Concept--An Evaluation Protocol on Conversation Recommender Systems with System-and User-centric Factors
The conversational recommendation system (CRS) has been criticized regarding its user
experience in real-world scenarios, despite recent significant progress achieved in …
experience in real-world scenarios, despite recent significant progress achieved in …
Individual diversity preference aware neural collaborative filtering
The diversified recommendation of recommender systems enriches user experiences by
diversifying recommendation lists. However, the conventional post-processing strategy …
diversifying recommendation lists. However, the conventional post-processing strategy …
MHANER: A multi-source heterogeneous graph attention network for explainable recommendation in online games
Recommender system helps address information overload problem and satisfy consumers'
personalized requirement in many applications such as e-commerce, social networks and in …
personalized requirement in many applications such as e-commerce, social networks and in …
DSDRec: Next POI recommendation using deep semantic extraction and diffusion model
Abstract Semantics play a crucial role in many AI tasks, yet the lack of high-quality textual
data in LBSNs hampers deep semantic feature learning. Sparse user check-in records …
data in LBSNs hampers deep semantic feature learning. Sparse user check-in records …
Recommender systems, autonomy and user engagement
Recommender systems form the backbone of modern e-commerce, suggesting items to
users based on the collection of algorithmic data of a user's preferences. Companies that …
users based on the collection of algorithmic data of a user's preferences. Companies that …