most citedIntersectional Two-sided Fairness in Recommendation

18 citations · 43 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR202413 cited

Collaborative-Enhanced Prediction of Spending on Newly Downloaded Mobile Games under Consumption Uncertainty

Peijie Sun, Yifan Wang, Min Zhang +5

With the surge in mobile gaming, accurately predicting user spending on newly downloaded games has become paramount for maximizing revenue. However, the inherently unpredictable na…

cs.IR2024

EEG-SVRec: An EEG Dataset with User Multidimensional Affective Engagement Labels in Short Video Recommendation

Shaorun Zhang, Zhiyu He, Ziyi Ye +4

In recent years, short video platforms have gained widespread popularity, making the quality of video recommendations crucial for retaining users. Existing recommendation systems p…

cs.IR20241 cited

Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation

Hanyu Li, Weizhi Ma, Peijie Sun +6

Cross-domain recommender (CDR) systems aim to enhance the performance of the target domain by utilizing data from other related domains. However, irrelevant information from the so…

cs.IR202418 cited

Intersectional Two-sided Fairness in Recommendation

Yifan Wang, Peijie Sun, Weizhi Ma +4

Fairness of recommender systems (RS) has attracted increasing attention recently. Based on the involved stakeholders, the fairness of RS can be divided into user fairness, item fai…

cs.IR202311 cited

Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction

Yifan Wang, Peijie Sun, Min Zhang +3

Conversion rate prediction is critical to many online applications such as digital display advertising. To capture dynamic data distribution, industrial systems often require retra…

cs.IR2023

Measuring Item Global Residual Value for Fair Recommendation

Jiayin Wang, Weizhi Ma, Chumeng Jiang +4

In the era of information explosion, numerous items emerge every day, especially in feed scenarios. Due to the limited system display slots and user browsing attention, various rec…