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Sparsification of influence networks
2011
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11
We present Spine, an efficient algorithm for finding the "backbone" of an influence network. Given a social graph and a log of past propagations, we build an instance of the independent-cascade model that describes the propagations. We aim at reducing the complexity of that model, while preserving most of its accuracy in describing the data. We show that the problem is inapproximable and we present an optimal, dynamic-programming algorithm, whose search space, albeit exponential, is typically
doi:10.1145/2020408.2020492
dblp:conf/kdd/MathioudakisBCGU11
fatcat:v35756h7xndrrgsosrkp63qgha