By Abraham D. Flaxman, Juan Vera (auth.), Anthony Bonato, Fan R. K. Chung (eds.)

This e-book constitutes the refereed complaints of the fifth overseas Workshop on Algorithms and versions for the Web-Graph, WAW 2007, held in San Diego, CA, united states, in December 2007 - colocated with WINE 2007, the 3rd overseas Workshop on net and community Economics.

The thirteen revised complete papers and 5 revised brief papers offered have been rigorously reviewed and chosen from a wide pool of submissions for inclusion within the booklet. The papers handle a large choice of subject matters relating to the research of the Web-graph comparable to random graph versions for the Web-graph, PageRank research and computation, decentralized seek, neighborhood partitioning algorithms, and traceroute sampling.

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Extra info for Algorithms and Models for the Web-Graph: 5th International Workshop, WAW 2007, San Diego, CA, USA, December 11-12, 2007. Proceedings

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Algorithmica 29(3), 410– 421 (2001) 16. : Approximation algorithms for maximization problems arising in graph partitioning. Journal of Algorithms 41, 174–211 (2001) 17. : On the densest k-subgraph problem. Technical report, Department of Applied Mathematics and Computer Science, The Weizmann Institute, Rehovot (1997) 18. : On the hierarchical structure of the logical Internet graph. In: SPIE ITCOM (August 2001) 19. : Property testing and its connections to learning and approximation. J. ACM 45, 653–750 (1998) 20.

The Web as a graph. In: PODS 2000. Proc. 19th ACM SIGACT-SIGMODAIGART Symp. Principles of Database Systems, pp. 1–10. ACM Press, New York (2000) 11. : Analytic Perturbation Theory and its Applications. PhD thesis, University of South Australia (1999) 12. : Mathematical foundations of the state lumping of large systems. Mathematics and its Applications, vol. 264. Kluwer Academic Publishers, Dordrecht (1993) 13. : Theory of Suboptimal Decisions. Mathematics and its Applications (Soviet Series), vol.

This model yields a graph with power-law degree distribution where the expansion property depends on a tunable parameter of the model. The vertices of Gn are n sequentially generated points x1 , x2 , . . , xn chosen uniformly at random from the unit sphere in R 3 . After generating xt , we randomly connect it to m points from those points in x1 , x2 , . . , xt−1 .... 1 Introduction During the last decade a large body of research has centered on understanding and modeling the structure of large-scale networks like the Internet and the World Wide Web.

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