
By Kevin J. Lang (auth.), Konstantin Avrachenkov, Debora Donato, Nelly Litvak (eds.)
ISBN-10: 3540959947
ISBN-13: 9783540959946
This booklet constitutes the refereed lawsuits of the sixth foreign Workshop on Algorithms and versions for the Web-Graph, WAW 2009, held in Barcelona, Spain, in February 2009 - co-located with WSDM 2009, the second one ACM overseas convention on net seek and information Mining.
The 14 revised complete papers awarded have been conscientiously reviewed and chosen from quite a few submissions for inclusion within the booklet. The papers tackle a large choice of themes on the topic of the examine of the Web-graph comparable to theoretical and empirical research of the internet graph and internet 2.0 graphs, random walks on the internet and net 2.0 graphs and their functions, and layout and function evaluate of the algorithms for social networks. The workshop papers were obviously clustered in 3 topical sections on graph versions for complicated networks, pagerank and net graph, and social networks and search.
Read Online or Download Algorithms and Models for the Web-Graph: 6th International Workshop, WAW 2009, Barcelona, Spain, February 12-13, 2009. Proceedings PDF
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Additional info for Algorithms and Models for the Web-Graph: 6th International Workshop, WAW 2009, Barcelona, Spain, February 12-13, 2009. Proceedings
Example text
We have I − L − ϕϕ∗ ≤ σ. Then, ˜ = |ρ − d| is the unit eigenvector of L corresponding A − dd∗ vol(G) ≤ A− dd∗ vol(G) = D1/2 (I − L − ϕϕ∗ )D1/2 ≤ D1/2 · I − L − ϕϕ∗ · D1/2 ≤ σΔ. 42 F. Chung, P. Horn, and L. Lu For any subset of the vertices, S, we let let S¯ denote the complement set of S. The vertex boundary of S in G, denoted by Γ G (S) is defined as follows: Γ G (S) = {u ∈ S | ∃v ∈ S such that {u, v} ∈ E(G)}. When S consists of one vertex v, we simply write Γ G (v) for Γ G ({v}). We also write Γ (S) = Γ G (S) if there is no confusion.
Bioinformatics 20(11), 1746 (2004) 12. : Network motifs: Simple building blocks of complex networks. Science 298, 824–827 (2002) 13. : Biological network comparison using graphlet degree distribution. Bioinformatics 23(2), e177–e183 (2007) 14. : Modeling interactome: Scale- free or geometric? Bioinformatics 150, 216–231 (2005) 15. : Efficient algorithms for detecting signaling pathways in protein interaction networks. , Waterman, M. ) RECOMB 2005. LNCS (LNBI), vol. 3500, pp. 1–13. Springer, Heidelberg (2005) 16.
Proteomics 5, 444 (2005) The Giant Component in a Random Subgraph of a Given Graph Fan Chung1,⋆ , Paul Horn1 , and Linyuan Lu2,⋆⋆ 1 University of California, San Diego 2 University of South Carolina Abstract. We consider a random subgraph Gp of a host graph G formed by retaining each edge of G with probability p. We address the question of determining the critical value p (as a function of G) for which a giant component emerges. Suppose G satisfies some (mild) conditions depending on its spectral gap and higher moments of its degree sequence.
Algorithms and Models for the Web-Graph: 6th International Workshop, WAW 2009, Barcelona, Spain, February 12-13, 2009. Proceedings by Kevin J. Lang (auth.), Konstantin Avrachenkov, Debora Donato, Nelly Litvak (eds.)
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