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Multi-modal Behavioral Information-Aware Recommendation with Recurrent Neural Networks

  • Guoyong CaiEmail author
  • Nannan Chen
  • Weidong Gu
  • Jiao Pan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 895)

Abstract

Data sparsity is one of the most challenging problems in recommendation systems. In this paper, we tackle this problem by proposing a novel multi-modal behavioral information-aware recommendation method named MIAR which is based on recurrent neural networks and matrix factorization. First, an interaction context-aware sequential prediction model is designed to capture user-item interaction contextual information and behavioral sequence information. Second, an attributed context-aware rating prediction model is proposed to capture attribution contextual information and rating information. Finally, three fusion methods are developed to combine two sub-models. As a result, the MIAR method has several distinguished advantages in terms of mitigating the data sparsity problem. The method can well perceive diverse influences of interaction and attribution contextual information. Meanwhile, a large number of behavioral sequence and rating information can be utilized by the MIAR approach. The proposed algorithm is evaluated on real-world datasets and the experimental results show that MIAR can significantly improve recommendation performance compared to the existing state-of-art recommendation algorithms.

Keywords

Data sparsity Multi-modal information Recommendation Recurrent neural networks 

Notes

Acknowledgments

This work is supported by the Chinese National Science Foundation (#61763007), the Guilin Science and Technology Project (20170113-6) and the Guangxi Natural Science Foundation (#2017JJD160017).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Guoyong Cai
    • 1
    Email author
  • Nannan Chen
    • 1
  • Weidong Gu
    • 1
  • Jiao Pan
    • 2
  1. 1.Guangxi Key Lab of Trusted SoftwareGuilin University of Electronic TechnologyGuilinChina
  2. 2.Guilin Kaige Information Technology Co. Ltd.GuilinChina

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