
Graph Mining
Laws, Tools, and Case Studies
Morgan & Claypool Publishers
Published on 30. October 2012
Book
Paperback/Softback
207 pages
978-1-60845-115-9 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
San Rafael
United States
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 187 mm
Weight
333 gr
ISBN-13
978-1-60845-115-9 (9781608451159)
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Schweitzer Classification
Content
- 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
- 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