Intent-aware Retrieval

Intent-Aware Retrieval is a knowledge retrieval paradigm that identifies and leverages the underlying user intent to guide the selection and ranking of relevant information, thereby distinguishing itself from context- or keyword-based retrieval methods by explicitly modeling intentional semantics.

69

Publications

3K

Citations

221

Authors

95

Institutions

Publications per year

2017–2026

21

Authors

221

  1. TS
    Tetsuya Sakai

    Waseda University, Japan

    7 publications · 277 citations

    7

    h-index

  2. ZD
    Zhicheng Dou

    Renmin University of China, China

    7 publications · 222 citations

    7

    h-index

  3. JW
    Ji-Rong Wen

    Renmin University of China, China

    4 publications · 147 citations

    4

    h-index

  4. NC
    Nick Craswell

    Microsoft (United States), United States

    2 publications · 253 citations

    2

    h-index

  5. CF
    Chen Fu

    Accenture (United States), United States

    2 publications · 267 citations

    2

    h-index

1–5 of 221

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 69 citations

    2

    h-index

  2. MDPI (MDPI AG)

    Repository · 1 publications · 14 citations

    1

    h-index

  3. Journal of Computer Science and Technology

    1 publications · 14 citations

    1

    h-index

  4. Archives of biochemistry

    1 publications · 50 citations

    1

    h-index

  5. 1

    h-index

1–5