activity
20242026
most citedCategory-based and Popularity-guided Video Game Recommendation: A Balance-oriented Framework

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.IR20261 cited

Category-based and Popularity-guided Video Game Recommendation: A Balance-oriented Framework

Xiping Li, Jianghong Ma, Kangzhe Liu +3

In recent years, the video game industry has experienced substantial growth, presenting players with a vast array of game choices. This surge in options has spurred the need for a…

cs.IR2026

CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations

Xiping Li, Aier Yang, Jianghong Ma +4

The rapid expansion of gaming industry requires advanced recommender systems tailored to its dynamic landscape. Existing Graph Neural Network (GNN)-based methods primarily prioriti…

cs.IR2025

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects

Zihan Hong, Yushi Wu, Zhiting Zhao +4

With the recent progress in generative artificial intelligence (Generative AI), particularly in the development of large language models, recommendation systems are evolving to bec…

cs.LG2025

Multi-Hierarchical Fine-Grained Feature Mapping Driven by Feature Contribution for Molecular Odor Prediction

Hong Xin Xie, Jian De Sun, Fan Fu Xue +3

Molecular odor prediction is the process of using a molecule's structure to predict its smell. While accurate prediction remains challenging, AI models can suggest potential odors.…

cs.AI2024

IDVT: Interest-aware Denoising and View-guided Tuning for Social Recommendation

Dezhao Yang, Jianghong Ma, Shanshan Feng +2

In the information age, recommendation systems are vital for efficiently filtering information and identifying user preferences. Online social platforms have enriched these systems…