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基于自适应双向信息流的序列推荐方法

马丽 刘文哲 李雨豪

郑州大学学报(工学版)2026,Vol.47Issue(4):100-107,8.
郑州大学学报(工学版)2026,Vol.47Issue(4):100-107,8.DOI:10.13705/j.issn.1671-6833.2026.04.003

基于自适应双向信息流的序列推荐方法

Sequential Recommendation Method Based on Adaptive Bidirectional Information Flow

马丽 1刘文哲 2李雨豪2

作者信息

  • 1. 河北地质大学 信息工程学院,河北 石家庄 052161||河北地质大学 智能传感物联网技术河北省工程研究中心,河北 石家庄 052161
  • 2. 河北地质大学 信息工程学院,河北 石家庄 052161
  • 折叠

摘要

Abstract

To address the challenges of inefficient information fusion and noise interference in sequential recommen-dation,a novel method based on an adaptive bidirectional information flow was proposed.Built upon a dual-path encoder architecture,a hierarchical history summarization module was integrated to distill long-term user prefer-ences,and dynamic frequency-domain filtering was introduced to suppress data noise.The approach fully consid-ered the dependency and interactivity between past and future information by employing an adaptive bidirectional information flow mechanism.This mechanism dynamically adjusted fusion weights via uncertainty perception,enab-ling a precise characterization of the evolution of user preferences.To validate its effectiveness,experiments were conducted on four public datasets including Beauty,Sports,Yelp,and ML1M.And a comparative analysis was performed against 10 mainstream methods.The experimental results demonstrated that the proposed method outper-formed the baseline models in three key metrics:NDCG,HR,and MRR.Compared to three leading baseline mod-els of FMLP-Rec,DualRec,and Oracle4Rec,the proposed method's HR@20 reached 0.652 0 and 0.913 3 on the Beauty and Yelp datasets,which was 2.08 percentage points and 2.89 percentage points higher than their average performance,respectively.Furthermore,its NDCG@20 on the Beauty and Yelp datasets reached 0.394 4 and 0.564 5,outperforming the average of the three baselines by 2.67 percentage points and 2.72 percentage points,respectively.

关键词

序列推荐/自适应双向信息流/动态偏好建模/频域滤波/注意力机制

Key words

sequential recommendation/adaptive bidirectional information flow/dynamic preference modeling/fre-quency-domain filtering/attention mechanism

分类

信息技术与安全科学

引用本文复制引用

马丽,刘文哲,李雨豪..基于自适应双向信息流的序列推荐方法[J].郑州大学学报(工学版),2026,47(4):100-107,8.

基金项目

国家自然科学基金资助项目(62476078) (62476078)

河北省教育科学规划课题(2303121) (2303121)

河北地质大学博士科研启动基金(BQ2017045) (BQ2017045)

郑州大学学报(工学版)

1671-6833

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