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 …
Field-aware variational autoencoders for billion-scale user representation learning
User representation learning plays an essential role in Internet applications, such as
recommender systems. Though developing a universal embedding for users is demanding …
recommender systems. Though developing a universal embedding for users is demanding …
ABNS: Association-based negative sampling for collaborative filtering
R Chen, J Fan, M Wu - Expert Systems with Applications, 2024 - Elsevier
The purpose of the recommendation systems (RS) is to provide personalized information
filtering for users by analyzing their interactions with items. However, the sparsity of data in …
filtering for users by analyzing their interactions with items. However, the sparsity of data in …
MV-HAN: A hybrid attentive networks based multi-view learning model for large-scale contents recommendation
Industrial recommender systems usually employ multi-source data to improve the
recommendation quality, while effectively sharing information between different data …
recommendation quality, while effectively sharing information between different data …
Attribute community detection based on attribute edges weights fusion and graph embedding factorization
In recent years, factorization combined with attribute information has played an important
role in attribute community detection. However, previous studies focused more on …
role in attribute community detection. However, previous studies focused more on …