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The methodology is applied and demonstrated on two benchmark networks.
The various algorithms were tested using 12 benchmark networks available in the literature.
Open image in new window Fig. 1 Real community structure of the four selected benchmark networks.
The real-world benchmark networks and their properties are given in Table 1.
Results are supported by an extensive comparison with previous works on the benchmark networks here tested.
Community detection from benchmark networks by the proposed method is perfect or highly accurate.
Experimental results utilizing computer-generated artificial networks and real-world social benchmark networks give satisfactory correspondence.
5, experimentation on both small benchmark networks and applying the proposed task-oriented evaluation approach are described.
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As Zalesky et al. described in their studies, appropriate null networks should be used to benchmark network measures in correlation networks [86].
In each test, we compare the performance of benchmark network, Sal-Mask Networks using two different saliencies, with that of the Ada-Sal Network.
The conducted study considers well-known benchmark network topologies, real IoT monitoring services, and standardized settings for urban and rural environments.
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