A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models

27 July 2021

Papers citing "A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models"

7 / 7 papers shown

Title
Are We Really Measuring Progress? Transferring Insights from Evaluating Recommender Systems to Temporal Link Prediction Filip Cornell Oleg Smirnov Gabriela Zarzar Gandler Lele Cao 13 0 0 14 Jun 2025
ConsRec: Denoising Sequential Recommendation through User-Consistent Preference Modeling Haidong Xin Qiushi Xiong Zhenghao Liu Sen Mei Yukun Yan Shi Yu Shuo Wang Yu Gu Ge Yu Chenyan Xiong HAI 46 0 0 28 May 2025
Debias Can be Unreliable: Mitigating Bias Issue in Evaluating Debiasing Recommendation Chengbing Wang Wentao Shi Jizhi Zhang Wenjie Wang Hang Pan Fuli Feng 181 1 0 07 Sep 2024
Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction Elisabeth Fischer Albin Zehe Andreas Hotho Daniel Schlor HAI 157 0 0 28 Aug 2024
A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation Aleksandr V. Petrov Craig Macdonald 81 47 0 15 Jul 2022
Effective and Efficient Training for Sequential Recommendation using Recency Sampling Aleksandr V. Petrov Craig Macdonald 73 28 0 06 Jul 2022
Decoupled Side Information Fusion for Sequential Recommendation Yueqi Xie Peilin Zhou Sunghun Kim 97 113 0 23 Apr 2022