融合情感的异构图神经网络音乐会话推荐算法

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本文引用格式：，.融合情感的异构图神经网络音乐会话推荐算法[J].自动化与信息工程，2025，46（3）：9-16

LU Zhenye， DU Yuxiao. Emotion-enhanced heterogeneous graph neural network for music session-based recommendation algorithm[J]. Automation& Information Engineering，2025，46（3）：9-16.

关键词：会话推荐；异构图神经网络；音乐情感；匿名用户推荐中图分类号：TP391.3 文献标志码：A 文章编号：1674-2605（2025）03-0002-08DOI： 10.12475/aie.20250302 开放获取

Emotion-enhanced Heterogeneous Graph Neural Network for Music Session-based Recommendation Algorithm

LU Zhenye DU Yuxiao （School of Automation， Guangdong University of Technology， Guangzhou 510oo6， China）

Abstract： To addressthe limitations ofcurrent music session-based recommendation methods foranonymous or new users such a simplisticrecommendations based solelyon short-term sesions and neglect ofemotional factors influencinguserchoices this studyproposes anemotion-enhanced heterogeneous graph neuralnetwork for music sesson-basedrecommendationalgorithm. Thealgorithmconstructsasession-basedrecommendationsystemusinghistoricaldatafromallusersandcurentsessionsviagraph neural networks，integratingmusical emotional semantics toprovide more acuraterecommendationsforanonymous/nwusers. ExperimentalresultsontheNowplayingdatasetdemonstrate thatcomparedtothesuboptimal GNN-basedesionrecommedation method， the proposed algorithm achieves a 2.1% improvement in P@20 and a 6.8% increase in MRR @20 ， effectively enhancing recommendation performance.

Keywords： sesion-based recommendation; heterogeneous graph neural network; music emotion; anonymous user recommendation

0 引言

信息技术的飞速发展，如5G、智能手机、云服务等，为音乐传播带来了前所未有的机遇。（剩余10234字）