DaisyRec 2.0: benchmarking recommendation for rigorous evaluation

• Main Authors: Sun, Zhu, Fang, Hui, Yang, Jie, Qu, Xinghua, Liu, Hongyang, Yu, Di, Ong, Yew-Soon, Zhang, Jie
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Recommender Systems; Reproducible Evaluation
• Online Access: https://hdl.handle.net/10356/172177
• Institution: Nanyang Technological University

Recently, one critical issue looms large in the field of recommender systems - there are no effective benchmarks for rigorous evaluation - which consequently leads to unreproducible evaluation and unfair comparison. We, therefore, conduct studies from the perspectives of practical theory and experim...