A Parallel Community Structure Mining Method in Big Social Networks

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/934301/figures/934301.fig.0010a.svgz" name="934301.fig.0010a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Speedup ratio test on D4</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/934301/figures/934301.fig.0010b.svgz" name="934301.fig.0010b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Effective edge lost ratio test on D4</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/934301/figures/934301.fig.0010c.svgz" name="934301.fig.0010c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Running time test on D5</td></tr></table>

<div>Scalability tests on data sets D4 and D5.</div>

Mathematical Problems in Engineering

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Figure 10

Figure 10: A Parallel Community Structure Mining Method in Big Social Networks 