Download Computational Social Networks: 4th International Conference, by My T. Thai, Nam P. Nguyen, Huawei Shen PDF

By My T. Thai, Nam P. Nguyen, Huawei Shen

This e-book constitutes the refereed court cases of the 4th overseas convention on Computational Social Networks, CSoNet 2015, held in Beijing, China, in August 2015.

The 23 revised complete papers and three brief papers offered including 2 prolonged abstracts have been conscientiously reviewed and chosen from a hundred and one submissions and canopy subject matters on social details diffusion; community clustering and neighborhood constitution; social hyperlink prediction and suggestion; and social community constitution analysis.

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Extra info for Computational Social Networks: 4th International Conference, CSoNet 2015, Beijing, China, August 4-6, 2015, Proceedings

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As soon as a price is announced, a consumer in Q buys the product if and only if her current total value is greater than or equal to the current price. – Simultaneous moves. We assume that, for each newly announced price, all consumers in Q make their decisions (buying or not buying) simultaneously. Note that a consumer in Q who does not purchase at current time t under price pt may be willing to buy at a later time t > t under a lower price pt < pt . For each t = 1, 2, . . , at time t, or in the t-th round).

A e 0-th moment b c f g 1-th moment 2-th moment d 3-th (T-th) moment Fig. 1. (Figure (a) illustrates the time temporal graph G which consists of a series of graphs G1 , G2 , G3 , G4 representing the social relation at each moment. Figure (b) shows ˆ which is induced graph G. In this graph, node a, b, c, d, e, f, g are the integrated graph G fake nodes and does not exist. This means that e cannot be infected at the beginning. Social Relation Based Long-Term Vaccine Distribution Planning 31 Fig. 2.

Therefore, we have |f | = |IT |. 3 Polynomial Time Exact Algorithm Based on Enumeration In this section, we discuss how the best possible solution of SVDP2 can be computed within polynomial time. Our strategy consists of the following steps. (a) Our key observation on this step is that as we stated in Theorem 1, once (i) (j) a node vk receives a vaccine, then all nodes vk with j ≥ i and their ˆ . Based on this observation, we corresponding edges are removed from G (i) (i) (i+1) (T ) (i) first construct a subset Xk = {vk , vk , · · · , vk } for each node vk in ˆ )\ {s, t} V (G0 ) .

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