activity
20202026
most citedCapturing Popularity Trends: A Simplistic Non-Personalized Approach for Enhanced Item Recommendation

9 citations · 11 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2026

Following the TRAIL: Predicting and Explaining Tomorrow's Hits with a Fine-Tuned LLM

Yinan Zhang, Zhixi Chen, Jiazheng Jing +1

Large Language Models (LLMs) have been widely applied across multiple domains for their broad knowledge and strong reasoning capabilities. However, applying them to recommendation…

cs.IR2025

Bites of Tomorrow: Personalized Recommendations for a Healthier and Greener Plate

Jiazheng Jing, Yinan Zhang, Chunyan Miao

The recent emergence of extreme climate events has significantly raised awareness about sustainable living. In addition to developing energy-saving materials and technologies, exis…

cs.CL2024

Enabling Patient-side Disease Prediction via the Integration of Patient Narratives

Zhixiang Su, Yinan Zhang, Jiazheng Jing +2

Disease prediction holds considerable significance in modern healthcare, because of its crucial role in facilitating early intervention and implementing effective prevention measur…

cs.IR2023★ 9 cited

Capturing Popularity Trends: A Simplistic Non-Personalized Approach for Enhanced Item Recommendation

Jiazheng Jing, Yinan Zhang, Xin Zhou +1

Recommender systems have been gaining increasing research attention over the years. Most existing recommendation methods focus on capturing users' personalized preferences through…

cs.IR2020★ 2 cited

Enhancing Factorization Machines with Generalized Metric Learning

Yangyang Guo, Zhiyong Cheng, Jiazheng Jing +3

Factorization Machines (FMs) are effective in incorporating side information to overcome the cold-start and data sparsity problems in recommender systems. Traditional FMs adopt the…