4 papers
NewsReX: A More Efficient Approach to News Recommendation with Keras 3 and JAX
Igor L. R. Azevedo, Toyotaro Suzumura, Yuichiro Yasui
Reproducing and comparing results in news recommendation research has become increasingly difficult. This is due to a fragmented ecosystem of diverse codebases, varied configuratio…
A Look Into News Avoidance Through AWRS: An Avoidance-Aware Recommender System
Igor L. R. Azevedo, Toyotaro Suzumura, Yuichiro Yasui
In recent years, journalists have expressed concerns about the increasing trend of news article avoidance, especially within specific domains. This issue has been exacerbated by th…
From Votes to Volatility Predicting the Stock Market on Election Day
Igor L. R. Azevedo, Toyotaro Suzumura
Stock market forecasting has been a topic of extensive research, aiming to provide investors with optimal stock recommendations for higher returns. In recent years, this field has…
Popular News Always Compete for the User's Attention! POPK: Mitigating Popularity Bias via a Temporal-Counterfactual
Igor L. R. Azevedo, Toyotaro Suzumura, Yuichiro Yasui
In news recommendation systems, reducing popularity bias is essential for delivering accurate and diverse recommendations. This paper presents POPK, a new method that uses temporal…