
Preface  Preview Material  Table of Contents  Supplementary Material 
CBMS Regional Conference Series in Mathematics 2006; 264 pp; softcover Number: 107 ISBN10: 0821836579 ISBN13: 9780821836576 List Price: US$57 Member Price: US$45.60 All Individuals: US$45.60 Order Code: CBMS/107 See also: A Course on the Web Graph  Anthony Bonato The Game of Cops and Robbers on Graphs  Anthony Bonato and Richard J Nowakowski  Through examples of large complex graphs in realistic networks, research in graph theory has been forging ahead into exciting new directions. Graph theory has emerged as a primary tool for detecting numerous hidden structures in various information networks, including Internet graphs, social networks, biological networks, or, more generally, any graph representing relations in massive data sets. How will we explain from first principles the universal and ubiquitous coherence in the structure of these realistic but complex networks? In order to analyze these large sparse graphs, we use combinatorial, probabilistic, and spectral methods, as well as new and improved tools to analyze these networks. The examples of these networks have led us to focus on new, general, and powerful ways to look at graph theory. The book, based on lectures given at the CBMS Workshop on the Combinatorics of Large Sparse Graphs, presents new perspectives in graph theory and helps to contribute to a sound scientific foundation for our understanding of discrete networks that permeate this information age. Readership Graduate students and research mathematicians interested in combinatorics (graph theory) and its applications to large networks. Reviews "This is a wellstructured and useful book for researchers in random graphs, combinatorics and computer science. Because of its selfcontained nature, and the careful way the topics are introduced, it is a good text for graduate level courses in the subject."  Colin D. Cooper for Mathematical Reviews 


AMS Home 
Comments: webmaster@ams.org © Copyright 2014, American Mathematical Society Privacy Statement 