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Pattern Recognition and Artificial Intelligence  2024, Vol. 37 Issue (6): 513-524    DOI: 10.16451/j.cnki.issn1003-6059.202406003
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Global Consistency Augmented Multi-preference Session-Based Recommendation Model
WU Jiangming1, ZHANG Xiaokun1, XU Bo1, YANG Liang1, LIN Hongfei1
1. School of Computer Science and Technology, Dalian University of Technology, Dalian 116024

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Abstract  Session-based recommendation aims to predict the next item which a user is likely to interact with based on an anonymous session. However, existing session-based recommendation methods based on graph neural networks underutilize the global information. To address this issue, a global consistency augmented multi-preference session-based recommendation model(GCAM) is proposed. Firstly, a consistent global graph is constructed through the shortest path routing algorithm. The consistency of global information is ensured by capturing reliable item relationships and filtering out unreliable item relationships. Secondly, a multi-preference label smoothing strategy is applied to mine collaborative information from historical sessions to soften labels, and thereby the label can fit the true user preferences. Extensive experiments on three different datasets demonstrate the superiority of GCAM.
Key wordsSession-Based Recommendation      Multi-preference Learning      Self-Supervised Learning      Global Consistency Augmentation     
Received: 14 March 2024     
ZTFLH: TP 391  
Fund:National Natural Science Foundation of China(No.62076046,62006034)
Corresponding Authors: LIN Hongfei, Ph.D., professor. His research interests include natural language processing, affective computing, social media processing and information retrieval.   
About author:: WU Jiangming, Master student. His research interests include recommendation systems and natural language processing. ZHANG Xiaokun, Ph.D. candidate. His research interests include data mining and recommendation systems. XU Bo, Ph.D., associate professor. His research interests include information retrieval and natural language processing. YANG Liang, Ph.D., associate professor. His research interests include natural language processing.
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WU Jiangming
ZHANG Xiaokun
XU Bo
YANG Liang
LIN Hongfei
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WU Jiangming,ZHANG Xiaokun,XU Bo等. Global Consistency Augmented Multi-preference Session-Based Recommendation Model[J]. Pattern Recognition and Artificial Intelligence, 2024, 37(6): 513-524.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202406003      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2024/V37/I6/513
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