3 papers
cs.IR2022
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering
Alireza Gharahighehi, Felipe Kenji Nakano, Celine Vens
Recommender systems are information retrieval methods that predict user preferences to personalize services. These systems use the feedback and the ratings provided by users to mod…
cs.LG2020
Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery
Bin Liu, Konstantinos Pliakos, Celine Vens +1
Predicting drug-target interactions (DTI) via reliable computational methods is an effective and efficient way to mitigate the enormous costs and time of the drug discovery process…
cs.IR2020
Fair Multi-Stakeholder News Recommender System with Hypergraph ranking
Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos
Recommender systems are typically designed to fulfill end user needs. However, in some domains the users are not the only stakeholders in the system. For instance, in a news aggreg…