Individual Persistence Adaptation for User-Centric Evaluation of User Satisfaction in Recommender Systems

The primary objective of a recommender system (RS) is to enhance user satisfaction, which serves as the gold standard for evaluation. In order to support the advancement of RS, it is crucial to study how to accurately measure user satisfaction. This paper proposes a novel evaluation framework that l...

詳細記述

書誌詳細
出版年:IEEE Access
主要な著者: Nozomu Onodera, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama
フォーマット: 論文
言語:英語
出版事項: IEEE 2024-01-01
主題:
オンライン・アクセス:https://ieeexplore.ieee.org/document/10418128/