Multimodal pretraining, adaptation, and generation for recommendation: A survey
Personalized recommendation serves as a ubiquitous channel for users to discover
information tailored to their interests. However, traditional recommendation models primarily …
information tailored to their interests. However, traditional recommendation models primarily …
[HTML][HTML] A graph neural approach for group recommendation system based on pairwise preferences
Pairwise preference information, which involves users expressing their preferences by
comparing items, plays a crucial role in decision-making and has recently found application …
comparing items, plays a crucial role in decision-making and has recently found application …
Multi-hop neighbor fusion enhanced hierarchical transformer for multi-modal knowledge graph completion
Multi-modal knowledge graph (MKG) refers to a structured semantic network that accurately
represents the real-world information by incorporating multiple modalities. Existing …
represents the real-world information by incorporating multiple modalities. Existing …
Distilling Knowledge Based on Curriculum Learning for Temporal Knowledge Graph Embeddings
B Zhang, J Li, Y Dai - Proceedings of the 33rd ACM International …, 2024 - dl.acm.org
Lower-dimensional temporal knowledge graph embedding (TKGE) models are crucial for
practical applications and resource-limited scenarios, although existing models employ …
practical applications and resource-limited scenarios, although existing models employ …
Heterogeneous Hypergraph Structure Learning for Multimedia Recommendation
Multimedia recommender systems (MRS) become prevalent due to their rich multimodal
data (eg, visual and textual content). Recent advancements have leveraged Graph Neural …
data (eg, visual and textual content). Recent advancements have leveraged Graph Neural …