首页|Fu-Rec:Multi-Task Learning Recommendation Model Fusing Neighbor-Discrimination and Self-Discrimination

Fu-Rec:Multi-Task Learning Recommendation Model Fusing Neighbor-Discrimination and Self-Discrimination

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In recent years,self-supervised learning has achieved great success in areas such as computer vision and natural language pro-cessing because it can mine supervised signals from unlabeled data and reduce the reliance on manual labels.However,the currently gener-ated self-supervised signals are either neighbor discrimination or self-discrimination,and there is no model to integrate neighbor discrimi-nation and self-discrimination.Based on this,this paper proposes Fu-Rec that integrates neighbor-discrimination contrastive learning and self-discrimination contrastive learning,which consists of three modules:(1)neighbor-discrimination contrastive learning,(2)self-discrimination contrastive learning,and(3)recommendation module.The neighbor-discrimination contrastive learning and self-discrimination contrastive learning tasks are used as auxiliary tasks to assist the recommendation task.The Fu-Rec model effectively uti-lizes the respective advantages of neighbor-discrimination and self-discrimination to consider the information of the user's neighbors as well as the user and the item itself for the recommendation,which results in better performance of the recommendation module.Experi-mental results on several public datasets demonstrate the effectiveness of the Fu-Rec proposed in this paper.

self-supervised learningrecommendation systemcontrastive learningmulti-task learning

ZHENG Sirui、HUANG Bo、LIU Jin、ZENG Guohui、YIN Ling、LI Zhi、SUN Tie

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School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201600,China

School of Computer,Wuhan University,Wuhan 430072,Hubei,China

School of Computer Science and Engineering,Guangxi Normal University,Guilin 541004,Guangxi,China

AIoT Manufacturing Solutions Technology Co.,Ltd.,Hefei 230000,Anhui,China

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Scientific and Technological Innovation 2030-Major Project of New Generation Artificial Intelligencescience and Technology Commission of Shanghai Municipality2023 Anhui Province Key Research and Development Plan Project-Special Project of Science and Technology Cooperation

2020AAA010930021DZ22031002023i11020002

2024

10.1051/wujns/2024292134

武汉大学自然科学学报(英文版)
武汉大学

武汉大学自然科学学报(英文版)

CSTPCD
影响因子：0.066
ISSN：1007-1202
年,卷(期)：2024.29(2)
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