Kazuhide Nakata

Temporal Positive Collective Matrix Factorization for Interpretable Trend Analysis in Recommender Systems

2023

Matrix Factorization (MF) is a common method in Recommender Systems (RS). However, distinguishing between continuously and temporarily popular items is challenging, as the basic MF relies on the accumulated user rating records for an item. …

Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback

2020

Recommender systems widely use implicit feedback such as click data because of its general availability. Although the presence of clicks signals the users' preference to some extent, the lack of such clicks does not necessarily …