Attention-based Matching

Attention-Based Matching is a message matching method that employs attention mechanisms to dynamically align and weigh relevant parts of messages by focusing on contextually significant features, thereby enhancing correspondence accuracy through adaptive relevance scoring.

104

Publications

7.5K

Citations

381

Authors

121

Institutions

Publications per year

2017–2026

93

Authors

381

  1. AL
    An-An Liu

    Tianjin University, China

    4 publications · 131 citations

    4

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  2. JH
    Jungong Han

    Lancaster University, United Kingdom

    4 publications · 572 citations

    4

    h-index

  3. LW
    Liang Wang

    Chinese Academy of Sciences, China

    4 publications · 363 citations

    4

    h-index

  4. YL
    Yang Liu

    Nanyang Technological University, Singapore

    3 publications · 257 citations

    3

    h-index

  5. LM
    Lin Ma

    Tencent (China), China

    3 publications · 562 citations

    3

    h-index

1–5 of 381

Venues

  1. arXiv (Cornell University)

    Repository · 16 publications · 778 citations

    12

    h-index

  2. IEEE Transactions on Image Processing

    8 publications · 390 citations

    8

    h-index

  3. Pattern Recognition

    5 publications · 167 citations

    5

    h-index

  4. 3

    h-index

  5. 3

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1–5