research-article

Hierarchical Social Similarity-guided Model with Dual-mode Attention for session-based recommendation

Authors:

Daohua YuAuthors Info & Claims

Volume 230, Issue C

https://doi.org/10.1016/j.knosys.2021.107380

Published: 27 October 2021 Publication History

Abstract

Session-based recommendation models users’ interests in sessions to make recommendations. Many previous studies have shown that users usually have similar interests to their friends, and are easily influenced by friends. However, these studies also tend to ignore the fact that users’ interests may merely be similar to certain friends’ interests in certain aspects. To address the above issues, we propose a novel Hierarchical Social Similarity-guided Model with Dual-mode Attention (HMDA) for Session-based Recommendation. Specifically, we first calculate the item-level similarity between users and their friends to select influential friends. We then compute the aspect-level similarity to explore the aspect difference between users’ interests and friends’ interests. Under the guidance of the item-level and aspect-level similarity, HMDA is capable of effectively and accurately aggregating the social influence exerted by friends on users, and further combining users’ individual interests to enhance recommendation performance. In addition, we design a dual-mode attention mechanism to capture the internal dependence and mutual dependence between the long-term and short-term interests of users. The proposed model is extensively evaluated on three real-world datasets. Experimental results demonstrate that our model outperforms the state-of-the-art baseline methods.

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Cited By

Gan MWang CYi LGu H(2024)Exploiting dynamic social feedback for session-based recommendationInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10363261:3Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.ipm.2023.103632
Sang SYuan WLi WYang ZZhang ZLiu N(2023)Position-aware graph neural network for session-based recommendationKnowledge-Based Systems10.1016/j.knosys.2022.110201262:COnline publication date: 28-Feb-2023
https://dl.acm.org/doi/10.1016/j.knosys.2022.110201
Oh BSuh ICha KKim JPark GJeong S(2023)Pre-training local and non-local geographical influences with contrastive learningKnowledge-Based Systems10.1016/j.knosys.2022.110016259:COnline publication date: 10-Jan-2023
https://dl.acm.org/doi/10.1016/j.knosys.2022.110016
Show More Cited By

Index Terms

Hierarchical Social Similarity-guided Model with Dual-mode Attention for session-based recommendation
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
  2. Information systems applications
    1. Data mining

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 230, Issue C

Oct 2021

279 pages

ISSN:0950-7051

Issue’s Table of Contents

Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 27 October 2021

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Cited By

Gan MWang CYi LGu H(2024)Exploiting dynamic social feedback for session-based recommendationInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10363261:3Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.ipm.2023.103632
Sang SYuan WLi WYang ZZhang ZLiu N(2023)Position-aware graph neural network for session-based recommendationKnowledge-Based Systems10.1016/j.knosys.2022.110201262:COnline publication date: 28-Feb-2023
https://dl.acm.org/doi/10.1016/j.knosys.2022.110201
Oh BSuh ICha KKim JPark GJeong S(2023)Pre-training local and non-local geographical influences with contrastive learningKnowledge-Based Systems10.1016/j.knosys.2022.110016259:COnline publication date: 10-Jan-2023
https://dl.acm.org/doi/10.1016/j.knosys.2022.110016
Li ZAmagata DZhang YMaekawa THara TYonekawa KKurokawa M(2022)HML4RecKnowledge-Based Systems10.1016/j.knosys.2022.109674255:COnline publication date: 14-Nov-2022
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Jiang XZhang QShi CJiang KHu LWang S(2022)An Ion Exchange Mechanism Inspired Story Ending Generator for Different CharactersMachine Learning and Knowledge Discovery in Databases10.1007/978-3-031-26390-3_32(553-570)Online publication date: 19-Sep-2022
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