Uncertain Query Retrieval

Uncertain Query Retrieval is a probabilistic information retrieval framework that models query term uncertainty by integrating likelihood distributions over possible query interpretations to rank documents according to their probability of relevance under ambiguous or incomplete query conditions.

5

Publications

135

Citations

21

Authors

8

Institutions

Publications per year

2017–2026

2

Authors

21

  1. GC
    Guo Chen

    Kunming University of Science and Technology, China

    1 publications · 35 citations

    1

    h-index

  2. HK
    Hemal Khatri

    Arizona State University, United States

    1 publications · 26 citations

    1

    h-index

  3. KL
    Kenli Li

    Hunan University, China

    1 publications · 35 citations

    1

    h-index

  4. FR
    Fedor Romanenko

    Yandex (Russia), Russia

    1 publications · 16 citations

    1

    h-index

  5. PS
    Pavel Serdyukov

    Yandex (Russia), Russia

    1 publications · 16 citations

    1

    h-index

1–5 of 21

Venues

  1. Knowledge-Based Systems

    1 publications · 35 citations

    1

    h-index

  2. Neurocomputing

    1 publications · 22 citations

    1

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 1 publications · 36 citations

    1

    h-index

1–3