Graph Mining: Laws, Tools, and Case Studies
Author:   Deepayan Chakrabarti ,  Christos Faloutsos
Publisher:   Springer International Publishing AG
ISBN:  

9783031007750


Pages:   191
Publication Date:   18 October 2012
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Graph Mining: Laws, Tools, and Case Studies


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Author:   Deepayan Chakrabarti ,  Christos Faloutsos
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Weight:   0.401kg
ISBN:  

9783031007750


ISBN 10:   3031007751
Pages:   191
Publication Date:   18 October 2012
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.
Language:   English

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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Author Information

Dr. Deepayan Chakrabarti obtained his Ph.D. from Carnegie Mellon University in 2005. He was a Senior Research Scientist with Yahoo, and now with Facebook Inc. He has published over 35 refereed articles and is the co-inventor of the RMat graph generator (the basis of the graph500 supercomputer benchmark). He is the co-inventor in over 20 patents (issued or pending). He has given tutorials in CIKM and KDD, and his interests include graph mining, computational advertising, and web search. Christos Faloutsos is a Professor at Carnegie Mellon University and an ACM Fellow. He has received the Research Contributions Award in ICDM 2006, the SIGKDD Innovations Award (2010), 18 ""best paper"" awards (including two ""test of time"" awards), and four teaching awards. He has published over 200 refereed articles, and has given over 30 tutorials. His research interests include data mining for graphs and streams, fractals, and self-similarity, database performance, and indexing for multimedia and bio-informatics data.

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