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DynamicRec: A Dynamic Convolutional Network for Next Item Recommendation

Authors:

Md Mehrab Tanjim,

Hammad A. Ayuubi,

Garrison W. CottrellAuthors Info & Claims

CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management

Pages 2237 - 2240

https://doi.org/10.1145/3340531.3412118

Published: 19 October 2020 Publication History

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Abstract

Recently convolutional networks have shown significant promise for modeling sequential user interactions for recommendations. Critically, such networks rely on fixed convolutional kernels to capture sequential behavior. In this paper, we argue that all the dynamics of the item-to-item transition in session-based settings may not be observable at training time. Hence we propose DynamicRec, which uses dynamic convolutions to compute the convolutional kernels on the fly based on the current input. We show through experiments that this approach significantly outperforms existing convolutional models on real datasets in session-based settings.

Supplementary Material

MP4 File (3340531.3412118.mp4)

This video shows the presentation of the work DynamicRec which uses dynamic convolution to recommend items in session-based settings. Here, the author has gone through the model architecture, its performance compared to strong state-of-the-art baselines, and the importance of its various components.

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Cited By

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Chen ZXie DWang XYou DShen L(2025)High-order complementary cloud application programming interface recommendation with logical reasoning for incremental developmentEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.109698140:COnline publication date: 15-Jan-2025
https://dl.acm.org/doi/10.1016/j.engappai.2024.109698
Wang BZhang YLong WCui Z(2024)Joint features-guided linear transformer and CNN for efficient image super-resolutionInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02277-215:12(5765-5780)Online publication date: 9-Jul-2024
https://doi.org/10.1007/s13042-024-02277-2
Feng YWen WHao ZCai R(2024)Time-aware tensor factorization for temporal recommendationApplied Intelligence10.1007/s10489-024-05851-x55:1Online publication date: 27-Nov-2024
https://doi.org/10.1007/s10489-024-05851-x
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Index Terms

DynamicRec: A Dynamic Convolutional Network for Next Item Recommendation
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Learning to rank
    2. Machine learning approaches
      1. Neural networks
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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Information & Contributors

Information

Published In

CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management

October 2020

3619 pages

ISBN:9781450368599

DOI:10.1145/3340531

General Chairs:
Mathieu d'Aquin
DSI, Insight, NUI Galway, Ireland
,
Stefan Dietze
GESIS, Cologne, Germany, Heinrich-Heine-University Düsseldorf, Germany, L3S Research Center, Germany
,
Program Chairs:
Claudia Hauff
TU Delft, The Netherlands
,
Edward Curry
DSI, Insight, NUI Galway, Ireland
,
Philippe Cudre Mauroux
eXascale, University of Fribourg, Switzerland

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 October 2020

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CIKM '20

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CIKM '20: The 29th ACM International Conference on Information and Knowledge Management

October 19 - 23, 2020

Virtual Event, Ireland

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

View all

Chen ZXie DWang XYou DShen L(2025)High-order complementary cloud application programming interface recommendation with logical reasoning for incremental developmentEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.109698140:COnline publication date: 15-Jan-2025
https://dl.acm.org/doi/10.1016/j.engappai.2024.109698
Wang BZhang YLong WCui Z(2024)Joint features-guided linear transformer and CNN for efficient image super-resolutionInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02277-215:12(5765-5780)Online publication date: 9-Jul-2024
https://doi.org/10.1007/s13042-024-02277-2
Feng YWen WHao ZCai R(2024)Time-aware tensor factorization for temporal recommendationApplied Intelligence10.1007/s10489-024-05851-x55:1Online publication date: 27-Nov-2024
https://doi.org/10.1007/s10489-024-05851-x
Wu BHe XZhang QWang MYe Y(2023)GCRec: Graph-Augmented Capsule Network for Next-Item RecommendationIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.316498234:12(10164-10177)Online publication date: Dec-2023
https://doi.org/10.1109/TNNLS.2022.3164982
Wu BZhong LYe Y(2023)Graph-Augmented Social Translation Model for Next-Item RecommendationIEEE Transactions on Industrial Informatics10.1109/TII.2023.324280919:11(10913-10922)Online publication date: Nov-2023
https://doi.org/10.1109/TII.2023.3242809
Kang MZhu JZhang RPark JShechtman EParis SPark T(2023)Scaling up GANs for Text-to-Image Synthesis2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.00976(10124-10134)Online publication date: Jun-2023
https://doi.org/10.1109/CVPR52729.2023.00976
Li QXu XLiu JLi G(2022)Learning Sequential General Pattern and Dependency via Hybrid Neural Model for Session-Based RecommendationIEEE Access10.1109/ACCESS.2022.320124410(89634-89644)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3201244
He MHan TDing T(2022)Multilevel Feature Interaction Learning for Session-Based Recommendation via Graph Neural NetworksWeb Engineering10.1007/978-3-031-09917-5_3(31-46)Online publication date: 5-Jul-2022
https://dl.acm.org/doi/10.1007/978-3-031-09917-5_3
Zang YLiu YChen WLi BLi AYue LMa W(2022)GISDCN: A Graph-Based Interpolation Sequential Recommender with Deformable Convolutional NetworkDatabase Systems for Advanced Applications10.1007/978-3-031-00126-0_21(289-297)Online publication date: 11-Apr-2022
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Gupta GKatarya R(2022)A novel approach to alleviate data sparsity and generate dynamic fruit recommendations from point‐of‐sale dataConcurrency and Computation: Practice and Experience10.1002/cpe.742335:1Online publication date: 21-Oct-2022
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