适宜 发表于 2025-3-23 13:25:33

http://reply.papertrans.cn/15/1487/148647/148647_11.png

思想灵活 发表于 2025-3-23 15:28:51

http://reply.papertrans.cn/15/1487/148647/148647_12.png

STAT 发表于 2025-3-23 21:48:36

Matthew Brown MD,Kevin C. Chung MD, MScommendation is highly context-dependent: (1) geographical influence, e.g., users prefer to visit POIs that are not far away; (2) time-sensitivity, e.g., restaurants are preferred in dinner time; (3) dependency in a user’s check-in sequence, e.g., POIs planned in a trip. Yet, existing methods either

consent 发表于 2025-3-24 00:25:49

Matthew Brown MD,Kevin C. Chung MD, MSave been proposed to achieve low-order and high-order feature interactions. However, most of them ignore the importance of cross features and fail to suppress the negative impact of useless features. In this paper, a novel multi-scale feature-crossing attention network (MsFcNET) is proposed to extra

产生 发表于 2025-3-24 06:05:25

http://reply.papertrans.cn/15/1487/148647/148647_15.png

aspect 发表于 2025-3-24 07:45:16

William W. Huang,Christine S. Ahnhich has become increasingly popular in academic research and practical applications. Short-term transition dependencies contain the information of partial item orders, while long-term transition dependencies infer long-range user preference, the two dependencies are mutually restrictive and complem

易于 发表于 2025-3-24 13:49:19

http://reply.papertrans.cn/15/1487/148647/148647_17.png

vibrant 发表于 2025-3-24 15:04:13

http://reply.papertrans.cn/15/1487/148647/148647_18.png

crease 发表于 2025-3-24 19:25:51

Clinical Manual of Fever in Childrenining dataset, but are out of work when the classes are not in the training dataset. Zero-shot learning aims at solving this problem. In this paper, we propose a novel model termed .ulti-.ayer .ross .oss .odel (MLCLM). Our model has two novel ideas: (1) In the model, we design a multi-nonlinear laye

Abrupt 发表于 2025-3-25 02:04:04

http://reply.papertrans.cn/15/1487/148647/148647_20.png
页: 1 [2] 3 4 5 6
查看完整版本: Titlebook: Advances in Knowledge Discovery and Data Mining; 24th Pacific-Asia Co Hady W. Lauw,Raymond Chi-Wing Wong,Sinno Jialin Pa Conference proceed