research-article

Neural Feature-aware Recommendation with Signed Hypergraph Convolutional Network

Authors:

Yongfeng Zhang,

Jimmy Xiangji HuangAuthors Info & Claims

ACM Transactions on Information Systems (TOIS), Volume 39, Issue 1

Article No.: 8, Pages 1 - 22

https://doi.org/10.1145/3423322

Published: 10 November 2020 Publication History

Abstract

Understanding user preference is of key importance for an effective recommender system. For comprehensive user profiling, many efforts have been devoted to extract user feature-level preference from the review information. Despite effectiveness, existing methods mostly assume linear relationships among the users, items, and features, and the collaborative information is usually utilized in an implicit and insufficient manner, which limits the recommender capacity in modeling users’ diverse preferences. For bridging this gap, in this article, we propose to formulate user feature-level preferences by a neural signed hypergraph and carefully design the information propagation paths for diffusing collaborative filtering signals in a more effective manner. By taking the advantages of the neural model’s powerful expressiveness, the complex relationship patterns among users, items, and features are sufficiently discovered and well utilized. By infusing graph structure information into the embedding process, the collaborative information is harnessed in a more explicit and effective way. We conduct comprehensive experiments on real-world datasets to demonstrate the superiorities of our model.

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Cited By

Heshmati AMeghdadi MAfsharchi MAhmadian S(2025)SiSRS: Signed social recommender system using deep neural network representation learningExpert Systems with Applications10.1016/j.eswa.2024.125205259(125205)Online publication date: Jan-2025
https://doi.org/10.1016/j.eswa.2024.125205
An JGao MTang J(2024)MvStHgL: Multi-View Hypergraph Learning with Spatial-Temporal Periodic Interests for Next POI RecommendationACM Transactions on Information Systems10.1145/366465142:6(1-29)Online publication date: 19-Aug-2024
https://dl.acm.org/doi/10.1145/3664651
Seo CJeong KLim SShin W(2024)SiReN: Sign-Aware Recommendation Using Graph Neural NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.3175772(1-15)Online publication date: 2024
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Index Terms

Neural Feature-aware Recommendation with Signed Hypergraph Convolutional Network
1. Information systems
  1. World Wide Web
    1. Web searching and information discovery
      1. Collaborative filtering
      2. Personalization

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Published In

cover image ACM Transactions on Information Systems

ACM Transactions on Information Systems Volume 39, Issue 1

January 2021

329 pages

ISSN:1046-8188

EISSN:1558-2868

DOI:10.1145/3423044

Editor:
Min Zhang
Tsinghua University, China

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Copyright © 2020 ACM.

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Publication History

Published: 10 November 2020

Accepted: 01 September 2020

Revised: 01 August 2020

Received: 01 January 2020

Published in TOIS Volume 39, Issue 1

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Natural Sciences and Engineering Research Council (NSERC) of Canada
York Research Chairs (YRC) program
Beijing Outstanding Young Scientist Program
National Natural Science Foundation of China

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Cited By

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https://doi.org/10.1016/j.eswa.2024.125205
An JGao MTang J(2024)MvStHgL: Multi-View Hypergraph Learning with Spatial-Temporal Periodic Interests for Next POI RecommendationACM Transactions on Information Systems10.1145/366465142:6(1-29)Online publication date: 19-Aug-2024
https://dl.acm.org/doi/10.1145/3664651
Seo CJeong KLim SShin W(2024)SiReN: Sign-Aware Recommendation Using Graph Neural NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.3175772(1-15)Online publication date: 2024
https://doi.org/10.1109/TNNLS.2022.3175772
Bastola RShakya S(2024)Knowledge-Enriched Graph Convolution Network for Hybrid Explainable Recommendation from Review Texts and Reasoning Path2024 International Conference on Inventive Computation Technologies (ICICT)10.1109/ICICT60155.2024.10544384(590-599)Online publication date: 24-Apr-2024
https://doi.org/10.1109/ICICT60155.2024.10544384
Shu HMeng CDe Meo PWang QZhu J(2024)Self-Supervised Hypergraph Learning for Enhanced Multimodal RepresentationIEEE Access10.1109/ACCESS.2024.336168012(20830-20839)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3361680
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Shi JShu TWu KJiang ZZheng LWang WWu HZheng Y(2024)Masked hypergraph learning for weakly supervised histopathology whole slide image classificationComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2024.108237253(108237)Online publication date: Aug-2024
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