Analysis of Different Random Graph Models in the Identification of Network
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This work investigates random graph models used in the fields Graph Theory and Network Analysis. To be more precise, it is tested with statistical measures whether different random graph models could be used interchangeable in analysis. The results show that some models are prone to errors that get accepted most of the time since the models generate graphs quite fast.
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