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Junlin Zhu

Biographic Data

ID8354638
NAMEJunlin Zhu
GIVEN NAMESJunlin
FAMILY NAMEZhu
SIGNATUREZHU J
AFFILIATIONSChongqing University of Technology
ORCID0000-0002-0735-8983
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2024
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Reverse supply chain recycling decisions via Pigovian theory

    Open Access•Xingwei Li, Yi Zhang et al.•ARTICLE•Socio-Economic Planning Sciences•2026

  • Frequency Meets Intent

    Open Access•Jiahao Hu, Wei Zhou et al.•ARTICLE•IEEE Transactions on Computational…•2026

  • Deep learning-based research on cultural symbols in few-shot destination social media images

    Xiaodou Huang, Sheng Ye et al.•ARTICLE•Tourism Recreation Research•2026

    In the digital age, cultural heritage sites utilise social media imagery for marketing. Nevertheless, existing research reveals two gaps: the scarcity of methods for accurately identifying multi-cultural element fusion in images under few-shot conditions; and the difficulty in quantifying their collective impact on user behaviour, which limits data-driven content strategy optimisation. Grounded in destination image theory and symbolic consumption…

  • Leveraging Hyperbolic Dynamic Neural Networks for Knowledge-Aware Recommendation

    Open Access•Yihao Zhang, Kaibei Li et al.•ARTICLE•IEEE Transactions on Computational…•2024

    Knowledge graph (KG) is of growing significance in enabling explainable recommendations. Recent research works involve constructing propagation-based recommendation models. Nevertheless, most of the current propagation-based recommendation methods cannot explicitly handle the diverse relations of items, resulting in the inability to model the underlying hierarchies and diverse relations, and it is difficult to capture the high-order collaborative…

No prominent works on this page.

  • Leveraging Hyperbolic Dynamic Neural Networks for Knowledge-Aware Recommendation

    Open Access•Yihao Zhang, Kaibei Li et al.•ARTICLE•IEEE Transactions on Computational…•2024

    Knowledge graph (KG) is of growing significance in enabling explainable recommendations. Recent research works involve constructing propagation-based recommendation models. Nevertheless, most of the current propagation-based recommendation methods cannot explicitly handle the diverse relations of items, resulting in the inability to model the underlying hierarchies and diverse relations, and it is difficult to capture the high-order collaborative…

  • Reverse supply chain recycling decisions via Pigovian theory

    Open Access•Xingwei Li, Yi Zhang et al.•ARTICLE•Socio-Economic Planning Sciences•2026

  • Frequency Meets Intent

    Open Access•Jiahao Hu, Wei Zhou et al.•ARTICLE•IEEE Transactions on Computational…•2026

  • Deep learning-based research on cultural symbols in few-shot destination social media images

    Xiaodou Huang, Sheng Ye et al.•ARTICLE•Tourism Recreation Research•2026

    In the digital age, cultural heritage sites utilise social media imagery for marketing. Nevertheless, existing research reveals two gaps: the scarcity of methods for accurately identifying multi-cultural element fusion in images under few-shot conditions; and the difficulty in quantifying their collective impact on user behaviour, which limits data-driven content strategy optimisation. Grounded in destination image theory and symbolic consumption…

Recommender Systems and Techniques (2 works) · Advanced Graph Neural Networks (1 work) · Advanced Technologies in Various Fields (1 work) · Artificial Intelligence (1 work) · Artificial neural network (1 work) · Bipartite graph (1 work) · Collaborative filtering (1 work) · Computer Science (1 work) · Contrastive analysis (1 work) · Cultural heritage (1 work)

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