Abnormal User Detection via Multiview Graph Clustering in the Mobile e-Commerce Network

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/wcmc/volume-2022/3766810/figures/3766810.fig.003a.svgz" name="3766810.fig.003a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>A heterogeneous graph for e-commerce network</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/wcmc/volume-2022/3766810/figures/3766810.fig.003b.svgz" name="3766810.fig.003b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>UDU metapath</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/wcmc/volume-2022/3766810/figures/3766810.fig.003c.svgz" name="3766810.fig.003c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>UMU metapath</td></tr></table>

<div>A mobile e-commerce network organized by a heterogeneous graph.</div>

Wireless Communications and Mobile Computing

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Figure 3

Figure 3: Abnormal User Detection via Multiview Graph Clustering in the Mobile e-Commerce Network 