We present our ongoing work on the problem of increasing the information spread in a network by creating a limited amount of new edges incident to a given initial set of active nodes. As a preliminary result, we give a constant approximation algorithm for the case in which the set of initial active nodes is a singleton. Our aim is to extend this result to the general case. We outline some further research directions which we are investigating.
Influence maximization in the independent cascade model
D'Angelo G;
2016-01-01
Abstract
We present our ongoing work on the problem of increasing the information spread in a network by creating a limited amount of new edges incident to a given initial set of active nodes. As a preliminary result, we give a constant approximation algorithm for the case in which the set of initial active nodes is a singleton. Our aim is to extend this result to the general case. We outline some further research directions which we are investigating.File in questo prodotto:
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