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

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

ISBN-10: 3642212867

ISBN-13: 9783642212864

This ebook constitutes the refereed court cases of the eighth foreign Workshop on Algorithms and versions for the Web-Graph, WAW 2011, held in Atlanta, GA, in could 2011 - co-located with RSA 2011, the fifteenth foreign convention on Random constructions and Algorithms.
The thirteen revised complete papers awarded including 1 invited lecture have been conscientiously reviewed and chosen from 19 submissions. Addressing a wide selection of subject matters concerning the research of the Web-graph resembling theoretical and empirical research, the papers characteristic unique study by way of algorithmic and mathematical research in all components touching on the World-Wide internet with particular concentration to the view of complicated information as networks.

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Read Online 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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In: Friedman, J. ) 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.

Cω , a, b, . . , z). a=1 b=1 z=1 For a large number of clusterings or large K this quickly becomes inconvenient. In these cases we order the clusterings by adding new clusterings to the set based on maximizing the minimum pairwise distance to every other clustering currently in the set. This process is seeded with the informationally maximal pair within the set. This does not avoid triple-wise information overlap but works well in practice.

IPCO 2004. LNCS, vol. 3064, pp. 325–337. Springer, Heidelberg (2004) 8. : Statistical properties of community structure in large social and information networks. In: Proc. 18th Int’l World Wide Web Conf. WWW (2008) 9. : Finding strongly-knit clusters in social networks. Internet Mathematics 5(1-2), 155–174 (2009) 10. : Detecting community structure in networks. The European Physical J. B 38, 321–330 (2004) 11. : Fast algorithm for detecting community structure in networks. Phys. Rev. E 69, 066133 (2004) 12.

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Algorithms and Models for the Web Graph: 8th International Workshop, WAW 2011, Atlanta, GA, USA, May 27-29, 2011. Proceedings by Evimaria Terzi, Marco Winkler (auth.), Alan Frieze, Paul Horn, Paweł Prałat (eds.)


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