## 5 Results
### Model Performance  
Tables 5-7 show two groups' test set performances of all methods under the metric of Recall@K and MRR@K: (1) For Reddit and Last.fm, we set K = 5, 10 and 20. (2) For 1/10 Reddit and 1/80 Last.fm, we set the same K as the full versions of Reddit and Last.fm. For Tmall, to keep consistent with the evaluation in [29], we use Recall@10, Recall@20 and MRR@20 to evaluate methods, and cited the same evaluation results of SWIWO and SWIWO-I in [29]. Relative scores are given compared to the strongest baselines. For all datasets, ASLM-LHS outperforms all baselines with moderate margins. Table 8 shows the validation set performances of three different methods under the metric of Recall@K and MRR@K in Reddit and Last.fm datasets. Please note that, for the Reddit dataset, the validation set performance of ASLM-LHS is better than that of ASLM-AP, and, for Reddit and Last.fm datasets, the validation set performances of ASLM-AP and ASLM-LHS are all better than the test set performances with moderate margins, respectively. Table 9 shows the validation set performances of three different methods in 1/10 Reddit and 1/80 Last.fm datasets. The validation set performances of the two ASLM models in the 1/10 Reddit dataset are all better than the test set performances, while, in the 1/80 Last.fm dataset, the majority of the validation set performances of the two ASLM models are better than the test set performances.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & **R@5** & **R@10** & **R@20** & **MRR@5** & **MRR@10** & **MRR@20** \\ \hline Most & 0.1451 & 0.2155 & 0.2882 & 0.0966 & 0.1060 & 0.1111 \\ Popular & 0.1484 & 0.2161 & 0.2928 & 0.0969 & 0.1058 & 0.1112 \\ II-RNN-LHS & 0.1614 & 0.2292 & 0.3062 & 0.1061 & 0.1151 & 0.1204 \\  & **0.1904** & **0.2507** & 0.3245 & **0.1256** & **0.1336** & **0.1387** \\  & **(+17.96\%)** & **(+9.38\%)** & (+5.98\%) & **(+18.37\%)** & **(+16.07\%)** & **(+15.17\%)** \\  & 0.1886 & 0.2488 & **0.3251** & 0.1234 & 0.1314 & 0.1366 \\  & (+16.83\%) & (+8.55\%) & **(+6.19\%)** & (+16.27\%) & (+14.13\%) & (+13.48\%) \\ \hline \end{tabular}
\begin{tabular}{c c c c c c} \hline  & **(a) 1/10 Reddit Dataset (Test)**. & & & & & \\ \hline  & **R@5** & **R@10** & **R@20** & **MRR@5** & **MRR@10** & **MRR@20** \\ \hline Most & 0.0371 & 0.0493 & 0.0596 & 0.0290 & 0.0308 & 0.0314 \\  & 0.0349 & 0.0448 & 0.0604 & 0.0282 & 0.0294 & 0.0305 \\ II-RNN-LHS & 0.0361 & 0.0459 & 0.0608 & 0.0285 & 0.0298 & 0.0308 \\  & **0.0388** & 0.0496 & 0.0656 & 0.0308 & 0.0323 & 0.0334 \\  & **(+4.38\%)** & (+0.57\%) & (+7.95\%) & (+6.18\%) & (+4.93\%) & (+6.13\%) \\  & **0.0388** & **0.0503** & **0.0674** & **0.0309** & **0.0324** & **0.0336** \\  & **(+4.38\%)** & **(+1.92\%)** & **(+10.97\%)** & **(+6.52\%)** & **(+5.37\%)** & **(+6.98\%)** \\ \hline \end{tabular}
\end{table}
Table 6: Group B: Recall and MRR scores for the ASLM models and the baselines for the test sets in 1/10 Reddit and 1/80 Last.fm datasets.  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **R@10** & **R@20** & **MRR@20** \\ \hline Most Popular & 0.0234 & 0.0420 & 0.0123 \\ SWIWO-I & 0.3177 & 0.3810 & 0.1903 \\ SWIWO & 0.3082 & 0.3703 & 0.1885 \\  & 0.5412 & 0.5661 & 0.4037 \\  & (+70.34\%) & (+48.57\%) & (+112.12\%) \\  & **0.5428** & **0.5679** & **0.4082** \\  & **(+70.86\%)** & **(+49.06\%)** & **(+114.50\%)** \\ \hline \end{tabular}
\end{table}
Table 7: Group B: Recall and MRR scores for the ASLM models and the baselines in the Tmall dataset.  
\begin{table}
\begin{tabular}{c c c c c c} \hline  & **(a) 1/10 Reddit Dataset (Test)**. & & & & & \\