In this work we address the problem of critical source selection in social sensing. We propose an approach to the ranking of information streams, which is aware of the interdependence among streams (redundancy and synergies), of the cost of individual streams, and of the cost related to the integration of multiple streams. The method is based on the use of the Coalitional Game Theory concept of Power Index, and relies on the polynomial-time estimate of the stream sets characteristics. With respect to other works using a power index, the method takes into account that the problem has a non-trivial cost structure.
Gianini, G., Mio, C., Viola, F., Lin, J., Almoosa, N., Selection of Information Streams in Social Sensing: An Interdependence-and Cost-aware Ranking Method, in Proceedings of the 12th International Conference on Management of Digital EcoSystems, MEDES 2020, (Online Conference, 02-04 November 2020), Association for Computing Machinery, Inc, New York 2020: 157-161. [10.1145/3415958.3433099] [http://hdl.handle.net/10807/177878]
Selection of Information Streams in Social Sensing: An Interdependence-and Cost-aware Ranking Method
Lin, Jianyi;
2020
Abstract
In this work we address the problem of critical source selection in social sensing. We propose an approach to the ranking of information streams, which is aware of the interdependence among streams (redundancy and synergies), of the cost of individual streams, and of the cost related to the integration of multiple streams. The method is based on the use of the Coalitional Game Theory concept of Power Index, and relies on the polynomial-time estimate of the stream sets characteristics. With respect to other works using a power index, the method takes into account that the problem has a non-trivial cost structure.
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