Knowledge graph contrastive learning for recommendation
Knowledge Graphs (KGs) have been utilized as useful side information to improve
recommendation quality. In those recommender systems, knowledge graph information …
recommendation quality. In those recommender systems, knowledge graph information …
Jointly non-sampling learning for knowledge graph enhanced recommendation
Knowledge graph (KG) contains well-structured external information and has shown to be
effective for high-quality recommendation. However, existing KG enhanced recommendation …
effective for high-quality recommendation. However, existing KG enhanced recommendation …
Multi-level cross-view contrastive learning for knowledge-aware recommender system
Knowledge graph (KG) plays an increasingly important role in recommender systems.
Recently, graph neural networks (GNNs) based model has gradually become the theme of …
Recently, graph neural networks (GNNs) based model has gradually become the theme of …
Knowledge-adaptive contrastive learning for recommendation
By jointly modeling user-item interactions and knowledge graph (KG) information, KG-based
recommender systems have shown their superiority in alleviating data sparsity and cold start …
recommender systems have shown their superiority in alleviating data sparsity and cold start …
Unifying knowledge graph learning and recommendation: Towards a better understanding of user preferences
Incorporating knowledge graph (KG) into recommender system is promising in improving the
recommendation accuracy and explainability. However, existing methods largely assume …
recommendation accuracy and explainability. However, existing methods largely assume …
Contextualized graph attention network for recommendation with item knowledge graph
Graph neural networks (GNN) have recently been applied to exploit knowledge graph (KG)
for recommendation. Existing GNN-based methods explicitly model the dependency …
for recommendation. Existing GNN-based methods explicitly model the dependency …
Knowledge-aware graph neural networks with label smoothness regularization for recommender systems
Knowledge graphs capture structured information and relations between a set of entities or
items. As such knowledge graphs represent an attractive source of information that could …
items. As such knowledge graphs represent an attractive source of information that could …
Hierarchical attentive knowledge graph embedding for personalized recommendation
Abstract Knowledge graphs (KGs) have proven to be effective for high-quality
recommendation, where the connectivities between users and items provide rich and …
recommendation, where the connectivities between users and items provide rich and …
entity2rec: Property-specific knowledge graph embeddings for item recommendation
Abstract Knowledge graphs have shown to be highly beneficial to recommender systems,
providing an ideal data structure to generate hybrid recommendations using both content …
providing an ideal data structure to generate hybrid recommendations using both content …
Recurrent knowledge graph embedding for effective recommendation
Knowledge graphs (KGs) have proven to be effective to improve recommendation. Existing
methods mainly rely on hand-engineered features from KGs (eg, meta paths), which …
methods mainly rely on hand-engineered features from KGs (eg, meta paths), which …