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cs.IR2025
AEFS: Adaptive Early Feature Selection for Deep Recommender Systems
Fan Hu, Gaofeng Lu, Jun Chen +3
Feature selection has emerged as a crucial technique in refining recommender systems. Recent advancements leveraging Automated Machine Learning (AutoML) has drawn significant atten…
cs.IR2024
EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations
Chiyu Zhang, Yifei Sun, Minghao Wu +9
Content-based recommendation systems play a crucial role in delivering personalized content to users in the digital world. In this work, we introduce EmbSum, a novel framework that…
cs.IR2024
SPAR: Personalized Content-Based Recommendation via Long Engagement Attention
Chiyu Zhang, Yifei Sun, Jun Chen +7
Leveraging users' long engagement histories is essential for personalized content recommendations. The success of pretrained language models (PLMs) in NLP has led to their use in e…