Download Algorithms and Models for the Web Graph: 8th International by Evimaria Terzi, Marco Winkler (auth.), Alan Frieze, Paul PDF

By Evimaria Terzi, Marco Winkler (auth.), Alan Frieze, Paul Horn, Paweł Prałat (eds.)

This booklet constitutes the refereed complaints of the eighth foreign Workshop on Algorithms and types for the Web-Graph, WAW 2011, held in Atlanta, GA, in could 2011 - co-located with RSA 2011, the fifteenth overseas convention on Random constructions and Algorithms.
The thirteen revised complete papers offered including 1 invited lecture have been conscientiously reviewed and chosen from 19 submissions. Addressing a wide selection of subject matters with regards to the learn of the Web-graph reminiscent of theoretical and empirical research, the papers characteristic unique examine when it comes to algorithmic and mathematical research in all parts concerning the World-Wide net with specific concentration to the view of advanced information as networks.

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Read or Download Algorithms and Models for the Web Graph: 8th International Workshop, WAW 2011, Atlanta, GA, USA, May 27-29, 2011. Proceedings PDF

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30 J. He et al. Next, we give a heuristic algorithm for finding an (α, β)-community of size k in a graph G = (V, E). A mathematical description of this (α, β)-Community algorithm, along with a subroutine called Swapping, is given above. See [6] for more details. 1 Experimental Results Social Graphs Twitter. The Twitter dataset [1, 2] corresponds to a directed friendship graph among a subset of Twitter user accounts. Each vertex represents an individual Twitter user account, and each edge represents a following relation from one user to another.

Phys. Rev. E 74, 036104 (2006) 13. : Modularity and community structure in networks. Proc. Natl. Acad. Sci. USA 103(23), 8577–8582 (2006) 14. : Finding and evaluating community structure in networks. Phys. Rev. E 69, 026113 (2004) 15. : Graph clustering. gov Abstract. We study clustering on graphs with multiple edge types. Our main motivation is that similarities between objects can be measured in many different metrics, and so allowing graphs with multivariate edges significantly increases modeling power.

Expanding graphs DIMACS series, pp. : An upper bound on the diameter of a graph from eigenvalues associated with its Laplacian. Siam. J. Disc. Math. : Spectral graph theory. AMS Publications. : Laplacians and the Cheeger inequality for directed graphs. Annals of Comb. : The diameter and Laplacian eigenvalues of directed graphs. : Loose Hamilton cycles in random 3-uniform hypergraphs. : 3 Dirac-type results for loose Hamilton cycles in uniform hypergraphs. J. Comb. Theory Ser. : Hamiltonian chains in hypergraphs.

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