By Anthony Bonato, Fan Chung Graham, Pawel Pralat
This publication constitutes the court cases of the thirteenth foreign Workshop on Algorithms and types for the internet Graph, WAW 2016, held in Montreal, quality control, Canada, in December 2016.
The thirteen complete papers awarded during this quantity have been rigorously reviewed and chosen from 14 submissions. The workshop accrued the researchers who're engaged on graph-theoretic and algorithmic facets of comparable complicated networks, together with social networks, quotation networks, organic networks, molecular networks, and different networks bobbing up from the Internet.
Read or Download Algorithms and Models for the Web Graph: 13th International Workshop, WAW 2016, Montreal, QC, Canada, December 14–15, 2016, Proceedings PDF
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Extra info for Algorithms and Models for the Web Graph: 13th International Workshop, WAW 2016, Montreal, QC, Canada, December 14–15, 2016, Proceedings
89(20), 208701 (2002) 19. : Power laws, Pareto distributions and Zipf’s law. Contemp. Phys. 46(N5), 323–351 (2005) 20. : The structure and function of complex networks. SIAM Rev. 45(2), 167–256 (2003) Assortativity in Generalized Preferential Attachment Models 21 21. : Generalized preferential attachment: tunable power-law degree distribution and clustering coeﬃcient. , Pralat, P. ) WAW 2013. LNCS, vol. 8305, pp. 185–202. Springer, Heidelberg (2013). 1007/978-3-319-03536-9 15 22. : Collective dynamics of ‘small-world’ networks.
The remaining cases are treated in much the same way. k ) = E p1k p2k q3k q4k = E p˜1k p˜2k q˜3k q˜4k + R, (19) where E p˜1k p˜2k q˜3k q˜4k = α4 m−4 A1 and |R| ≤ E p˜1k p˜2k q˜3k q˜4k I∗k = o(m−4 ). s. as m → ∞. k ) = α4 m−3 A1 (1+o(1)). Secondly we show that I2 (r) = o(m−3 ), for 1 ≤ r ≤ 4. l ) ≤ E p˜1k p˜2k q˜3k q˜4k p˜1l p˜2l q˜3l q˜4l = O(m−8 ). lk ). J5 = (k,l)∈Cr In the ﬁrst (second) sum distinct pairs x = (k, l) and y = (k , l ) share the ﬁrst (second) coordinate. In the third sum all coordinates of the pairs (k, l), (k , l ) are diﬀerent.
2. Node 1 follows node 2, because 1 demands attribute w1 supplied by 2. We consider a random bipartite digraph H where the pairs (i, wk ), i ∈ V , wk ∈ W establish adjacency relations independently of each other. That is, the bivariate binary random vectors (Ii→k , Ik→i ), 1 ≤ i ≤ n, 1 ≤ k ≤ m, are stochastically independent. Here Ii→k and Ik→i stand for the indicators of the events that links i → wk and wk → i are present in H. We assume that every pair (i, wk ) is assigned a triple of probabilities pik = P (i → wk ), qik = P (wk → i), rik = P (i → wk , wk → i).
Algorithms and Models for the Web Graph: 13th International Workshop, WAW 2016, Montreal, QC, Canada, December 14–15, 2016, Proceedings by Anthony Bonato, Fan Chung Graham, Pawel Pralat