Zero-shot micro-video classification with neural variational inference in graph prototype network
Micro-video classification plays a central role in online content recommendation platforms,
such as Kwai and Tik-Tok. Existing works on video classification largely exploit the …
such as Kwai and Tik-Tok. Existing works on video classification largely exploit the …
Unveiling user interests: A deep user interest exploration network for sequential location recommendation
Sequential location recommendation, also known as next location prediction, is a crucial
task aiming to compute the likelihood of a user visiting a certain point of interest (POI). It has …
task aiming to compute the likelihood of a user visiting a certain point of interest (POI). It has …
Improving rating prediction in multi-criteria recommender systems via a collective factor model
Existing recommendation methods usually train several independent modules for each
rating information instead of an end-to-end manner. Therefore, these methods may be …
rating information instead of an end-to-end manner. Therefore, these methods may be …
CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking System
The multiplayer online battle arena (MOBA) genre has gained significant popularity and
economic success, attracting considerable research interest within the Human-Computer …
economic success, attracting considerable research interest within the Human-Computer …
DIFN: A Dual Intention-aware Network for Repurchase Recommendation with Hierarchical Spatio-temporal Fusion
Recommendation systems play a crucial role in both industrial applications and research
fields, which target to understand user preferences and intentions to provide personalized …
fields, which target to understand user preferences and intentions to provide personalized …
AttFGCN: A GCN-Based Method Using Attention Flow for Knowledge Graph Completion
M Yu, F Gao, M Zhao, T Xu, J Guo, W Zhang… - … on Database Systems …, 2024 - Springer
Graph convolutional networks (GCNs) are a series of competitive methods for knowledge
graph completion (KGC). GCNs can effectively capture the implicit information by …
graph completion (KGC). GCNs can effectively capture the implicit information by …
MGSD: Multi-Graph Joint Framework Based on Semantic Dependency for Chinese NER
Z Feng, Y Zhang, S Mao, Y Jiang - International Conference on Database …, 2024 - Springer
In the realm of Natural Language Processing (NLP), Named Entity Recognition (NER) holds
a pivotal position as a foundational component. Recently, the majority of existing …
a pivotal position as a foundational component. Recently, the majority of existing …