, as well as other popular books in Informatica & Data mining. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Springer
Year
2022
ISBN
9783031019036
Topic
Informatica
Subtopic
Data mining

Table of contents

  1. Cover
  2. Copyright Page
  3. Title Page
  4. Dedication
  5. Contents
  6. Acknowledgments
  7. Introduction
  8. Patterns and Laws
  9. Graph Generators
  10. Tools and Case Studies
  11. Outreach—Related Work
  12. Resources
  13. Bibliography
  14. Authors' Biographies