effects of embedding dimension *d* on Foursquare and Gowalla are shown in Table \[tab:dimf\] and Table \[tab:dimw\], respectively.

           1       5      10      15      20
  ----- ------- ------- ------- ------- -------
   70    0.281   0.376   0.409   0.433   0.451
   80    0.294   0.384   0.417   0.445   0.462
   90    0.300   0.390   0.425   0.459   0.476
   100   0.307   0.393   0.434   0.461   0.483
   110   0.311   0.407   0.439   0.463   0.486
   120   0.312   0.407   0.439   0.464   0.486

  : Effects of Dimensionality on Foursquare

\[tab:dimf\]

           1       5      10      15      20
  ----- ------- ------- ------- ------- -------
   70    0.355   0.432   0.474   0.503   0.527
   80    0.358   0.436   0.478   0.508   0.530
   90    0.359   0.439   0.482   0.509   0.535
   100   0.361   0.445   0.486   0.511   0.539
   110   0.361   0.445   0.488   0.513   0.540
   120   0.361   0.445   0.488   0.513   0.540

  : Effects of Dimensionality on Gowalla

\[tab:dimw\]

We can see that the experimental results are not very sensitive to the dimension *d*. With an increasing number of dimension, the accuracy on Gowalla is almost unchanged, i.e., the improvement is less than 1% in nearly all cases. The accuracy on Foursquare is slightly enhanced with a large dimension *d*, and finally it becomes stable.

To investigate the effects of time interval, we divide timestamps by three methods, i.e., splitting time into 24, 