Exploiting Spatial and Temporal for Point of Interest Recommendation

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/complexity/volume-2018/6928605/figures/6928605.fig.006a.svgz" name="6928605.fig.006a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Gowalla (precision)</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/complexity/volume-2018/6928605/figures/6928605.fig.006b.svgz" name="6928605.fig.006b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Gowalla (recall)</td></tr></table>

<div>Effect of percentages of training data on the Gowalla dataset.</div>

Complexity

fig6

Figure 6

Figure 6: Exploiting Spatial and Temporal for Point of Interest Recommendation 