By Andrei Broder (auth.), Ravi Kumar, Dandapani Sivakumar (eds.)

ISBN-10: 3642180086

ISBN-13: 9783642180088

ISBN-10: 3642180094

ISBN-13: 9783642180095

This publication constitutes the refereed complaints of the seventh foreign Workshop on Algorithms and types for the Web-Graph, WAW 2010, held in Stanford, CA, united states, in December 2010, which used to be co-located with the sixth overseas Workshop on net and community Economics (WINE 2010).

The thirteen revised complete papers and the invited paper provided have been conscientiously reviewed and chosen from 19 submissions.

**Read Online or Download Algorithms and Models for the Web-Graph: 7th International Workshop, WAW 2010, Stanford, CA, USA, December 13-14, 2010. Proceedings PDF**

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**Extra info for Algorithms and Models for the Web-Graph: 7th International Workshop, WAW 2010, Stanford, CA, USA, December 13-14, 2010. Proceedings**

**Example text**

2 Expectation and Variance of φt The history Ht embodies the evolution of how the attributes are discovered over time. It is insightful to recast that history in terms of the discovery times Γw of each attribute in W . Given any sequence of nodes v0 , v1 , v2 , . , the probability that a given attribute w is first discovered at time t < n is P[Γw = t] = P[Ivt ,w = 1, Ivt−1 ,w = 0, . . , Iv0 ,w = 0] = pw (1 − pw )t . If an attribute w is not discovered by time n − 1, we set Γw = ∞ and note that P[Γw = ∞] = (1 − pw )n .

Component evolution in a secure wireless sensor network. Netw. 53(1), 19–26 (2009) 7. : The average distances in random graphs with given expected degrees. Proceedings of the National Academy of Sciences of the United States of America 99(25), 15879–15882 (2002) 8. : Random intersection graphs with tunable degree distribution and clustering. Probab. Eng. Inf. Sci. 23(4), 661–674 (2009) 9. : The representation of a graph by set intersections. Canad. J. Math. 18, 106–112 (1966) 10. : Random intersection graphs and classification.

WAW 2010, LNCS 6516, pp. 36–49, 2010. c Springer-Verlag Berlin Heidelberg 2010 Component Evolution in General Random Intersection Graphs 37 visit during a typical day [11]. Bipartite structure is hardly limited to social networks. The relation between nodes and keys in secure wireless communication, for examples, forms a bipartite network [6]. Factor graphs have become a standard representation for constraint satisfaction problems such as k-SAT and graph coloring. In general, bipartite graphs are well suited to problems of classifying objects, where each object has a set of properties [10].

### Algorithms and Models for the Web-Graph: 7th International Workshop, WAW 2010, Stanford, CA, USA, December 13-14, 2010. Proceedings by Andrei Broder (auth.), Ravi Kumar, Dandapani Sivakumar (eds.)

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