SCIENTIA SINICA Informationis, Volume 50 , Issue 12 : 1867(2020) https://doi.org/10.1360/SSI-2019-0177

## Recurrent memory networks: modeling long short-term user preferences for session-based recommendation

• AcceptedJan 7, 2020
• PublishedNov 20, 2020
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### References

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• Figure 1

(Color online) The overall framework of RMN for two consecutive sessions

• Figure 2

(Color online) Illustration of (a) intra-session memory reader and (b) inter-session memory writer in RMN

• Figure 3

(Color online) Results of (a) Precision@$K$, (b) Recall@$K$, and (c) F1@$K$ on XING dataset. Some of the baselines are not shown in this figure for the sake of clarity

• Figure 4

(Color online) The impact of the length of users' historical sessions used in prediction. (a) Recall@K; protectłinebreak (b) MRR@K

• Figure 5

(Color online) Parameters sensitivity of RMN. (a) The number of slots of preference memory; (b) the dimension of preference memory

• Table 1   Results of MRR@$K$ on MovieLens-20M and XING dataset
 MovieLens-20M XING MRR@2 MRR@5 MRR@10 MRR@20 MRR@50 MRR@2 MRR@5 MRR@10 MRR@20 MRR@50 RMN 0.2737 0.2892 0.2940 0.2981 0.3055 0.0922 0.1085 0.1158 0.1188 0.1211 M-Pop 0.0045 0.0073 0.0096 0.0130 0.0142 0.0003 0.0006 0.0010 0.0011 0.0014 S-Pop 0.1077 0.1251 0.1430 0.1612 0.1727 0.0693 0.0923 0.0953 0.0954 0.0960 Item-KNN 0.1855 0.2076 0.2196 0.2231 0.2249 0.0244 0.0380 0.0427 0.0453 0.0469 Session-KNN 0.2014 0.2175 0.2216 0.2360 0.2442 0.0457 0.0525 0.0688 0.0742 0.0863 RUM 0.0754 0.0846 0.1021 0.1068 0.1124 0.0205 0.0368 0.0425 0.0436 0.0477 NARM 0.2512 0.2687 0.2745 0.2895 0.2911 0.0657 0.0884 0.0951 0.0977 0.0995 RNN 0.2241 0.2389 0.2412 0.2426 0.2467 0.0512 0.0770 0.0867 0.0891 0.0904 II-RNN 0.2354 0.2546 0.2753 0.2778 0.2810 0.0815 0.0867 0.0916 0.0974 0.1058 HRNN 0.2310 0.2487 0.2502 0.2593 0.2644 0.0603 0.0883 0.0960 0.0992 0.1009 GNN 0.2134 0.2271 0.2429 0.2533 0.2631 0.0512 0.0721 0.0767 0.0836 0.0882
• Table 2   The comparison of RMN with its short-term-only (removing session initializer and inter-session memory writer) and long-term-only (removing intra-session memory reader) variants on XING dataset evaluated by F1@$K$
 F1@2 F1@5 F1@10 F1@20 F1@50 RMN 0.0743 0.0571 0.0415 0.0261 0.0136 RMN-short 0.0345 ($-53.6%$) 0.0408 ($-28.5%$) 0.0291 ($-29.9%$) 0.0190 ($-27.2%$) 0.0088 ($-35.3%$) RMN-long 0.0411 ($-44.7%$) 0.0455 ($-20.3%$) 0.0331 ($-20.2%$) 0.0220 ($-15.7%$) 0.0114 ($-16.2%$)

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