MHGNN: Hybrid Graph Neural Network with Mixers for Multi-interest Session-Aware Recommendation

Mingyu Cui; Zhaohui Peng; Yaohui Chu; Jikun Lu; Yashu Tan

doi:10.1007/978-981-97-7235-3_8

ScienceGate Book Chapters

BOOK-CHAPTER

MHGNN: Hybrid Graph Neural Network with Mixers for Multi-interest Session-Aware Recommendation

Mingyu Cui Zhaohui Peng Yaohui Chu Jikun Lu Yashu Tan

Year: 2024 Lecture notes in computer science Pages: 115-129 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-97-7235-3_8

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Session (web analytics) Artificial neural network Graph Computer network Artificial intelligence Theoretical computer science World Wide Web

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.36

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Recommender Systems and Techniques

Physical Sciences → Computer Science → Information Systems

Advanced Graph Neural Networks

Physical Sciences → Computer Science → Artificial Intelligence

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

MHGNN: Hybrid Graph Neural Network with Mixers for Multi-interest Session-Aware Recommendation

Metrics

Topics

Related Documents

Dynamic Multi-Interest Graph Neural Network for Session-Based Recommendation

Enhancing Session-Based Recommendation with Multi-granularity User Interest-Aware Graph Neural Networks

Multi-level category-aware graph neural network for session-based recommendation

Category-aware Graph Neural Network for Session-based Recommendation

Position-aware graph neural network for session-based recommendation