A hybrid bandit framework for diversified recommendation

• Main Authors: Ding, Qinxu, Liu, Yong, Miao, Chunyan, Cheng, Fei, Tang, Haihong
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Computer science and engineering; Engineering::Computer science and engineering::Information systems::Information storage and retrieval; Linear Modular Dispersion Bandit; Interactive Recommender Systems
• Online Access: https://ojs.aaai.org/index.php/AAAI/issue/archive; https://hdl.handle.net/10356/152719
• Institution: Nanyang Technological University

The interactive recommender systems involve users in the recommendation procedure by receiving timely user feedback to update the recommendation policy. Therefore, they are widely used in real application scenarios. Previous interactive recommendation methods primarily focus on learning users...