안지원/배홍균’s paper has been accepted in

Title: Is the Impression Log Beneficial to Effective Model Training in News Recommender Systems? No, It’s NOT
Author: Jeewon Ahn, Hong-Kyun Bae, and Sang-Wook Kim
Abstract
The MIND dataset, one of the most-popular real-world news datasets, has been used in many news recommendation researches. They all employ the impression log as training data to train their models (i.e., impression-based training). In this paper, we claim that the impression log has the preference bias issue and thus should not be used for model training in news recommendation. We validate our claim via extensive experiments; we also demonstrate the dramatic improvement of recommendation accuracy in five existing state-of-the-art models up to 82.1% by simply ignoring the impression log. We believe this surprising result provides a new insight towards better model training for both researchers and practitioners working in a news recommendation area.