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

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12571/3303
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