6 citations · 9 across the 2 of their papers we have counts for
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cs.IR2021★ 3 cited
Correcting the User Feedback-Loop Bias for Recommendation Systems
Weishen Pan, Sen Cui, Hongyi Wen +3
Selection bias is prevalent in the data for training and evaluating recommendation systems with explicit feedback. For example, users tend to rate items they like. However, when ra…
cs.IR2016★ 6 cited
Hybrid Recommender System Based on Personal Behavior Mining
Zhiyuan Fang, Lingqi Zhang, Kun Chen
Recommender systems are mostly well known for their applications in e-commerce sites and are mostly static models. Classical personalized recommender algorithm includes item-based…