Considerations about using the Shapley Value for Influence Maximization in the case of the Weighted Cascade Model

Autor: Tamás Képes, Noémi Gaskó, Rodica Ioana Lung, Mihai Alexandru Suciu
Rok vydání: 2020
Předmět:
Zdroj: 2020 IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI).
DOI: 10.1109/sami48414.2020.9108771
Popis: This paper explores the influence maximization problem for the weighted cascade model by considering an approach based on Shapley value and Extremal Optimization. The Shapley value is a solution concept in cooperative game theory that, given a total value of the game assigns to each player a value as part of it, computed as its marginal contribution to all possible coalitions of players. In the weighted cascade model we consider adding and updating nodes in the initial set during the extremal optimization search based on their Shapley value in an approach already tested for the independent cascade model. Comparisons with other methods by means of numerical experiments show that results reported by this approach are promising, prompting for further research in this direction.
Databáze: OpenAIRE